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https://github.com/c64scene-ar/llvm-6502.git
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582e77af02
git-svn-id: https://llvm.org/svn/llvm-project/llvm/trunk@229651 91177308-0d34-0410-b5e6-96231b3b80d8
5145 lines
194 KiB
C++
5145 lines
194 KiB
C++
//===- LoopVectorize.cpp - A Loop Vectorizer ------------------------------===//
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//
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// The LLVM Compiler Infrastructure
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//
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// This file is distributed under the University of Illinois Open Source
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// License. See LICENSE.TXT for details.
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//
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//===----------------------------------------------------------------------===//
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//
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// This is the LLVM loop vectorizer. This pass modifies 'vectorizable' loops
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// and generates target-independent LLVM-IR.
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// The vectorizer uses the TargetTransformInfo analysis to estimate the costs
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// of instructions in order to estimate the profitability of vectorization.
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//
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// The loop vectorizer combines consecutive loop iterations into a single
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// 'wide' iteration. After this transformation the index is incremented
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// by the SIMD vector width, and not by one.
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//
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// This pass has three parts:
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// 1. The main loop pass that drives the different parts.
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// 2. LoopVectorizationLegality - A unit that checks for the legality
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// of the vectorization.
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// 3. InnerLoopVectorizer - A unit that performs the actual
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// widening of instructions.
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// 4. LoopVectorizationCostModel - A unit that checks for the profitability
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// of vectorization. It decides on the optimal vector width, which
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// can be one, if vectorization is not profitable.
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//
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//===----------------------------------------------------------------------===//
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//
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// The reduction-variable vectorization is based on the paper:
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// D. Nuzman and R. Henderson. Multi-platform Auto-vectorization.
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//
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// Variable uniformity checks are inspired by:
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// Karrenberg, R. and Hack, S. Whole Function Vectorization.
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//
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// Other ideas/concepts are from:
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// A. Zaks and D. Nuzman. Autovectorization in GCC-two years later.
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//
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// S. Maleki, Y. Gao, M. Garzaran, T. Wong and D. Padua. An Evaluation of
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// Vectorizing Compilers.
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//
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//===----------------------------------------------------------------------===//
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#include "llvm/Transforms/Vectorize.h"
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#include "llvm/ADT/DenseMap.h"
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#include "llvm/ADT/EquivalenceClasses.h"
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#include "llvm/ADT/Hashing.h"
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#include "llvm/ADT/MapVector.h"
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#include "llvm/ADT/SetVector.h"
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#include "llvm/ADT/SmallPtrSet.h"
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#include "llvm/ADT/SmallSet.h"
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#include "llvm/ADT/SmallVector.h"
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#include "llvm/ADT/Statistic.h"
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#include "llvm/ADT/StringExtras.h"
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#include "llvm/Analysis/AliasAnalysis.h"
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#include "llvm/Analysis/AliasSetTracker.h"
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#include "llvm/Analysis/AssumptionCache.h"
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#include "llvm/Analysis/BlockFrequencyInfo.h"
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#include "llvm/Analysis/CodeMetrics.h"
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#include "llvm/Analysis/LoopAccessAnalysis.h"
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#include "llvm/Analysis/LoopInfo.h"
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#include "llvm/Analysis/LoopIterator.h"
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#include "llvm/Analysis/LoopPass.h"
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#include "llvm/Analysis/ScalarEvolution.h"
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#include "llvm/Analysis/ScalarEvolutionExpander.h"
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#include "llvm/Analysis/ScalarEvolutionExpressions.h"
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#include "llvm/Analysis/TargetTransformInfo.h"
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#include "llvm/Analysis/ValueTracking.h"
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#include "llvm/IR/Constants.h"
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#include "llvm/IR/DataLayout.h"
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#include "llvm/IR/DebugInfo.h"
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#include "llvm/IR/DerivedTypes.h"
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#include "llvm/IR/DiagnosticInfo.h"
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#include "llvm/IR/Dominators.h"
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#include "llvm/IR/Function.h"
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#include "llvm/IR/IRBuilder.h"
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#include "llvm/IR/Instructions.h"
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#include "llvm/IR/IntrinsicInst.h"
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#include "llvm/IR/LLVMContext.h"
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#include "llvm/IR/Module.h"
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#include "llvm/IR/PatternMatch.h"
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#include "llvm/IR/Type.h"
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#include "llvm/IR/Value.h"
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#include "llvm/IR/ValueHandle.h"
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#include "llvm/IR/Verifier.h"
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#include "llvm/Pass.h"
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#include "llvm/Support/BranchProbability.h"
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#include "llvm/Support/CommandLine.h"
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#include "llvm/Support/Debug.h"
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#include "llvm/Support/raw_ostream.h"
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#include "llvm/Transforms/Scalar.h"
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#include "llvm/Transforms/Utils/BasicBlockUtils.h"
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#include "llvm/Transforms/Utils/Local.h"
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#include "llvm/Transforms/Utils/VectorUtils.h"
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#include <algorithm>
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#include <map>
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#include <tuple>
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using namespace llvm;
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using namespace llvm::PatternMatch;
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#define LV_NAME "loop-vectorize"
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#define DEBUG_TYPE LV_NAME
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STATISTIC(LoopsVectorized, "Number of loops vectorized");
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STATISTIC(LoopsAnalyzed, "Number of loops analyzed for vectorization");
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static cl::opt<unsigned>
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VectorizationFactor("force-vector-width", cl::init(0), cl::Hidden,
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cl::desc("Sets the SIMD width. Zero is autoselect."));
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static cl::opt<unsigned>
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VectorizationInterleave("force-vector-interleave", cl::init(0), cl::Hidden,
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cl::desc("Sets the vectorization interleave count. "
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"Zero is autoselect."));
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static cl::opt<bool>
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EnableIfConversion("enable-if-conversion", cl::init(true), cl::Hidden,
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cl::desc("Enable if-conversion during vectorization."));
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/// We don't vectorize loops with a known constant trip count below this number.
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static cl::opt<unsigned>
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TinyTripCountVectorThreshold("vectorizer-min-trip-count", cl::init(16),
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cl::Hidden,
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cl::desc("Don't vectorize loops with a constant "
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"trip count that is smaller than this "
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"value."));
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/// This enables versioning on the strides of symbolically striding memory
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/// accesses in code like the following.
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/// for (i = 0; i < N; ++i)
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/// A[i * Stride1] += B[i * Stride2] ...
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///
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/// Will be roughly translated to
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/// if (Stride1 == 1 && Stride2 == 1) {
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/// for (i = 0; i < N; i+=4)
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/// A[i:i+3] += ...
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/// } else
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/// ...
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static cl::opt<bool> EnableMemAccessVersioning(
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"enable-mem-access-versioning", cl::init(true), cl::Hidden,
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cl::desc("Enable symblic stride memory access versioning"));
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/// We don't unroll loops with a known constant trip count below this number.
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static const unsigned TinyTripCountUnrollThreshold = 128;
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/// When performing memory disambiguation checks at runtime do not make more
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/// than this number of comparisons.
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static const unsigned RuntimeMemoryCheckThreshold = 8;
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/// Maximum simd width.
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static const unsigned MaxVectorWidth = 64;
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static cl::opt<unsigned> ForceTargetNumScalarRegs(
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"force-target-num-scalar-regs", cl::init(0), cl::Hidden,
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cl::desc("A flag that overrides the target's number of scalar registers."));
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static cl::opt<unsigned> ForceTargetNumVectorRegs(
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"force-target-num-vector-regs", cl::init(0), cl::Hidden,
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cl::desc("A flag that overrides the target's number of vector registers."));
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/// Maximum vectorization interleave count.
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static const unsigned MaxInterleaveFactor = 16;
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static cl::opt<unsigned> ForceTargetMaxScalarInterleaveFactor(
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"force-target-max-scalar-interleave", cl::init(0), cl::Hidden,
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cl::desc("A flag that overrides the target's max interleave factor for "
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"scalar loops."));
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static cl::opt<unsigned> ForceTargetMaxVectorInterleaveFactor(
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"force-target-max-vector-interleave", cl::init(0), cl::Hidden,
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cl::desc("A flag that overrides the target's max interleave factor for "
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"vectorized loops."));
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static cl::opt<unsigned> ForceTargetInstructionCost(
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"force-target-instruction-cost", cl::init(0), cl::Hidden,
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cl::desc("A flag that overrides the target's expected cost for "
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"an instruction to a single constant value. Mostly "
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"useful for getting consistent testing."));
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static cl::opt<unsigned> SmallLoopCost(
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"small-loop-cost", cl::init(20), cl::Hidden,
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cl::desc("The cost of a loop that is considered 'small' by the unroller."));
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static cl::opt<bool> LoopVectorizeWithBlockFrequency(
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"loop-vectorize-with-block-frequency", cl::init(false), cl::Hidden,
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cl::desc("Enable the use of the block frequency analysis to access PGO "
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"heuristics minimizing code growth in cold regions and being more "
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"aggressive in hot regions."));
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// Runtime unroll loops for load/store throughput.
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static cl::opt<bool> EnableLoadStoreRuntimeUnroll(
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"enable-loadstore-runtime-unroll", cl::init(true), cl::Hidden,
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cl::desc("Enable runtime unrolling until load/store ports are saturated"));
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/// The number of stores in a loop that are allowed to need predication.
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static cl::opt<unsigned> NumberOfStoresToPredicate(
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"vectorize-num-stores-pred", cl::init(1), cl::Hidden,
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cl::desc("Max number of stores to be predicated behind an if."));
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static cl::opt<bool> EnableIndVarRegisterHeur(
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"enable-ind-var-reg-heur", cl::init(true), cl::Hidden,
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cl::desc("Count the induction variable only once when unrolling"));
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static cl::opt<bool> EnableCondStoresVectorization(
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"enable-cond-stores-vec", cl::init(false), cl::Hidden,
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cl::desc("Enable if predication of stores during vectorization."));
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static cl::opt<unsigned> MaxNestedScalarReductionUF(
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"max-nested-scalar-reduction-unroll", cl::init(2), cl::Hidden,
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cl::desc("The maximum unroll factor to use when unrolling a scalar "
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"reduction in a nested loop."));
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namespace {
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// Forward declarations.
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class LoopVectorizationLegality;
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class LoopVectorizationCostModel;
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class LoopVectorizeHints;
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/// InnerLoopVectorizer vectorizes loops which contain only one basic
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/// block to a specified vectorization factor (VF).
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/// This class performs the widening of scalars into vectors, or multiple
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/// scalars. This class also implements the following features:
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/// * It inserts an epilogue loop for handling loops that don't have iteration
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/// counts that are known to be a multiple of the vectorization factor.
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/// * It handles the code generation for reduction variables.
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/// * Scalarization (implementation using scalars) of un-vectorizable
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/// instructions.
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/// InnerLoopVectorizer does not perform any vectorization-legality
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/// checks, and relies on the caller to check for the different legality
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/// aspects. The InnerLoopVectorizer relies on the
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/// LoopVectorizationLegality class to provide information about the induction
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/// and reduction variables that were found to a given vectorization factor.
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class InnerLoopVectorizer {
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public:
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InnerLoopVectorizer(Loop *OrigLoop, ScalarEvolution *SE, LoopInfo *LI,
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DominatorTree *DT, const DataLayout *DL,
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const TargetLibraryInfo *TLI, unsigned VecWidth,
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unsigned UnrollFactor)
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: OrigLoop(OrigLoop), SE(SE), LI(LI), DT(DT), DL(DL), TLI(TLI),
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VF(VecWidth), UF(UnrollFactor), Builder(SE->getContext()),
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Induction(nullptr), OldInduction(nullptr), WidenMap(UnrollFactor),
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Legal(nullptr) {}
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// Perform the actual loop widening (vectorization).
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void vectorize(LoopVectorizationLegality *L) {
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Legal = L;
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// Create a new empty loop. Unlink the old loop and connect the new one.
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createEmptyLoop();
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// Widen each instruction in the old loop to a new one in the new loop.
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// Use the Legality module to find the induction and reduction variables.
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vectorizeLoop();
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// Register the new loop and update the analysis passes.
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updateAnalysis();
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}
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virtual ~InnerLoopVectorizer() {}
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protected:
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/// A small list of PHINodes.
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typedef SmallVector<PHINode*, 4> PhiVector;
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/// When we unroll loops we have multiple vector values for each scalar.
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/// This data structure holds the unrolled and vectorized values that
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/// originated from one scalar instruction.
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typedef SmallVector<Value*, 2> VectorParts;
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// When we if-convert we need create edge masks. We have to cache values so
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// that we don't end up with exponential recursion/IR.
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typedef DenseMap<std::pair<BasicBlock*, BasicBlock*>,
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VectorParts> EdgeMaskCache;
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/// \brief Add checks for strides that where assumed to be 1.
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///
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/// Returns the last check instruction and the first check instruction in the
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/// pair as (first, last).
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std::pair<Instruction *, Instruction *> addStrideCheck(Instruction *Loc);
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/// Create an empty loop, based on the loop ranges of the old loop.
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void createEmptyLoop();
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/// Copy and widen the instructions from the old loop.
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virtual void vectorizeLoop();
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/// \brief The Loop exit block may have single value PHI nodes where the
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/// incoming value is 'Undef'. While vectorizing we only handled real values
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/// that were defined inside the loop. Here we fix the 'undef case'.
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/// See PR14725.
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void fixLCSSAPHIs();
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/// A helper function that computes the predicate of the block BB, assuming
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/// that the header block of the loop is set to True. It returns the *entry*
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/// mask for the block BB.
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VectorParts createBlockInMask(BasicBlock *BB);
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/// A helper function that computes the predicate of the edge between SRC
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/// and DST.
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VectorParts createEdgeMask(BasicBlock *Src, BasicBlock *Dst);
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/// A helper function to vectorize a single BB within the innermost loop.
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void vectorizeBlockInLoop(BasicBlock *BB, PhiVector *PV);
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/// Vectorize a single PHINode in a block. This method handles the induction
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/// variable canonicalization. It supports both VF = 1 for unrolled loops and
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/// arbitrary length vectors.
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void widenPHIInstruction(Instruction *PN, VectorParts &Entry,
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unsigned UF, unsigned VF, PhiVector *PV);
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/// Insert the new loop to the loop hierarchy and pass manager
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/// and update the analysis passes.
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void updateAnalysis();
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/// This instruction is un-vectorizable. Implement it as a sequence
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/// of scalars. If \p IfPredicateStore is true we need to 'hide' each
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/// scalarized instruction behind an if block predicated on the control
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/// dependence of the instruction.
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virtual void scalarizeInstruction(Instruction *Instr,
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bool IfPredicateStore=false);
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/// Vectorize Load and Store instructions,
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virtual void vectorizeMemoryInstruction(Instruction *Instr);
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/// Create a broadcast instruction. This method generates a broadcast
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/// instruction (shuffle) for loop invariant values and for the induction
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/// value. If this is the induction variable then we extend it to N, N+1, ...
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/// this is needed because each iteration in the loop corresponds to a SIMD
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/// element.
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virtual Value *getBroadcastInstrs(Value *V);
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/// This function adds (StartIdx, StartIdx + Step, StartIdx + 2*Step, ...)
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/// to each vector element of Val. The sequence starts at StartIndex.
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virtual Value *getStepVector(Value *Val, int StartIdx, Value *Step);
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/// When we go over instructions in the basic block we rely on previous
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/// values within the current basic block or on loop invariant values.
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/// When we widen (vectorize) values we place them in the map. If the values
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/// are not within the map, they have to be loop invariant, so we simply
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/// broadcast them into a vector.
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VectorParts &getVectorValue(Value *V);
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/// Generate a shuffle sequence that will reverse the vector Vec.
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virtual Value *reverseVector(Value *Vec);
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/// This is a helper class that holds the vectorizer state. It maps scalar
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/// instructions to vector instructions. When the code is 'unrolled' then
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/// then a single scalar value is mapped to multiple vector parts. The parts
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/// are stored in the VectorPart type.
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struct ValueMap {
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/// C'tor. UnrollFactor controls the number of vectors ('parts') that
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/// are mapped.
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ValueMap(unsigned UnrollFactor) : UF(UnrollFactor) {}
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/// \return True if 'Key' is saved in the Value Map.
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bool has(Value *Key) const { return MapStorage.count(Key); }
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/// Initializes a new entry in the map. Sets all of the vector parts to the
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/// save value in 'Val'.
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/// \return A reference to a vector with splat values.
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VectorParts &splat(Value *Key, Value *Val) {
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VectorParts &Entry = MapStorage[Key];
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Entry.assign(UF, Val);
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return Entry;
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}
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///\return A reference to the value that is stored at 'Key'.
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VectorParts &get(Value *Key) {
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VectorParts &Entry = MapStorage[Key];
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if (Entry.empty())
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Entry.resize(UF);
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assert(Entry.size() == UF);
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return Entry;
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}
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private:
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/// The unroll factor. Each entry in the map stores this number of vector
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/// elements.
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unsigned UF;
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/// Map storage. We use std::map and not DenseMap because insertions to a
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/// dense map invalidates its iterators.
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std::map<Value *, VectorParts> MapStorage;
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};
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/// The original loop.
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Loop *OrigLoop;
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/// Scev analysis to use.
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ScalarEvolution *SE;
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/// Loop Info.
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LoopInfo *LI;
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/// Dominator Tree.
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DominatorTree *DT;
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/// Alias Analysis.
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AliasAnalysis *AA;
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/// Data Layout.
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const DataLayout *DL;
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/// Target Library Info.
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const TargetLibraryInfo *TLI;
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/// The vectorization SIMD factor to use. Each vector will have this many
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/// vector elements.
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unsigned VF;
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protected:
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/// The vectorization unroll factor to use. Each scalar is vectorized to this
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/// many different vector instructions.
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unsigned UF;
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/// The builder that we use
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IRBuilder<> Builder;
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// --- Vectorization state ---
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/// The vector-loop preheader.
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BasicBlock *LoopVectorPreHeader;
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/// The scalar-loop preheader.
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BasicBlock *LoopScalarPreHeader;
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/// Middle Block between the vector and the scalar.
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BasicBlock *LoopMiddleBlock;
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///The ExitBlock of the scalar loop.
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BasicBlock *LoopExitBlock;
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///The vector loop body.
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SmallVector<BasicBlock *, 4> LoopVectorBody;
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///The scalar loop body.
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BasicBlock *LoopScalarBody;
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/// A list of all bypass blocks. The first block is the entry of the loop.
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SmallVector<BasicBlock *, 4> LoopBypassBlocks;
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/// The new Induction variable which was added to the new block.
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PHINode *Induction;
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/// The induction variable of the old basic block.
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PHINode *OldInduction;
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/// Holds the extended (to the widest induction type) start index.
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Value *ExtendedIdx;
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/// Maps scalars to widened vectors.
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ValueMap WidenMap;
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EdgeMaskCache MaskCache;
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LoopVectorizationLegality *Legal;
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};
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class InnerLoopUnroller : public InnerLoopVectorizer {
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public:
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InnerLoopUnroller(Loop *OrigLoop, ScalarEvolution *SE, LoopInfo *LI,
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DominatorTree *DT, const DataLayout *DL,
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const TargetLibraryInfo *TLI, unsigned UnrollFactor) :
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InnerLoopVectorizer(OrigLoop, SE, LI, DT, DL, TLI, 1, UnrollFactor) { }
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private:
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void scalarizeInstruction(Instruction *Instr,
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bool IfPredicateStore = false) override;
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void vectorizeMemoryInstruction(Instruction *Instr) override;
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Value *getBroadcastInstrs(Value *V) override;
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Value *getStepVector(Value *Val, int StartIdx, Value *Step) override;
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Value *reverseVector(Value *Vec) override;
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};
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/// \brief Look for a meaningful debug location on the instruction or it's
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/// operands.
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static Instruction *getDebugLocFromInstOrOperands(Instruction *I) {
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if (!I)
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return I;
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|
|
|
DebugLoc Empty;
|
|
if (I->getDebugLoc() != Empty)
|
|
return I;
|
|
|
|
for (User::op_iterator OI = I->op_begin(), OE = I->op_end(); OI != OE; ++OI) {
|
|
if (Instruction *OpInst = dyn_cast<Instruction>(*OI))
|
|
if (OpInst->getDebugLoc() != Empty)
|
|
return OpInst;
|
|
}
|
|
|
|
return I;
|
|
}
|
|
|
|
/// \brief Set the debug location in the builder using the debug location in the
|
|
/// instruction.
|
|
static void setDebugLocFromInst(IRBuilder<> &B, const Value *Ptr) {
|
|
if (const Instruction *Inst = dyn_cast_or_null<Instruction>(Ptr))
|
|
B.SetCurrentDebugLocation(Inst->getDebugLoc());
|
|
else
|
|
B.SetCurrentDebugLocation(DebugLoc());
|
|
}
|
|
|
|
#ifndef NDEBUG
|
|
/// \return string containing a file name and a line # for the given loop.
|
|
static std::string getDebugLocString(const Loop *L) {
|
|
std::string Result;
|
|
if (L) {
|
|
raw_string_ostream OS(Result);
|
|
const DebugLoc LoopDbgLoc = L->getStartLoc();
|
|
if (!LoopDbgLoc.isUnknown())
|
|
LoopDbgLoc.print(L->getHeader()->getContext(), OS);
|
|
else
|
|
// Just print the module name.
|
|
OS << L->getHeader()->getParent()->getParent()->getModuleIdentifier();
|
|
OS.flush();
|
|
}
|
|
return Result;
|
|
}
|
|
#endif
|
|
|
|
/// \brief Propagate known metadata from one instruction to another.
|
|
static void propagateMetadata(Instruction *To, const Instruction *From) {
|
|
SmallVector<std::pair<unsigned, MDNode *>, 4> Metadata;
|
|
From->getAllMetadataOtherThanDebugLoc(Metadata);
|
|
|
|
for (auto M : Metadata) {
|
|
unsigned Kind = M.first;
|
|
|
|
// These are safe to transfer (this is safe for TBAA, even when we
|
|
// if-convert, because should that metadata have had a control dependency
|
|
// on the condition, and thus actually aliased with some other
|
|
// non-speculated memory access when the condition was false, this would be
|
|
// caught by the runtime overlap checks).
|
|
if (Kind != LLVMContext::MD_tbaa &&
|
|
Kind != LLVMContext::MD_alias_scope &&
|
|
Kind != LLVMContext::MD_noalias &&
|
|
Kind != LLVMContext::MD_fpmath)
|
|
continue;
|
|
|
|
To->setMetadata(Kind, M.second);
|
|
}
|
|
}
|
|
|
|
/// \brief Propagate known metadata from one instruction to a vector of others.
|
|
static void propagateMetadata(SmallVectorImpl<Value *> &To, const Instruction *From) {
|
|
for (Value *V : To)
|
|
if (Instruction *I = dyn_cast<Instruction>(V))
|
|
propagateMetadata(I, From);
|
|
}
|
|
|
|
/// LoopVectorizationLegality checks if it is legal to vectorize a loop, and
|
|
/// to what vectorization factor.
|
|
/// This class does not look at the profitability of vectorization, only the
|
|
/// legality. This class has two main kinds of checks:
|
|
/// * Memory checks - The code in canVectorizeMemory checks if vectorization
|
|
/// will change the order of memory accesses in a way that will change the
|
|
/// correctness of the program.
|
|
/// * Scalars checks - The code in canVectorizeInstrs and canVectorizeMemory
|
|
/// checks for a number of different conditions, such as the availability of a
|
|
/// single induction variable, that all types are supported and vectorize-able,
|
|
/// etc. This code reflects the capabilities of InnerLoopVectorizer.
|
|
/// This class is also used by InnerLoopVectorizer for identifying
|
|
/// induction variable and the different reduction variables.
|
|
class LoopVectorizationLegality {
|
|
public:
|
|
LoopVectorizationLegality(Loop *L, ScalarEvolution *SE, const DataLayout *DL,
|
|
DominatorTree *DT, TargetLibraryInfo *TLI,
|
|
AliasAnalysis *AA, Function *F,
|
|
const TargetTransformInfo *TTI)
|
|
: NumPredStores(0), TheLoop(L), SE(SE), DL(DL), TLI(TLI), TheFunction(F),
|
|
TTI(TTI), DT(DT), Induction(nullptr), WidestIndTy(nullptr),
|
|
LAI(F, L, SE, DL, TLI, AA, DT,
|
|
LoopAccessInfo::VectorizerParams(
|
|
MaxVectorWidth, VectorizationFactor, VectorizationInterleave,
|
|
RuntimeMemoryCheckThreshold)),
|
|
HasFunNoNaNAttr(false) {}
|
|
|
|
/// This enum represents the kinds of reductions that we support.
|
|
enum ReductionKind {
|
|
RK_NoReduction, ///< Not a reduction.
|
|
RK_IntegerAdd, ///< Sum of integers.
|
|
RK_IntegerMult, ///< Product of integers.
|
|
RK_IntegerOr, ///< Bitwise or logical OR of numbers.
|
|
RK_IntegerAnd, ///< Bitwise or logical AND of numbers.
|
|
RK_IntegerXor, ///< Bitwise or logical XOR of numbers.
|
|
RK_IntegerMinMax, ///< Min/max implemented in terms of select(cmp()).
|
|
RK_FloatAdd, ///< Sum of floats.
|
|
RK_FloatMult, ///< Product of floats.
|
|
RK_FloatMinMax ///< Min/max implemented in terms of select(cmp()).
|
|
};
|
|
|
|
/// This enum represents the kinds of inductions that we support.
|
|
enum InductionKind {
|
|
IK_NoInduction, ///< Not an induction variable.
|
|
IK_IntInduction, ///< Integer induction variable. Step = C.
|
|
IK_PtrInduction ///< Pointer induction var. Step = C / sizeof(elem).
|
|
};
|
|
|
|
// This enum represents the kind of minmax reduction.
|
|
enum MinMaxReductionKind {
|
|
MRK_Invalid,
|
|
MRK_UIntMin,
|
|
MRK_UIntMax,
|
|
MRK_SIntMin,
|
|
MRK_SIntMax,
|
|
MRK_FloatMin,
|
|
MRK_FloatMax
|
|
};
|
|
|
|
/// This struct holds information about reduction variables.
|
|
struct ReductionDescriptor {
|
|
ReductionDescriptor() : StartValue(nullptr), LoopExitInstr(nullptr),
|
|
Kind(RK_NoReduction), MinMaxKind(MRK_Invalid) {}
|
|
|
|
ReductionDescriptor(Value *Start, Instruction *Exit, ReductionKind K,
|
|
MinMaxReductionKind MK)
|
|
: StartValue(Start), LoopExitInstr(Exit), Kind(K), MinMaxKind(MK) {}
|
|
|
|
// The starting value of the reduction.
|
|
// It does not have to be zero!
|
|
TrackingVH<Value> StartValue;
|
|
// The instruction who's value is used outside the loop.
|
|
Instruction *LoopExitInstr;
|
|
// The kind of the reduction.
|
|
ReductionKind Kind;
|
|
// If this a min/max reduction the kind of reduction.
|
|
MinMaxReductionKind MinMaxKind;
|
|
};
|
|
|
|
/// This POD struct holds information about a potential reduction operation.
|
|
struct ReductionInstDesc {
|
|
ReductionInstDesc(bool IsRedux, Instruction *I) :
|
|
IsReduction(IsRedux), PatternLastInst(I), MinMaxKind(MRK_Invalid) {}
|
|
|
|
ReductionInstDesc(Instruction *I, MinMaxReductionKind K) :
|
|
IsReduction(true), PatternLastInst(I), MinMaxKind(K) {}
|
|
|
|
// Is this instruction a reduction candidate.
|
|
bool IsReduction;
|
|
// The last instruction in a min/max pattern (select of the select(icmp())
|
|
// pattern), or the current reduction instruction otherwise.
|
|
Instruction *PatternLastInst;
|
|
// If this is a min/max pattern the comparison predicate.
|
|
MinMaxReductionKind MinMaxKind;
|
|
};
|
|
|
|
/// A struct for saving information about induction variables.
|
|
struct InductionInfo {
|
|
InductionInfo(Value *Start, InductionKind K, ConstantInt *Step)
|
|
: StartValue(Start), IK(K), StepValue(Step) {
|
|
assert(IK != IK_NoInduction && "Not an induction");
|
|
assert(StartValue && "StartValue is null");
|
|
assert(StepValue && !StepValue->isZero() && "StepValue is zero");
|
|
assert((IK != IK_PtrInduction || StartValue->getType()->isPointerTy()) &&
|
|
"StartValue is not a pointer for pointer induction");
|
|
assert((IK != IK_IntInduction || StartValue->getType()->isIntegerTy()) &&
|
|
"StartValue is not an integer for integer induction");
|
|
assert(StepValue->getType()->isIntegerTy() &&
|
|
"StepValue is not an integer");
|
|
}
|
|
InductionInfo()
|
|
: StartValue(nullptr), IK(IK_NoInduction), StepValue(nullptr) {}
|
|
|
|
/// Get the consecutive direction. Returns:
|
|
/// 0 - unknown or non-consecutive.
|
|
/// 1 - consecutive and increasing.
|
|
/// -1 - consecutive and decreasing.
|
|
int getConsecutiveDirection() const {
|
|
if (StepValue && (StepValue->isOne() || StepValue->isMinusOne()))
|
|
return StepValue->getSExtValue();
|
|
return 0;
|
|
}
|
|
|
|
/// Compute the transformed value of Index at offset StartValue using step
|
|
/// StepValue.
|
|
/// For integer induction, returns StartValue + Index * StepValue.
|
|
/// For pointer induction, returns StartValue[Index * StepValue].
|
|
/// FIXME: The newly created binary instructions should contain nsw/nuw
|
|
/// flags, which can be found from the original scalar operations.
|
|
Value *transform(IRBuilder<> &B, Value *Index) const {
|
|
switch (IK) {
|
|
case IK_IntInduction:
|
|
assert(Index->getType() == StartValue->getType() &&
|
|
"Index type does not match StartValue type");
|
|
if (StepValue->isMinusOne())
|
|
return B.CreateSub(StartValue, Index);
|
|
if (!StepValue->isOne())
|
|
Index = B.CreateMul(Index, StepValue);
|
|
return B.CreateAdd(StartValue, Index);
|
|
|
|
case IK_PtrInduction:
|
|
if (StepValue->isMinusOne())
|
|
Index = B.CreateNeg(Index);
|
|
else if (!StepValue->isOne())
|
|
Index = B.CreateMul(Index, StepValue);
|
|
return B.CreateGEP(StartValue, Index);
|
|
|
|
case IK_NoInduction:
|
|
return nullptr;
|
|
}
|
|
llvm_unreachable("invalid enum");
|
|
}
|
|
|
|
/// Start value.
|
|
TrackingVH<Value> StartValue;
|
|
/// Induction kind.
|
|
InductionKind IK;
|
|
/// Step value.
|
|
ConstantInt *StepValue;
|
|
};
|
|
|
|
/// ReductionList contains the reduction descriptors for all
|
|
/// of the reductions that were found in the loop.
|
|
typedef DenseMap<PHINode*, ReductionDescriptor> ReductionList;
|
|
|
|
/// InductionList saves induction variables and maps them to the
|
|
/// induction descriptor.
|
|
typedef MapVector<PHINode*, InductionInfo> InductionList;
|
|
|
|
/// Returns true if it is legal to vectorize this loop.
|
|
/// This does not mean that it is profitable to vectorize this
|
|
/// loop, only that it is legal to do so.
|
|
bool canVectorize();
|
|
|
|
/// Returns the Induction variable.
|
|
PHINode *getInduction() { return Induction; }
|
|
|
|
/// Returns the reduction variables found in the loop.
|
|
ReductionList *getReductionVars() { return &Reductions; }
|
|
|
|
/// Returns the induction variables found in the loop.
|
|
InductionList *getInductionVars() { return &Inductions; }
|
|
|
|
/// Returns the widest induction type.
|
|
Type *getWidestInductionType() { return WidestIndTy; }
|
|
|
|
/// Returns True if V is an induction variable in this loop.
|
|
bool isInductionVariable(const Value *V);
|
|
|
|
/// Return true if the block BB needs to be predicated in order for the loop
|
|
/// to be vectorized.
|
|
bool blockNeedsPredication(BasicBlock *BB);
|
|
|
|
/// Check if this pointer is consecutive when vectorizing. This happens
|
|
/// when the last index of the GEP is the induction variable, or that the
|
|
/// pointer itself is an induction variable.
|
|
/// This check allows us to vectorize A[idx] into a wide load/store.
|
|
/// Returns:
|
|
/// 0 - Stride is unknown or non-consecutive.
|
|
/// 1 - Address is consecutive.
|
|
/// -1 - Address is consecutive, and decreasing.
|
|
int isConsecutivePtr(Value *Ptr);
|
|
|
|
/// Returns true if the value V is uniform within the loop.
|
|
bool isUniform(Value *V);
|
|
|
|
/// Returns true if this instruction will remain scalar after vectorization.
|
|
bool isUniformAfterVectorization(Instruction* I) { return Uniforms.count(I); }
|
|
|
|
/// Returns the information that we collected about runtime memory check.
|
|
LoopAccessInfo::RuntimePointerCheck *getRuntimePointerCheck() {
|
|
return LAI.getRuntimePointerCheck();
|
|
}
|
|
|
|
LoopAccessInfo *getLAI() { return &LAI; }
|
|
|
|
/// This function returns the identity element (or neutral element) for
|
|
/// the operation K.
|
|
static Constant *getReductionIdentity(ReductionKind K, Type *Tp);
|
|
|
|
unsigned getMaxSafeDepDistBytes() { return LAI.getMaxSafeDepDistBytes(); }
|
|
|
|
bool hasStride(Value *V) { return StrideSet.count(V); }
|
|
bool mustCheckStrides() { return !StrideSet.empty(); }
|
|
SmallPtrSet<Value *, 8>::iterator strides_begin() {
|
|
return StrideSet.begin();
|
|
}
|
|
SmallPtrSet<Value *, 8>::iterator strides_end() { return StrideSet.end(); }
|
|
|
|
/// Returns true if the target machine supports masked store operation
|
|
/// for the given \p DataType and kind of access to \p Ptr.
|
|
bool isLegalMaskedStore(Type *DataType, Value *Ptr) {
|
|
return TTI->isLegalMaskedStore(DataType, isConsecutivePtr(Ptr));
|
|
}
|
|
/// Returns true if the target machine supports masked load operation
|
|
/// for the given \p DataType and kind of access to \p Ptr.
|
|
bool isLegalMaskedLoad(Type *DataType, Value *Ptr) {
|
|
return TTI->isLegalMaskedLoad(DataType, isConsecutivePtr(Ptr));
|
|
}
|
|
/// Returns true if vector representation of the instruction \p I
|
|
/// requires mask.
|
|
bool isMaskRequired(const Instruction *I) { return (MaskedOp.count(I) != 0); }
|
|
unsigned getNumStores() const { return LAI.getNumStores(); }
|
|
unsigned getNumLoads() const { return LAI.getNumLoads(); }
|
|
unsigned getNumPredStores() const { return NumPredStores; }
|
|
|
|
private:
|
|
/// Check if a single basic block loop is vectorizable.
|
|
/// At this point we know that this is a loop with a constant trip count
|
|
/// and we only need to check individual instructions.
|
|
bool canVectorizeInstrs();
|
|
|
|
/// When we vectorize loops we may change the order in which
|
|
/// we read and write from memory. This method checks if it is
|
|
/// legal to vectorize the code, considering only memory constrains.
|
|
/// Returns true if the loop is vectorizable
|
|
bool canVectorizeMemory();
|
|
|
|
/// Return true if we can vectorize this loop using the IF-conversion
|
|
/// transformation.
|
|
bool canVectorizeWithIfConvert();
|
|
|
|
/// Collect the variables that need to stay uniform after vectorization.
|
|
void collectLoopUniforms();
|
|
|
|
/// Return true if all of the instructions in the block can be speculatively
|
|
/// executed. \p SafePtrs is a list of addresses that are known to be legal
|
|
/// and we know that we can read from them without segfault.
|
|
bool blockCanBePredicated(BasicBlock *BB, SmallPtrSetImpl<Value *> &SafePtrs);
|
|
|
|
/// Returns True, if 'Phi' is the kind of reduction variable for type
|
|
/// 'Kind'. If this is a reduction variable, it adds it to ReductionList.
|
|
bool AddReductionVar(PHINode *Phi, ReductionKind Kind);
|
|
/// Returns a struct describing if the instruction 'I' can be a reduction
|
|
/// variable of type 'Kind'. If the reduction is a min/max pattern of
|
|
/// select(icmp()) this function advances the instruction pointer 'I' from the
|
|
/// compare instruction to the select instruction and stores this pointer in
|
|
/// 'PatternLastInst' member of the returned struct.
|
|
ReductionInstDesc isReductionInstr(Instruction *I, ReductionKind Kind,
|
|
ReductionInstDesc &Desc);
|
|
/// Returns true if the instruction is a Select(ICmp(X, Y), X, Y) instruction
|
|
/// pattern corresponding to a min(X, Y) or max(X, Y).
|
|
static ReductionInstDesc isMinMaxSelectCmpPattern(Instruction *I,
|
|
ReductionInstDesc &Prev);
|
|
/// Returns the induction kind of Phi and record the step. This function may
|
|
/// return NoInduction if the PHI is not an induction variable.
|
|
InductionKind isInductionVariable(PHINode *Phi, ConstantInt *&StepValue);
|
|
|
|
/// \brief Collect memory access with loop invariant strides.
|
|
///
|
|
/// Looks for accesses like "a[i * StrideA]" where "StrideA" is loop
|
|
/// invariant.
|
|
void collectStridedAccess(Value *LoadOrStoreInst);
|
|
|
|
/// Report an analysis message to assist the user in diagnosing loops that are
|
|
/// not vectorized.
|
|
void emitAnalysis(VectorizationReport &Message) {
|
|
VectorizationReport::emitAnalysis(Message, TheFunction, TheLoop);
|
|
}
|
|
|
|
unsigned NumPredStores;
|
|
|
|
/// The loop that we evaluate.
|
|
Loop *TheLoop;
|
|
/// Scev analysis.
|
|
ScalarEvolution *SE;
|
|
/// DataLayout analysis.
|
|
const DataLayout *DL;
|
|
/// Target Library Info.
|
|
TargetLibraryInfo *TLI;
|
|
/// Parent function
|
|
Function *TheFunction;
|
|
/// Target Transform Info
|
|
const TargetTransformInfo *TTI;
|
|
/// Dominator Tree.
|
|
DominatorTree *DT;
|
|
|
|
// --- vectorization state --- //
|
|
|
|
/// Holds the integer induction variable. This is the counter of the
|
|
/// loop.
|
|
PHINode *Induction;
|
|
/// Holds the reduction variables.
|
|
ReductionList Reductions;
|
|
/// Holds all of the induction variables that we found in the loop.
|
|
/// Notice that inductions don't need to start at zero and that induction
|
|
/// variables can be pointers.
|
|
InductionList Inductions;
|
|
/// Holds the widest induction type encountered.
|
|
Type *WidestIndTy;
|
|
|
|
/// Allowed outside users. This holds the reduction
|
|
/// vars which can be accessed from outside the loop.
|
|
SmallPtrSet<Value*, 4> AllowedExit;
|
|
/// This set holds the variables which are known to be uniform after
|
|
/// vectorization.
|
|
SmallPtrSet<Instruction *, 4> Uniforms;
|
|
LoopAccessInfo LAI;
|
|
/// Can we assume the absence of NaNs.
|
|
bool HasFunNoNaNAttr;
|
|
|
|
ValueToValueMap Strides;
|
|
SmallPtrSet<Value *, 8> StrideSet;
|
|
|
|
/// While vectorizing these instructions we have to generate a
|
|
/// call to the appropriate masked intrinsic
|
|
SmallPtrSet<const Instruction*, 8> MaskedOp;
|
|
};
|
|
|
|
/// LoopVectorizationCostModel - estimates the expected speedups due to
|
|
/// vectorization.
|
|
/// In many cases vectorization is not profitable. This can happen because of
|
|
/// a number of reasons. In this class we mainly attempt to predict the
|
|
/// expected speedup/slowdowns due to the supported instruction set. We use the
|
|
/// TargetTransformInfo to query the different backends for the cost of
|
|
/// different operations.
|
|
class LoopVectorizationCostModel {
|
|
public:
|
|
LoopVectorizationCostModel(Loop *L, ScalarEvolution *SE, LoopInfo *LI,
|
|
LoopVectorizationLegality *Legal,
|
|
const TargetTransformInfo &TTI,
|
|
const DataLayout *DL, const TargetLibraryInfo *TLI,
|
|
AssumptionCache *AC, const Function *F,
|
|
const LoopVectorizeHints *Hints)
|
|
: TheLoop(L), SE(SE), LI(LI), Legal(Legal), TTI(TTI), DL(DL), TLI(TLI),
|
|
TheFunction(F), Hints(Hints) {
|
|
CodeMetrics::collectEphemeralValues(L, AC, EphValues);
|
|
}
|
|
|
|
/// Information about vectorization costs
|
|
struct VectorizationFactor {
|
|
unsigned Width; // Vector width with best cost
|
|
unsigned Cost; // Cost of the loop with that width
|
|
};
|
|
/// \return The most profitable vectorization factor and the cost of that VF.
|
|
/// This method checks every power of two up to VF. If UserVF is not ZERO
|
|
/// then this vectorization factor will be selected if vectorization is
|
|
/// possible.
|
|
VectorizationFactor selectVectorizationFactor(bool OptForSize);
|
|
|
|
/// \return The size (in bits) of the widest type in the code that
|
|
/// needs to be vectorized. We ignore values that remain scalar such as
|
|
/// 64 bit loop indices.
|
|
unsigned getWidestType();
|
|
|
|
/// \return The most profitable unroll factor.
|
|
/// If UserUF is non-zero then this method finds the best unroll-factor
|
|
/// based on register pressure and other parameters.
|
|
/// VF and LoopCost are the selected vectorization factor and the cost of the
|
|
/// selected VF.
|
|
unsigned selectUnrollFactor(bool OptForSize, unsigned VF, unsigned LoopCost);
|
|
|
|
/// \brief A struct that represents some properties of the register usage
|
|
/// of a loop.
|
|
struct RegisterUsage {
|
|
/// Holds the number of loop invariant values that are used in the loop.
|
|
unsigned LoopInvariantRegs;
|
|
/// Holds the maximum number of concurrent live intervals in the loop.
|
|
unsigned MaxLocalUsers;
|
|
/// Holds the number of instructions in the loop.
|
|
unsigned NumInstructions;
|
|
};
|
|
|
|
/// \return information about the register usage of the loop.
|
|
RegisterUsage calculateRegisterUsage();
|
|
|
|
private:
|
|
/// Returns the expected execution cost. The unit of the cost does
|
|
/// not matter because we use the 'cost' units to compare different
|
|
/// vector widths. The cost that is returned is *not* normalized by
|
|
/// the factor width.
|
|
unsigned expectedCost(unsigned VF);
|
|
|
|
/// Returns the execution time cost of an instruction for a given vector
|
|
/// width. Vector width of one means scalar.
|
|
unsigned getInstructionCost(Instruction *I, unsigned VF);
|
|
|
|
/// A helper function for converting Scalar types to vector types.
|
|
/// If the incoming type is void, we return void. If the VF is 1, we return
|
|
/// the scalar type.
|
|
static Type* ToVectorTy(Type *Scalar, unsigned VF);
|
|
|
|
/// Returns whether the instruction is a load or store and will be a emitted
|
|
/// as a vector operation.
|
|
bool isConsecutiveLoadOrStore(Instruction *I);
|
|
|
|
/// Report an analysis message to assist the user in diagnosing loops that are
|
|
/// not vectorized.
|
|
void emitAnalysis(VectorizationReport &Message) {
|
|
VectorizationReport::emitAnalysis(Message, TheFunction, TheLoop);
|
|
}
|
|
|
|
/// Values used only by @llvm.assume calls.
|
|
SmallPtrSet<const Value *, 32> EphValues;
|
|
|
|
/// The loop that we evaluate.
|
|
Loop *TheLoop;
|
|
/// Scev analysis.
|
|
ScalarEvolution *SE;
|
|
/// Loop Info analysis.
|
|
LoopInfo *LI;
|
|
/// Vectorization legality.
|
|
LoopVectorizationLegality *Legal;
|
|
/// Vector target information.
|
|
const TargetTransformInfo &TTI;
|
|
/// Target data layout information.
|
|
const DataLayout *DL;
|
|
/// Target Library Info.
|
|
const TargetLibraryInfo *TLI;
|
|
const Function *TheFunction;
|
|
// Loop Vectorize Hint.
|
|
const LoopVectorizeHints *Hints;
|
|
};
|
|
|
|
/// Utility class for getting and setting loop vectorizer hints in the form
|
|
/// of loop metadata.
|
|
/// This class keeps a number of loop annotations locally (as member variables)
|
|
/// and can, upon request, write them back as metadata on the loop. It will
|
|
/// initially scan the loop for existing metadata, and will update the local
|
|
/// values based on information in the loop.
|
|
/// We cannot write all values to metadata, as the mere presence of some info,
|
|
/// for example 'force', means a decision has been made. So, we need to be
|
|
/// careful NOT to add them if the user hasn't specifically asked so.
|
|
class LoopVectorizeHints {
|
|
enum HintKind {
|
|
HK_WIDTH,
|
|
HK_UNROLL,
|
|
HK_FORCE
|
|
};
|
|
|
|
/// Hint - associates name and validation with the hint value.
|
|
struct Hint {
|
|
const char * Name;
|
|
unsigned Value; // This may have to change for non-numeric values.
|
|
HintKind Kind;
|
|
|
|
Hint(const char * Name, unsigned Value, HintKind Kind)
|
|
: Name(Name), Value(Value), Kind(Kind) { }
|
|
|
|
bool validate(unsigned Val) {
|
|
switch (Kind) {
|
|
case HK_WIDTH:
|
|
return isPowerOf2_32(Val) && Val <= MaxVectorWidth;
|
|
case HK_UNROLL:
|
|
return isPowerOf2_32(Val) && Val <= MaxInterleaveFactor;
|
|
case HK_FORCE:
|
|
return (Val <= 1);
|
|
}
|
|
return false;
|
|
}
|
|
};
|
|
|
|
/// Vectorization width.
|
|
Hint Width;
|
|
/// Vectorization interleave factor.
|
|
Hint Interleave;
|
|
/// Vectorization forced
|
|
Hint Force;
|
|
|
|
/// Return the loop metadata prefix.
|
|
static StringRef Prefix() { return "llvm.loop."; }
|
|
|
|
public:
|
|
enum ForceKind {
|
|
FK_Undefined = -1, ///< Not selected.
|
|
FK_Disabled = 0, ///< Forcing disabled.
|
|
FK_Enabled = 1, ///< Forcing enabled.
|
|
};
|
|
|
|
LoopVectorizeHints(const Loop *L, bool DisableInterleaving)
|
|
: Width("vectorize.width", VectorizationFactor, HK_WIDTH),
|
|
Interleave("interleave.count", DisableInterleaving, HK_UNROLL),
|
|
Force("vectorize.enable", FK_Undefined, HK_FORCE),
|
|
TheLoop(L) {
|
|
// Populate values with existing loop metadata.
|
|
getHintsFromMetadata();
|
|
|
|
// force-vector-interleave overrides DisableInterleaving.
|
|
if (VectorizationInterleave.getNumOccurrences() > 0)
|
|
Interleave.Value = VectorizationInterleave;
|
|
|
|
DEBUG(if (DisableInterleaving && Interleave.Value == 1) dbgs()
|
|
<< "LV: Interleaving disabled by the pass manager\n");
|
|
}
|
|
|
|
/// Mark the loop L as already vectorized by setting the width to 1.
|
|
void setAlreadyVectorized() {
|
|
Width.Value = Interleave.Value = 1;
|
|
Hint Hints[] = {Width, Interleave};
|
|
writeHintsToMetadata(Hints);
|
|
}
|
|
|
|
/// Dumps all the hint information.
|
|
std::string emitRemark() const {
|
|
VectorizationReport R;
|
|
if (Force.Value == LoopVectorizeHints::FK_Disabled)
|
|
R << "vectorization is explicitly disabled";
|
|
else {
|
|
R << "use -Rpass-analysis=loop-vectorize for more info";
|
|
if (Force.Value == LoopVectorizeHints::FK_Enabled) {
|
|
R << " (Force=true";
|
|
if (Width.Value != 0)
|
|
R << ", Vector Width=" << Width.Value;
|
|
if (Interleave.Value != 0)
|
|
R << ", Interleave Count=" << Interleave.Value;
|
|
R << ")";
|
|
}
|
|
}
|
|
|
|
return R.str();
|
|
}
|
|
|
|
unsigned getWidth() const { return Width.Value; }
|
|
unsigned getInterleave() const { return Interleave.Value; }
|
|
enum ForceKind getForce() const { return (ForceKind)Force.Value; }
|
|
|
|
private:
|
|
/// Find hints specified in the loop metadata and update local values.
|
|
void getHintsFromMetadata() {
|
|
MDNode *LoopID = TheLoop->getLoopID();
|
|
if (!LoopID)
|
|
return;
|
|
|
|
// First operand should refer to the loop id itself.
|
|
assert(LoopID->getNumOperands() > 0 && "requires at least one operand");
|
|
assert(LoopID->getOperand(0) == LoopID && "invalid loop id");
|
|
|
|
for (unsigned i = 1, ie = LoopID->getNumOperands(); i < ie; ++i) {
|
|
const MDString *S = nullptr;
|
|
SmallVector<Metadata *, 4> Args;
|
|
|
|
// The expected hint is either a MDString or a MDNode with the first
|
|
// operand a MDString.
|
|
if (const MDNode *MD = dyn_cast<MDNode>(LoopID->getOperand(i))) {
|
|
if (!MD || MD->getNumOperands() == 0)
|
|
continue;
|
|
S = dyn_cast<MDString>(MD->getOperand(0));
|
|
for (unsigned i = 1, ie = MD->getNumOperands(); i < ie; ++i)
|
|
Args.push_back(MD->getOperand(i));
|
|
} else {
|
|
S = dyn_cast<MDString>(LoopID->getOperand(i));
|
|
assert(Args.size() == 0 && "too many arguments for MDString");
|
|
}
|
|
|
|
if (!S)
|
|
continue;
|
|
|
|
// Check if the hint starts with the loop metadata prefix.
|
|
StringRef Name = S->getString();
|
|
if (Args.size() == 1)
|
|
setHint(Name, Args[0]);
|
|
}
|
|
}
|
|
|
|
/// Checks string hint with one operand and set value if valid.
|
|
void setHint(StringRef Name, Metadata *Arg) {
|
|
if (!Name.startswith(Prefix()))
|
|
return;
|
|
Name = Name.substr(Prefix().size(), StringRef::npos);
|
|
|
|
const ConstantInt *C = mdconst::dyn_extract<ConstantInt>(Arg);
|
|
if (!C) return;
|
|
unsigned Val = C->getZExtValue();
|
|
|
|
Hint *Hints[] = {&Width, &Interleave, &Force};
|
|
for (auto H : Hints) {
|
|
if (Name == H->Name) {
|
|
if (H->validate(Val))
|
|
H->Value = Val;
|
|
else
|
|
DEBUG(dbgs() << "LV: ignoring invalid hint '" << Name << "'\n");
|
|
break;
|
|
}
|
|
}
|
|
}
|
|
|
|
/// Create a new hint from name / value pair.
|
|
MDNode *createHintMetadata(StringRef Name, unsigned V) const {
|
|
LLVMContext &Context = TheLoop->getHeader()->getContext();
|
|
Metadata *MDs[] = {MDString::get(Context, Name),
|
|
ConstantAsMetadata::get(
|
|
ConstantInt::get(Type::getInt32Ty(Context), V))};
|
|
return MDNode::get(Context, MDs);
|
|
}
|
|
|
|
/// Matches metadata with hint name.
|
|
bool matchesHintMetadataName(MDNode *Node, ArrayRef<Hint> HintTypes) {
|
|
MDString* Name = dyn_cast<MDString>(Node->getOperand(0));
|
|
if (!Name)
|
|
return false;
|
|
|
|
for (auto H : HintTypes)
|
|
if (Name->getString().endswith(H.Name))
|
|
return true;
|
|
return false;
|
|
}
|
|
|
|
/// Sets current hints into loop metadata, keeping other values intact.
|
|
void writeHintsToMetadata(ArrayRef<Hint> HintTypes) {
|
|
if (HintTypes.size() == 0)
|
|
return;
|
|
|
|
// Reserve the first element to LoopID (see below).
|
|
SmallVector<Metadata *, 4> MDs(1);
|
|
// If the loop already has metadata, then ignore the existing operands.
|
|
MDNode *LoopID = TheLoop->getLoopID();
|
|
if (LoopID) {
|
|
for (unsigned i = 1, ie = LoopID->getNumOperands(); i < ie; ++i) {
|
|
MDNode *Node = cast<MDNode>(LoopID->getOperand(i));
|
|
// If node in update list, ignore old value.
|
|
if (!matchesHintMetadataName(Node, HintTypes))
|
|
MDs.push_back(Node);
|
|
}
|
|
}
|
|
|
|
// Now, add the missing hints.
|
|
for (auto H : HintTypes)
|
|
MDs.push_back(createHintMetadata(Twine(Prefix(), H.Name).str(), H.Value));
|
|
|
|
// Replace current metadata node with new one.
|
|
LLVMContext &Context = TheLoop->getHeader()->getContext();
|
|
MDNode *NewLoopID = MDNode::get(Context, MDs);
|
|
// Set operand 0 to refer to the loop id itself.
|
|
NewLoopID->replaceOperandWith(0, NewLoopID);
|
|
|
|
TheLoop->setLoopID(NewLoopID);
|
|
}
|
|
|
|
/// The loop these hints belong to.
|
|
const Loop *TheLoop;
|
|
};
|
|
|
|
static void emitMissedWarning(Function *F, Loop *L,
|
|
const LoopVectorizeHints &LH) {
|
|
emitOptimizationRemarkMissed(F->getContext(), DEBUG_TYPE, *F,
|
|
L->getStartLoc(), LH.emitRemark());
|
|
|
|
if (LH.getForce() == LoopVectorizeHints::FK_Enabled) {
|
|
if (LH.getWidth() != 1)
|
|
emitLoopVectorizeWarning(
|
|
F->getContext(), *F, L->getStartLoc(),
|
|
"failed explicitly specified loop vectorization");
|
|
else if (LH.getInterleave() != 1)
|
|
emitLoopInterleaveWarning(
|
|
F->getContext(), *F, L->getStartLoc(),
|
|
"failed explicitly specified loop interleaving");
|
|
}
|
|
}
|
|
|
|
static void addInnerLoop(Loop &L, SmallVectorImpl<Loop *> &V) {
|
|
if (L.empty())
|
|
return V.push_back(&L);
|
|
|
|
for (Loop *InnerL : L)
|
|
addInnerLoop(*InnerL, V);
|
|
}
|
|
|
|
/// The LoopVectorize Pass.
|
|
struct LoopVectorize : public FunctionPass {
|
|
/// Pass identification, replacement for typeid
|
|
static char ID;
|
|
|
|
explicit LoopVectorize(bool NoUnrolling = false, bool AlwaysVectorize = true)
|
|
: FunctionPass(ID),
|
|
DisableUnrolling(NoUnrolling),
|
|
AlwaysVectorize(AlwaysVectorize) {
|
|
initializeLoopVectorizePass(*PassRegistry::getPassRegistry());
|
|
}
|
|
|
|
ScalarEvolution *SE;
|
|
const DataLayout *DL;
|
|
LoopInfo *LI;
|
|
TargetTransformInfo *TTI;
|
|
DominatorTree *DT;
|
|
BlockFrequencyInfo *BFI;
|
|
TargetLibraryInfo *TLI;
|
|
AliasAnalysis *AA;
|
|
AssumptionCache *AC;
|
|
bool DisableUnrolling;
|
|
bool AlwaysVectorize;
|
|
|
|
BlockFrequency ColdEntryFreq;
|
|
|
|
bool runOnFunction(Function &F) override {
|
|
SE = &getAnalysis<ScalarEvolution>();
|
|
DataLayoutPass *DLP = getAnalysisIfAvailable<DataLayoutPass>();
|
|
DL = DLP ? &DLP->getDataLayout() : nullptr;
|
|
LI = &getAnalysis<LoopInfoWrapperPass>().getLoopInfo();
|
|
TTI = &getAnalysis<TargetTransformInfoWrapperPass>().getTTI(F);
|
|
DT = &getAnalysis<DominatorTreeWrapperPass>().getDomTree();
|
|
BFI = &getAnalysis<BlockFrequencyInfo>();
|
|
auto *TLIP = getAnalysisIfAvailable<TargetLibraryInfoWrapperPass>();
|
|
TLI = TLIP ? &TLIP->getTLI() : nullptr;
|
|
AA = &getAnalysis<AliasAnalysis>();
|
|
AC = &getAnalysis<AssumptionCacheTracker>().getAssumptionCache(F);
|
|
|
|
// Compute some weights outside of the loop over the loops. Compute this
|
|
// using a BranchProbability to re-use its scaling math.
|
|
const BranchProbability ColdProb(1, 5); // 20%
|
|
ColdEntryFreq = BlockFrequency(BFI->getEntryFreq()) * ColdProb;
|
|
|
|
// If the target claims to have no vector registers don't attempt
|
|
// vectorization.
|
|
if (!TTI->getNumberOfRegisters(true))
|
|
return false;
|
|
|
|
if (!DL) {
|
|
DEBUG(dbgs() << "\nLV: Not vectorizing " << F.getName()
|
|
<< ": Missing data layout\n");
|
|
return false;
|
|
}
|
|
|
|
// Build up a worklist of inner-loops to vectorize. This is necessary as
|
|
// the act of vectorizing or partially unrolling a loop creates new loops
|
|
// and can invalidate iterators across the loops.
|
|
SmallVector<Loop *, 8> Worklist;
|
|
|
|
for (Loop *L : *LI)
|
|
addInnerLoop(*L, Worklist);
|
|
|
|
LoopsAnalyzed += Worklist.size();
|
|
|
|
// Now walk the identified inner loops.
|
|
bool Changed = false;
|
|
while (!Worklist.empty())
|
|
Changed |= processLoop(Worklist.pop_back_val());
|
|
|
|
// Process each loop nest in the function.
|
|
return Changed;
|
|
}
|
|
|
|
bool processLoop(Loop *L) {
|
|
assert(L->empty() && "Only process inner loops.");
|
|
|
|
#ifndef NDEBUG
|
|
const std::string DebugLocStr = getDebugLocString(L);
|
|
#endif /* NDEBUG */
|
|
|
|
DEBUG(dbgs() << "\nLV: Checking a loop in \""
|
|
<< L->getHeader()->getParent()->getName() << "\" from "
|
|
<< DebugLocStr << "\n");
|
|
|
|
LoopVectorizeHints Hints(L, DisableUnrolling);
|
|
|
|
DEBUG(dbgs() << "LV: Loop hints:"
|
|
<< " force="
|
|
<< (Hints.getForce() == LoopVectorizeHints::FK_Disabled
|
|
? "disabled"
|
|
: (Hints.getForce() == LoopVectorizeHints::FK_Enabled
|
|
? "enabled"
|
|
: "?")) << " width=" << Hints.getWidth()
|
|
<< " unroll=" << Hints.getInterleave() << "\n");
|
|
|
|
// Function containing loop
|
|
Function *F = L->getHeader()->getParent();
|
|
|
|
// Looking at the diagnostic output is the only way to determine if a loop
|
|
// was vectorized (other than looking at the IR or machine code), so it
|
|
// is important to generate an optimization remark for each loop. Most of
|
|
// these messages are generated by emitOptimizationRemarkAnalysis. Remarks
|
|
// generated by emitOptimizationRemark and emitOptimizationRemarkMissed are
|
|
// less verbose reporting vectorized loops and unvectorized loops that may
|
|
// benefit from vectorization, respectively.
|
|
|
|
if (Hints.getForce() == LoopVectorizeHints::FK_Disabled) {
|
|
DEBUG(dbgs() << "LV: Not vectorizing: #pragma vectorize disable.\n");
|
|
emitOptimizationRemarkAnalysis(F->getContext(), DEBUG_TYPE, *F,
|
|
L->getStartLoc(), Hints.emitRemark());
|
|
return false;
|
|
}
|
|
|
|
if (!AlwaysVectorize && Hints.getForce() != LoopVectorizeHints::FK_Enabled) {
|
|
DEBUG(dbgs() << "LV: Not vectorizing: No #pragma vectorize enable.\n");
|
|
emitOptimizationRemarkAnalysis(F->getContext(), DEBUG_TYPE, *F,
|
|
L->getStartLoc(), Hints.emitRemark());
|
|
return false;
|
|
}
|
|
|
|
if (Hints.getWidth() == 1 && Hints.getInterleave() == 1) {
|
|
DEBUG(dbgs() << "LV: Not vectorizing: Disabled/already vectorized.\n");
|
|
emitOptimizationRemarkAnalysis(
|
|
F->getContext(), DEBUG_TYPE, *F, L->getStartLoc(),
|
|
"loop not vectorized: vector width and interleave count are "
|
|
"explicitly set to 1");
|
|
return false;
|
|
}
|
|
|
|
// Check the loop for a trip count threshold:
|
|
// do not vectorize loops with a tiny trip count.
|
|
const unsigned TC = SE->getSmallConstantTripCount(L);
|
|
if (TC > 0u && TC < TinyTripCountVectorThreshold) {
|
|
DEBUG(dbgs() << "LV: Found a loop with a very small trip count. "
|
|
<< "This loop is not worth vectorizing.");
|
|
if (Hints.getForce() == LoopVectorizeHints::FK_Enabled)
|
|
DEBUG(dbgs() << " But vectorizing was explicitly forced.\n");
|
|
else {
|
|
DEBUG(dbgs() << "\n");
|
|
emitOptimizationRemarkAnalysis(
|
|
F->getContext(), DEBUG_TYPE, *F, L->getStartLoc(),
|
|
"vectorization is not beneficial and is not explicitly forced");
|
|
return false;
|
|
}
|
|
}
|
|
|
|
// Check if it is legal to vectorize the loop.
|
|
LoopVectorizationLegality LVL(L, SE, DL, DT, TLI, AA, F, TTI);
|
|
if (!LVL.canVectorize()) {
|
|
DEBUG(dbgs() << "LV: Not vectorizing: Cannot prove legality.\n");
|
|
emitMissedWarning(F, L, Hints);
|
|
return false;
|
|
}
|
|
|
|
// Use the cost model.
|
|
LoopVectorizationCostModel CM(L, SE, LI, &LVL, *TTI, DL, TLI, AC, F,
|
|
&Hints);
|
|
|
|
// Check the function attributes to find out if this function should be
|
|
// optimized for size.
|
|
bool OptForSize = Hints.getForce() != LoopVectorizeHints::FK_Enabled &&
|
|
F->hasFnAttribute(Attribute::OptimizeForSize);
|
|
|
|
// Compute the weighted frequency of this loop being executed and see if it
|
|
// is less than 20% of the function entry baseline frequency. Note that we
|
|
// always have a canonical loop here because we think we *can* vectoriez.
|
|
// FIXME: This is hidden behind a flag due to pervasive problems with
|
|
// exactly what block frequency models.
|
|
if (LoopVectorizeWithBlockFrequency) {
|
|
BlockFrequency LoopEntryFreq = BFI->getBlockFreq(L->getLoopPreheader());
|
|
if (Hints.getForce() != LoopVectorizeHints::FK_Enabled &&
|
|
LoopEntryFreq < ColdEntryFreq)
|
|
OptForSize = true;
|
|
}
|
|
|
|
// Check the function attributes to see if implicit floats are allowed.a
|
|
// FIXME: This check doesn't seem possibly correct -- what if the loop is
|
|
// an integer loop and the vector instructions selected are purely integer
|
|
// vector instructions?
|
|
if (F->hasFnAttribute(Attribute::NoImplicitFloat)) {
|
|
DEBUG(dbgs() << "LV: Can't vectorize when the NoImplicitFloat"
|
|
"attribute is used.\n");
|
|
emitOptimizationRemarkAnalysis(
|
|
F->getContext(), DEBUG_TYPE, *F, L->getStartLoc(),
|
|
"loop not vectorized due to NoImplicitFloat attribute");
|
|
emitMissedWarning(F, L, Hints);
|
|
return false;
|
|
}
|
|
|
|
// Select the optimal vectorization factor.
|
|
const LoopVectorizationCostModel::VectorizationFactor VF =
|
|
CM.selectVectorizationFactor(OptForSize);
|
|
|
|
// Select the unroll factor.
|
|
const unsigned UF =
|
|
CM.selectUnrollFactor(OptForSize, VF.Width, VF.Cost);
|
|
|
|
DEBUG(dbgs() << "LV: Found a vectorizable loop (" << VF.Width << ") in "
|
|
<< DebugLocStr << '\n');
|
|
DEBUG(dbgs() << "LV: Unroll Factor is " << UF << '\n');
|
|
|
|
if (VF.Width == 1) {
|
|
DEBUG(dbgs() << "LV: Vectorization is possible but not beneficial\n");
|
|
|
|
if (UF == 1) {
|
|
emitOptimizationRemarkAnalysis(
|
|
F->getContext(), DEBUG_TYPE, *F, L->getStartLoc(),
|
|
"not beneficial to vectorize and user disabled interleaving");
|
|
return false;
|
|
}
|
|
DEBUG(dbgs() << "LV: Trying to at least unroll the loops.\n");
|
|
|
|
// Report the unrolling decision.
|
|
emitOptimizationRemark(F->getContext(), DEBUG_TYPE, *F, L->getStartLoc(),
|
|
Twine("unrolled with interleaving factor " +
|
|
Twine(UF) +
|
|
" (vectorization not beneficial)"));
|
|
|
|
// We decided not to vectorize, but we may want to unroll.
|
|
|
|
InnerLoopUnroller Unroller(L, SE, LI, DT, DL, TLI, UF);
|
|
Unroller.vectorize(&LVL);
|
|
} else {
|
|
// If we decided that it is *legal* to vectorize the loop then do it.
|
|
InnerLoopVectorizer LB(L, SE, LI, DT, DL, TLI, VF.Width, UF);
|
|
LB.vectorize(&LVL);
|
|
++LoopsVectorized;
|
|
|
|
// Report the vectorization decision.
|
|
emitOptimizationRemark(
|
|
F->getContext(), DEBUG_TYPE, *F, L->getStartLoc(),
|
|
Twine("vectorized loop (vectorization factor: ") + Twine(VF.Width) +
|
|
", unrolling interleave factor: " + Twine(UF) + ")");
|
|
}
|
|
|
|
// Mark the loop as already vectorized to avoid vectorizing again.
|
|
Hints.setAlreadyVectorized();
|
|
|
|
DEBUG(verifyFunction(*L->getHeader()->getParent()));
|
|
return true;
|
|
}
|
|
|
|
void getAnalysisUsage(AnalysisUsage &AU) const override {
|
|
AU.addRequired<AssumptionCacheTracker>();
|
|
AU.addRequiredID(LoopSimplifyID);
|
|
AU.addRequiredID(LCSSAID);
|
|
AU.addRequired<BlockFrequencyInfo>();
|
|
AU.addRequired<DominatorTreeWrapperPass>();
|
|
AU.addRequired<LoopInfoWrapperPass>();
|
|
AU.addRequired<ScalarEvolution>();
|
|
AU.addRequired<TargetTransformInfoWrapperPass>();
|
|
AU.addRequired<AliasAnalysis>();
|
|
AU.addPreserved<LoopInfoWrapperPass>();
|
|
AU.addPreserved<DominatorTreeWrapperPass>();
|
|
AU.addPreserved<AliasAnalysis>();
|
|
}
|
|
|
|
};
|
|
|
|
} // end anonymous namespace
|
|
|
|
//===----------------------------------------------------------------------===//
|
|
// Implementation of LoopVectorizationLegality, InnerLoopVectorizer and
|
|
// LoopVectorizationCostModel.
|
|
//===----------------------------------------------------------------------===//
|
|
|
|
Value *InnerLoopVectorizer::getBroadcastInstrs(Value *V) {
|
|
// We need to place the broadcast of invariant variables outside the loop.
|
|
Instruction *Instr = dyn_cast<Instruction>(V);
|
|
bool NewInstr =
|
|
(Instr && std::find(LoopVectorBody.begin(), LoopVectorBody.end(),
|
|
Instr->getParent()) != LoopVectorBody.end());
|
|
bool Invariant = OrigLoop->isLoopInvariant(V) && !NewInstr;
|
|
|
|
// Place the code for broadcasting invariant variables in the new preheader.
|
|
IRBuilder<>::InsertPointGuard Guard(Builder);
|
|
if (Invariant)
|
|
Builder.SetInsertPoint(LoopVectorPreHeader->getTerminator());
|
|
|
|
// Broadcast the scalar into all locations in the vector.
|
|
Value *Shuf = Builder.CreateVectorSplat(VF, V, "broadcast");
|
|
|
|
return Shuf;
|
|
}
|
|
|
|
Value *InnerLoopVectorizer::getStepVector(Value *Val, int StartIdx,
|
|
Value *Step) {
|
|
assert(Val->getType()->isVectorTy() && "Must be a vector");
|
|
assert(Val->getType()->getScalarType()->isIntegerTy() &&
|
|
"Elem must be an integer");
|
|
assert(Step->getType() == Val->getType()->getScalarType() &&
|
|
"Step has wrong type");
|
|
// Create the types.
|
|
Type *ITy = Val->getType()->getScalarType();
|
|
VectorType *Ty = cast<VectorType>(Val->getType());
|
|
int VLen = Ty->getNumElements();
|
|
SmallVector<Constant*, 8> Indices;
|
|
|
|
// Create a vector of consecutive numbers from zero to VF.
|
|
for (int i = 0; i < VLen; ++i)
|
|
Indices.push_back(ConstantInt::get(ITy, StartIdx + i));
|
|
|
|
// Add the consecutive indices to the vector value.
|
|
Constant *Cv = ConstantVector::get(Indices);
|
|
assert(Cv->getType() == Val->getType() && "Invalid consecutive vec");
|
|
Step = Builder.CreateVectorSplat(VLen, Step);
|
|
assert(Step->getType() == Val->getType() && "Invalid step vec");
|
|
// FIXME: The newly created binary instructions should contain nsw/nuw flags,
|
|
// which can be found from the original scalar operations.
|
|
Step = Builder.CreateMul(Cv, Step);
|
|
return Builder.CreateAdd(Val, Step, "induction");
|
|
}
|
|
|
|
/// \brief Find the operand of the GEP that should be checked for consecutive
|
|
/// stores. This ignores trailing indices that have no effect on the final
|
|
/// pointer.
|
|
static unsigned getGEPInductionOperand(const DataLayout *DL,
|
|
const GetElementPtrInst *Gep) {
|
|
unsigned LastOperand = Gep->getNumOperands() - 1;
|
|
unsigned GEPAllocSize = DL->getTypeAllocSize(
|
|
cast<PointerType>(Gep->getType()->getScalarType())->getElementType());
|
|
|
|
// Walk backwards and try to peel off zeros.
|
|
while (LastOperand > 1 && match(Gep->getOperand(LastOperand), m_Zero())) {
|
|
// Find the type we're currently indexing into.
|
|
gep_type_iterator GEPTI = gep_type_begin(Gep);
|
|
std::advance(GEPTI, LastOperand - 1);
|
|
|
|
// If it's a type with the same allocation size as the result of the GEP we
|
|
// can peel off the zero index.
|
|
if (DL->getTypeAllocSize(*GEPTI) != GEPAllocSize)
|
|
break;
|
|
--LastOperand;
|
|
}
|
|
|
|
return LastOperand;
|
|
}
|
|
|
|
int LoopVectorizationLegality::isConsecutivePtr(Value *Ptr) {
|
|
assert(Ptr->getType()->isPointerTy() && "Unexpected non-ptr");
|
|
// Make sure that the pointer does not point to structs.
|
|
if (Ptr->getType()->getPointerElementType()->isAggregateType())
|
|
return 0;
|
|
|
|
// If this value is a pointer induction variable we know it is consecutive.
|
|
PHINode *Phi = dyn_cast_or_null<PHINode>(Ptr);
|
|
if (Phi && Inductions.count(Phi)) {
|
|
InductionInfo II = Inductions[Phi];
|
|
return II.getConsecutiveDirection();
|
|
}
|
|
|
|
GetElementPtrInst *Gep = dyn_cast_or_null<GetElementPtrInst>(Ptr);
|
|
if (!Gep)
|
|
return 0;
|
|
|
|
unsigned NumOperands = Gep->getNumOperands();
|
|
Value *GpPtr = Gep->getPointerOperand();
|
|
// If this GEP value is a consecutive pointer induction variable and all of
|
|
// the indices are constant then we know it is consecutive. We can
|
|
Phi = dyn_cast<PHINode>(GpPtr);
|
|
if (Phi && Inductions.count(Phi)) {
|
|
|
|
// Make sure that the pointer does not point to structs.
|
|
PointerType *GepPtrType = cast<PointerType>(GpPtr->getType());
|
|
if (GepPtrType->getElementType()->isAggregateType())
|
|
return 0;
|
|
|
|
// Make sure that all of the index operands are loop invariant.
|
|
for (unsigned i = 1; i < NumOperands; ++i)
|
|
if (!SE->isLoopInvariant(SE->getSCEV(Gep->getOperand(i)), TheLoop))
|
|
return 0;
|
|
|
|
InductionInfo II = Inductions[Phi];
|
|
return II.getConsecutiveDirection();
|
|
}
|
|
|
|
unsigned InductionOperand = getGEPInductionOperand(DL, Gep);
|
|
|
|
// Check that all of the gep indices are uniform except for our induction
|
|
// operand.
|
|
for (unsigned i = 0; i != NumOperands; ++i)
|
|
if (i != InductionOperand &&
|
|
!SE->isLoopInvariant(SE->getSCEV(Gep->getOperand(i)), TheLoop))
|
|
return 0;
|
|
|
|
// We can emit wide load/stores only if the last non-zero index is the
|
|
// induction variable.
|
|
const SCEV *Last = nullptr;
|
|
if (!Strides.count(Gep))
|
|
Last = SE->getSCEV(Gep->getOperand(InductionOperand));
|
|
else {
|
|
// Because of the multiplication by a stride we can have a s/zext cast.
|
|
// We are going to replace this stride by 1 so the cast is safe to ignore.
|
|
//
|
|
// %indvars.iv = phi i64 [ 0, %entry ], [ %indvars.iv.next, %for.body ]
|
|
// %0 = trunc i64 %indvars.iv to i32
|
|
// %mul = mul i32 %0, %Stride1
|
|
// %idxprom = zext i32 %mul to i64 << Safe cast.
|
|
// %arrayidx = getelementptr inbounds i32* %B, i64 %idxprom
|
|
//
|
|
Last = replaceSymbolicStrideSCEV(SE, Strides,
|
|
Gep->getOperand(InductionOperand), Gep);
|
|
if (const SCEVCastExpr *C = dyn_cast<SCEVCastExpr>(Last))
|
|
Last =
|
|
(C->getSCEVType() == scSignExtend || C->getSCEVType() == scZeroExtend)
|
|
? C->getOperand()
|
|
: Last;
|
|
}
|
|
if (const SCEVAddRecExpr *AR = dyn_cast<SCEVAddRecExpr>(Last)) {
|
|
const SCEV *Step = AR->getStepRecurrence(*SE);
|
|
|
|
// The memory is consecutive because the last index is consecutive
|
|
// and all other indices are loop invariant.
|
|
if (Step->isOne())
|
|
return 1;
|
|
if (Step->isAllOnesValue())
|
|
return -1;
|
|
}
|
|
|
|
return 0;
|
|
}
|
|
|
|
bool LoopVectorizationLegality::isUniform(Value *V) { return LAI.isUniform(V); }
|
|
|
|
InnerLoopVectorizer::VectorParts&
|
|
InnerLoopVectorizer::getVectorValue(Value *V) {
|
|
assert(V != Induction && "The new induction variable should not be used.");
|
|
assert(!V->getType()->isVectorTy() && "Can't widen a vector");
|
|
|
|
// If we have a stride that is replaced by one, do it here.
|
|
if (Legal->hasStride(V))
|
|
V = ConstantInt::get(V->getType(), 1);
|
|
|
|
// If we have this scalar in the map, return it.
|
|
if (WidenMap.has(V))
|
|
return WidenMap.get(V);
|
|
|
|
// If this scalar is unknown, assume that it is a constant or that it is
|
|
// loop invariant. Broadcast V and save the value for future uses.
|
|
Value *B = getBroadcastInstrs(V);
|
|
return WidenMap.splat(V, B);
|
|
}
|
|
|
|
Value *InnerLoopVectorizer::reverseVector(Value *Vec) {
|
|
assert(Vec->getType()->isVectorTy() && "Invalid type");
|
|
SmallVector<Constant*, 8> ShuffleMask;
|
|
for (unsigned i = 0; i < VF; ++i)
|
|
ShuffleMask.push_back(Builder.getInt32(VF - i - 1));
|
|
|
|
return Builder.CreateShuffleVector(Vec, UndefValue::get(Vec->getType()),
|
|
ConstantVector::get(ShuffleMask),
|
|
"reverse");
|
|
}
|
|
|
|
void InnerLoopVectorizer::vectorizeMemoryInstruction(Instruction *Instr) {
|
|
// Attempt to issue a wide load.
|
|
LoadInst *LI = dyn_cast<LoadInst>(Instr);
|
|
StoreInst *SI = dyn_cast<StoreInst>(Instr);
|
|
|
|
assert((LI || SI) && "Invalid Load/Store instruction");
|
|
|
|
Type *ScalarDataTy = LI ? LI->getType() : SI->getValueOperand()->getType();
|
|
Type *DataTy = VectorType::get(ScalarDataTy, VF);
|
|
Value *Ptr = LI ? LI->getPointerOperand() : SI->getPointerOperand();
|
|
unsigned Alignment = LI ? LI->getAlignment() : SI->getAlignment();
|
|
// An alignment of 0 means target abi alignment. We need to use the scalar's
|
|
// target abi alignment in such a case.
|
|
if (!Alignment)
|
|
Alignment = DL->getABITypeAlignment(ScalarDataTy);
|
|
unsigned AddressSpace = Ptr->getType()->getPointerAddressSpace();
|
|
unsigned ScalarAllocatedSize = DL->getTypeAllocSize(ScalarDataTy);
|
|
unsigned VectorElementSize = DL->getTypeStoreSize(DataTy)/VF;
|
|
|
|
if (SI && Legal->blockNeedsPredication(SI->getParent()) &&
|
|
!Legal->isMaskRequired(SI))
|
|
return scalarizeInstruction(Instr, true);
|
|
|
|
if (ScalarAllocatedSize != VectorElementSize)
|
|
return scalarizeInstruction(Instr);
|
|
|
|
// If the pointer is loop invariant or if it is non-consecutive,
|
|
// scalarize the load.
|
|
int ConsecutiveStride = Legal->isConsecutivePtr(Ptr);
|
|
bool Reverse = ConsecutiveStride < 0;
|
|
bool UniformLoad = LI && Legal->isUniform(Ptr);
|
|
if (!ConsecutiveStride || UniformLoad)
|
|
return scalarizeInstruction(Instr);
|
|
|
|
Constant *Zero = Builder.getInt32(0);
|
|
VectorParts &Entry = WidenMap.get(Instr);
|
|
|
|
// Handle consecutive loads/stores.
|
|
GetElementPtrInst *Gep = dyn_cast<GetElementPtrInst>(Ptr);
|
|
if (Gep && Legal->isInductionVariable(Gep->getPointerOperand())) {
|
|
setDebugLocFromInst(Builder, Gep);
|
|
Value *PtrOperand = Gep->getPointerOperand();
|
|
Value *FirstBasePtr = getVectorValue(PtrOperand)[0];
|
|
FirstBasePtr = Builder.CreateExtractElement(FirstBasePtr, Zero);
|
|
|
|
// Create the new GEP with the new induction variable.
|
|
GetElementPtrInst *Gep2 = cast<GetElementPtrInst>(Gep->clone());
|
|
Gep2->setOperand(0, FirstBasePtr);
|
|
Gep2->setName("gep.indvar.base");
|
|
Ptr = Builder.Insert(Gep2);
|
|
} else if (Gep) {
|
|
setDebugLocFromInst(Builder, Gep);
|
|
assert(SE->isLoopInvariant(SE->getSCEV(Gep->getPointerOperand()),
|
|
OrigLoop) && "Base ptr must be invariant");
|
|
|
|
// The last index does not have to be the induction. It can be
|
|
// consecutive and be a function of the index. For example A[I+1];
|
|
unsigned NumOperands = Gep->getNumOperands();
|
|
unsigned InductionOperand = getGEPInductionOperand(DL, Gep);
|
|
// Create the new GEP with the new induction variable.
|
|
GetElementPtrInst *Gep2 = cast<GetElementPtrInst>(Gep->clone());
|
|
|
|
for (unsigned i = 0; i < NumOperands; ++i) {
|
|
Value *GepOperand = Gep->getOperand(i);
|
|
Instruction *GepOperandInst = dyn_cast<Instruction>(GepOperand);
|
|
|
|
// Update last index or loop invariant instruction anchored in loop.
|
|
if (i == InductionOperand ||
|
|
(GepOperandInst && OrigLoop->contains(GepOperandInst))) {
|
|
assert((i == InductionOperand ||
|
|
SE->isLoopInvariant(SE->getSCEV(GepOperandInst), OrigLoop)) &&
|
|
"Must be last index or loop invariant");
|
|
|
|
VectorParts &GEPParts = getVectorValue(GepOperand);
|
|
Value *Index = GEPParts[0];
|
|
Index = Builder.CreateExtractElement(Index, Zero);
|
|
Gep2->setOperand(i, Index);
|
|
Gep2->setName("gep.indvar.idx");
|
|
}
|
|
}
|
|
Ptr = Builder.Insert(Gep2);
|
|
} else {
|
|
// Use the induction element ptr.
|
|
assert(isa<PHINode>(Ptr) && "Invalid induction ptr");
|
|
setDebugLocFromInst(Builder, Ptr);
|
|
VectorParts &PtrVal = getVectorValue(Ptr);
|
|
Ptr = Builder.CreateExtractElement(PtrVal[0], Zero);
|
|
}
|
|
|
|
VectorParts Mask = createBlockInMask(Instr->getParent());
|
|
// Handle Stores:
|
|
if (SI) {
|
|
assert(!Legal->isUniform(SI->getPointerOperand()) &&
|
|
"We do not allow storing to uniform addresses");
|
|
setDebugLocFromInst(Builder, SI);
|
|
// We don't want to update the value in the map as it might be used in
|
|
// another expression. So don't use a reference type for "StoredVal".
|
|
VectorParts StoredVal = getVectorValue(SI->getValueOperand());
|
|
|
|
for (unsigned Part = 0; Part < UF; ++Part) {
|
|
// Calculate the pointer for the specific unroll-part.
|
|
Value *PartPtr = Builder.CreateGEP(Ptr, Builder.getInt32(Part * VF));
|
|
|
|
if (Reverse) {
|
|
// If we store to reverse consecutive memory locations then we need
|
|
// to reverse the order of elements in the stored value.
|
|
StoredVal[Part] = reverseVector(StoredVal[Part]);
|
|
// If the address is consecutive but reversed, then the
|
|
// wide store needs to start at the last vector element.
|
|
PartPtr = Builder.CreateGEP(Ptr, Builder.getInt32(-Part * VF));
|
|
PartPtr = Builder.CreateGEP(PartPtr, Builder.getInt32(1 - VF));
|
|
Mask[Part] = reverseVector(Mask[Part]);
|
|
}
|
|
|
|
Value *VecPtr = Builder.CreateBitCast(PartPtr,
|
|
DataTy->getPointerTo(AddressSpace));
|
|
|
|
Instruction *NewSI;
|
|
if (Legal->isMaskRequired(SI))
|
|
NewSI = Builder.CreateMaskedStore(StoredVal[Part], VecPtr, Alignment,
|
|
Mask[Part]);
|
|
else
|
|
NewSI = Builder.CreateAlignedStore(StoredVal[Part], VecPtr, Alignment);
|
|
propagateMetadata(NewSI, SI);
|
|
}
|
|
return;
|
|
}
|
|
|
|
// Handle loads.
|
|
assert(LI && "Must have a load instruction");
|
|
setDebugLocFromInst(Builder, LI);
|
|
for (unsigned Part = 0; Part < UF; ++Part) {
|
|
// Calculate the pointer for the specific unroll-part.
|
|
Value *PartPtr = Builder.CreateGEP(Ptr, Builder.getInt32(Part * VF));
|
|
|
|
if (Reverse) {
|
|
// If the address is consecutive but reversed, then the
|
|
// wide load needs to start at the last vector element.
|
|
PartPtr = Builder.CreateGEP(Ptr, Builder.getInt32(-Part * VF));
|
|
PartPtr = Builder.CreateGEP(PartPtr, Builder.getInt32(1 - VF));
|
|
Mask[Part] = reverseVector(Mask[Part]);
|
|
}
|
|
|
|
Instruction* NewLI;
|
|
Value *VecPtr = Builder.CreateBitCast(PartPtr,
|
|
DataTy->getPointerTo(AddressSpace));
|
|
if (Legal->isMaskRequired(LI))
|
|
NewLI = Builder.CreateMaskedLoad(VecPtr, Alignment, Mask[Part],
|
|
UndefValue::get(DataTy),
|
|
"wide.masked.load");
|
|
else
|
|
NewLI = Builder.CreateAlignedLoad(VecPtr, Alignment, "wide.load");
|
|
propagateMetadata(NewLI, LI);
|
|
Entry[Part] = Reverse ? reverseVector(NewLI) : NewLI;
|
|
}
|
|
}
|
|
|
|
void InnerLoopVectorizer::scalarizeInstruction(Instruction *Instr, bool IfPredicateStore) {
|
|
assert(!Instr->getType()->isAggregateType() && "Can't handle vectors");
|
|
// Holds vector parameters or scalars, in case of uniform vals.
|
|
SmallVector<VectorParts, 4> Params;
|
|
|
|
setDebugLocFromInst(Builder, Instr);
|
|
|
|
// Find all of the vectorized parameters.
|
|
for (unsigned op = 0, e = Instr->getNumOperands(); op != e; ++op) {
|
|
Value *SrcOp = Instr->getOperand(op);
|
|
|
|
// If we are accessing the old induction variable, use the new one.
|
|
if (SrcOp == OldInduction) {
|
|
Params.push_back(getVectorValue(SrcOp));
|
|
continue;
|
|
}
|
|
|
|
// Try using previously calculated values.
|
|
Instruction *SrcInst = dyn_cast<Instruction>(SrcOp);
|
|
|
|
// If the src is an instruction that appeared earlier in the basic block
|
|
// then it should already be vectorized.
|
|
if (SrcInst && OrigLoop->contains(SrcInst)) {
|
|
assert(WidenMap.has(SrcInst) && "Source operand is unavailable");
|
|
// The parameter is a vector value from earlier.
|
|
Params.push_back(WidenMap.get(SrcInst));
|
|
} else {
|
|
// The parameter is a scalar from outside the loop. Maybe even a constant.
|
|
VectorParts Scalars;
|
|
Scalars.append(UF, SrcOp);
|
|
Params.push_back(Scalars);
|
|
}
|
|
}
|
|
|
|
assert(Params.size() == Instr->getNumOperands() &&
|
|
"Invalid number of operands");
|
|
|
|
// Does this instruction return a value ?
|
|
bool IsVoidRetTy = Instr->getType()->isVoidTy();
|
|
|
|
Value *UndefVec = IsVoidRetTy ? nullptr :
|
|
UndefValue::get(VectorType::get(Instr->getType(), VF));
|
|
// Create a new entry in the WidenMap and initialize it to Undef or Null.
|
|
VectorParts &VecResults = WidenMap.splat(Instr, UndefVec);
|
|
|
|
Instruction *InsertPt = Builder.GetInsertPoint();
|
|
BasicBlock *IfBlock = Builder.GetInsertBlock();
|
|
BasicBlock *CondBlock = nullptr;
|
|
|
|
VectorParts Cond;
|
|
Loop *VectorLp = nullptr;
|
|
if (IfPredicateStore) {
|
|
assert(Instr->getParent()->getSinglePredecessor() &&
|
|
"Only support single predecessor blocks");
|
|
Cond = createEdgeMask(Instr->getParent()->getSinglePredecessor(),
|
|
Instr->getParent());
|
|
VectorLp = LI->getLoopFor(IfBlock);
|
|
assert(VectorLp && "Must have a loop for this block");
|
|
}
|
|
|
|
// For each vector unroll 'part':
|
|
for (unsigned Part = 0; Part < UF; ++Part) {
|
|
// For each scalar that we create:
|
|
for (unsigned Width = 0; Width < VF; ++Width) {
|
|
|
|
// Start if-block.
|
|
Value *Cmp = nullptr;
|
|
if (IfPredicateStore) {
|
|
Cmp = Builder.CreateExtractElement(Cond[Part], Builder.getInt32(Width));
|
|
Cmp = Builder.CreateICmp(ICmpInst::ICMP_EQ, Cmp, ConstantInt::get(Cmp->getType(), 1));
|
|
CondBlock = IfBlock->splitBasicBlock(InsertPt, "cond.store");
|
|
LoopVectorBody.push_back(CondBlock);
|
|
VectorLp->addBasicBlockToLoop(CondBlock, *LI);
|
|
// Update Builder with newly created basic block.
|
|
Builder.SetInsertPoint(InsertPt);
|
|
}
|
|
|
|
Instruction *Cloned = Instr->clone();
|
|
if (!IsVoidRetTy)
|
|
Cloned->setName(Instr->getName() + ".cloned");
|
|
// Replace the operands of the cloned instructions with extracted scalars.
|
|
for (unsigned op = 0, e = Instr->getNumOperands(); op != e; ++op) {
|
|
Value *Op = Params[op][Part];
|
|
// Param is a vector. Need to extract the right lane.
|
|
if (Op->getType()->isVectorTy())
|
|
Op = Builder.CreateExtractElement(Op, Builder.getInt32(Width));
|
|
Cloned->setOperand(op, Op);
|
|
}
|
|
|
|
// Place the cloned scalar in the new loop.
|
|
Builder.Insert(Cloned);
|
|
|
|
// If the original scalar returns a value we need to place it in a vector
|
|
// so that future users will be able to use it.
|
|
if (!IsVoidRetTy)
|
|
VecResults[Part] = Builder.CreateInsertElement(VecResults[Part], Cloned,
|
|
Builder.getInt32(Width));
|
|
// End if-block.
|
|
if (IfPredicateStore) {
|
|
BasicBlock *NewIfBlock = CondBlock->splitBasicBlock(InsertPt, "else");
|
|
LoopVectorBody.push_back(NewIfBlock);
|
|
VectorLp->addBasicBlockToLoop(NewIfBlock, *LI);
|
|
Builder.SetInsertPoint(InsertPt);
|
|
Instruction *OldBr = IfBlock->getTerminator();
|
|
BranchInst::Create(CondBlock, NewIfBlock, Cmp, OldBr);
|
|
OldBr->eraseFromParent();
|
|
IfBlock = NewIfBlock;
|
|
}
|
|
}
|
|
}
|
|
}
|
|
|
|
static Instruction *getFirstInst(Instruction *FirstInst, Value *V,
|
|
Instruction *Loc) {
|
|
if (FirstInst)
|
|
return FirstInst;
|
|
if (Instruction *I = dyn_cast<Instruction>(V))
|
|
return I->getParent() == Loc->getParent() ? I : nullptr;
|
|
return nullptr;
|
|
}
|
|
|
|
std::pair<Instruction *, Instruction *>
|
|
InnerLoopVectorizer::addStrideCheck(Instruction *Loc) {
|
|
Instruction *tnullptr = nullptr;
|
|
if (!Legal->mustCheckStrides())
|
|
return std::pair<Instruction *, Instruction *>(tnullptr, tnullptr);
|
|
|
|
IRBuilder<> ChkBuilder(Loc);
|
|
|
|
// Emit checks.
|
|
Value *Check = nullptr;
|
|
Instruction *FirstInst = nullptr;
|
|
for (SmallPtrSet<Value *, 8>::iterator SI = Legal->strides_begin(),
|
|
SE = Legal->strides_end();
|
|
SI != SE; ++SI) {
|
|
Value *Ptr = stripIntegerCast(*SI);
|
|
Value *C = ChkBuilder.CreateICmpNE(Ptr, ConstantInt::get(Ptr->getType(), 1),
|
|
"stride.chk");
|
|
// Store the first instruction we create.
|
|
FirstInst = getFirstInst(FirstInst, C, Loc);
|
|
if (Check)
|
|
Check = ChkBuilder.CreateOr(Check, C);
|
|
else
|
|
Check = C;
|
|
}
|
|
|
|
// We have to do this trickery because the IRBuilder might fold the check to a
|
|
// constant expression in which case there is no Instruction anchored in a
|
|
// the block.
|
|
LLVMContext &Ctx = Loc->getContext();
|
|
Instruction *TheCheck =
|
|
BinaryOperator::CreateAnd(Check, ConstantInt::getTrue(Ctx));
|
|
ChkBuilder.Insert(TheCheck, "stride.not.one");
|
|
FirstInst = getFirstInst(FirstInst, TheCheck, Loc);
|
|
|
|
return std::make_pair(FirstInst, TheCheck);
|
|
}
|
|
|
|
void InnerLoopVectorizer::createEmptyLoop() {
|
|
/*
|
|
In this function we generate a new loop. The new loop will contain
|
|
the vectorized instructions while the old loop will continue to run the
|
|
scalar remainder.
|
|
|
|
[ ] <-- Back-edge taken count overflow check.
|
|
/ |
|
|
/ v
|
|
| [ ] <-- vector loop bypass (may consist of multiple blocks).
|
|
| / |
|
|
| / v
|
|
|| [ ] <-- vector pre header.
|
|
|| |
|
|
|| v
|
|
|| [ ] \
|
|
|| [ ]_| <-- vector loop.
|
|
|| |
|
|
| \ v
|
|
| >[ ] <--- middle-block.
|
|
| / |
|
|
| / v
|
|
-|- >[ ] <--- new preheader.
|
|
| |
|
|
| v
|
|
| [ ] \
|
|
| [ ]_| <-- old scalar loop to handle remainder.
|
|
\ |
|
|
\ v
|
|
>[ ] <-- exit block.
|
|
...
|
|
*/
|
|
|
|
BasicBlock *OldBasicBlock = OrigLoop->getHeader();
|
|
BasicBlock *BypassBlock = OrigLoop->getLoopPreheader();
|
|
BasicBlock *ExitBlock = OrigLoop->getExitBlock();
|
|
assert(BypassBlock && "Invalid loop structure");
|
|
assert(ExitBlock && "Must have an exit block");
|
|
|
|
// Some loops have a single integer induction variable, while other loops
|
|
// don't. One example is c++ iterators that often have multiple pointer
|
|
// induction variables. In the code below we also support a case where we
|
|
// don't have a single induction variable.
|
|
OldInduction = Legal->getInduction();
|
|
Type *IdxTy = Legal->getWidestInductionType();
|
|
|
|
// Find the loop boundaries.
|
|
const SCEV *ExitCount = SE->getBackedgeTakenCount(OrigLoop);
|
|
assert(ExitCount != SE->getCouldNotCompute() && "Invalid loop count");
|
|
|
|
// The exit count might have the type of i64 while the phi is i32. This can
|
|
// happen if we have an induction variable that is sign extended before the
|
|
// compare. The only way that we get a backedge taken count is that the
|
|
// induction variable was signed and as such will not overflow. In such a case
|
|
// truncation is legal.
|
|
if (ExitCount->getType()->getPrimitiveSizeInBits() >
|
|
IdxTy->getPrimitiveSizeInBits())
|
|
ExitCount = SE->getTruncateOrNoop(ExitCount, IdxTy);
|
|
|
|
const SCEV *BackedgeTakeCount = SE->getNoopOrZeroExtend(ExitCount, IdxTy);
|
|
// Get the total trip count from the count by adding 1.
|
|
ExitCount = SE->getAddExpr(BackedgeTakeCount,
|
|
SE->getConstant(BackedgeTakeCount->getType(), 1));
|
|
|
|
// Expand the trip count and place the new instructions in the preheader.
|
|
// Notice that the pre-header does not change, only the loop body.
|
|
SCEVExpander Exp(*SE, "induction");
|
|
|
|
// We need to test whether the backedge-taken count is uint##_max. Adding one
|
|
// to it will cause overflow and an incorrect loop trip count in the vector
|
|
// body. In case of overflow we want to directly jump to the scalar remainder
|
|
// loop.
|
|
Value *BackedgeCount =
|
|
Exp.expandCodeFor(BackedgeTakeCount, BackedgeTakeCount->getType(),
|
|
BypassBlock->getTerminator());
|
|
if (BackedgeCount->getType()->isPointerTy())
|
|
BackedgeCount = CastInst::CreatePointerCast(BackedgeCount, IdxTy,
|
|
"backedge.ptrcnt.to.int",
|
|
BypassBlock->getTerminator());
|
|
Instruction *CheckBCOverflow =
|
|
CmpInst::Create(Instruction::ICmp, CmpInst::ICMP_EQ, BackedgeCount,
|
|
Constant::getAllOnesValue(BackedgeCount->getType()),
|
|
"backedge.overflow", BypassBlock->getTerminator());
|
|
|
|
// The loop index does not have to start at Zero. Find the original start
|
|
// value from the induction PHI node. If we don't have an induction variable
|
|
// then we know that it starts at zero.
|
|
Builder.SetInsertPoint(BypassBlock->getTerminator());
|
|
Value *StartIdx = ExtendedIdx = OldInduction ?
|
|
Builder.CreateZExt(OldInduction->getIncomingValueForBlock(BypassBlock),
|
|
IdxTy):
|
|
ConstantInt::get(IdxTy, 0);
|
|
|
|
// We need an instruction to anchor the overflow check on. StartIdx needs to
|
|
// be defined before the overflow check branch. Because the scalar preheader
|
|
// is going to merge the start index and so the overflow branch block needs to
|
|
// contain a definition of the start index.
|
|
Instruction *OverflowCheckAnchor = BinaryOperator::CreateAdd(
|
|
StartIdx, ConstantInt::get(IdxTy, 0), "overflow.check.anchor",
|
|
BypassBlock->getTerminator());
|
|
|
|
// Count holds the overall loop count (N).
|
|
Value *Count = Exp.expandCodeFor(ExitCount, ExitCount->getType(),
|
|
BypassBlock->getTerminator());
|
|
|
|
LoopBypassBlocks.push_back(BypassBlock);
|
|
|
|
// Split the single block loop into the two loop structure described above.
|
|
BasicBlock *VectorPH =
|
|
BypassBlock->splitBasicBlock(BypassBlock->getTerminator(), "vector.ph");
|
|
BasicBlock *VecBody =
|
|
VectorPH->splitBasicBlock(VectorPH->getTerminator(), "vector.body");
|
|
BasicBlock *MiddleBlock =
|
|
VecBody->splitBasicBlock(VecBody->getTerminator(), "middle.block");
|
|
BasicBlock *ScalarPH =
|
|
MiddleBlock->splitBasicBlock(MiddleBlock->getTerminator(), "scalar.ph");
|
|
|
|
// Create and register the new vector loop.
|
|
Loop* Lp = new Loop();
|
|
Loop *ParentLoop = OrigLoop->getParentLoop();
|
|
|
|
// Insert the new loop into the loop nest and register the new basic blocks
|
|
// before calling any utilities such as SCEV that require valid LoopInfo.
|
|
if (ParentLoop) {
|
|
ParentLoop->addChildLoop(Lp);
|
|
ParentLoop->addBasicBlockToLoop(ScalarPH, *LI);
|
|
ParentLoop->addBasicBlockToLoop(VectorPH, *LI);
|
|
ParentLoop->addBasicBlockToLoop(MiddleBlock, *LI);
|
|
} else {
|
|
LI->addTopLevelLoop(Lp);
|
|
}
|
|
Lp->addBasicBlockToLoop(VecBody, *LI);
|
|
|
|
// Use this IR builder to create the loop instructions (Phi, Br, Cmp)
|
|
// inside the loop.
|
|
Builder.SetInsertPoint(VecBody->getFirstNonPHI());
|
|
|
|
// Generate the induction variable.
|
|
setDebugLocFromInst(Builder, getDebugLocFromInstOrOperands(OldInduction));
|
|
Induction = Builder.CreatePHI(IdxTy, 2, "index");
|
|
// The loop step is equal to the vectorization factor (num of SIMD elements)
|
|
// times the unroll factor (num of SIMD instructions).
|
|
Constant *Step = ConstantInt::get(IdxTy, VF * UF);
|
|
|
|
// This is the IR builder that we use to add all of the logic for bypassing
|
|
// the new vector loop.
|
|
IRBuilder<> BypassBuilder(BypassBlock->getTerminator());
|
|
setDebugLocFromInst(BypassBuilder,
|
|
getDebugLocFromInstOrOperands(OldInduction));
|
|
|
|
// We may need to extend the index in case there is a type mismatch.
|
|
// We know that the count starts at zero and does not overflow.
|
|
if (Count->getType() != IdxTy) {
|
|
// The exit count can be of pointer type. Convert it to the correct
|
|
// integer type.
|
|
if (ExitCount->getType()->isPointerTy())
|
|
Count = BypassBuilder.CreatePointerCast(Count, IdxTy, "ptrcnt.to.int");
|
|
else
|
|
Count = BypassBuilder.CreateZExtOrTrunc(Count, IdxTy, "cnt.cast");
|
|
}
|
|
|
|
// Add the start index to the loop count to get the new end index.
|
|
Value *IdxEnd = BypassBuilder.CreateAdd(Count, StartIdx, "end.idx");
|
|
|
|
// Now we need to generate the expression for N - (N % VF), which is
|
|
// the part that the vectorized body will execute.
|
|
Value *R = BypassBuilder.CreateURem(Count, Step, "n.mod.vf");
|
|
Value *CountRoundDown = BypassBuilder.CreateSub(Count, R, "n.vec");
|
|
Value *IdxEndRoundDown = BypassBuilder.CreateAdd(CountRoundDown, StartIdx,
|
|
"end.idx.rnd.down");
|
|
|
|
// Now, compare the new count to zero. If it is zero skip the vector loop and
|
|
// jump to the scalar loop.
|
|
Value *Cmp =
|
|
BypassBuilder.CreateICmpEQ(IdxEndRoundDown, StartIdx, "cmp.zero");
|
|
|
|
BasicBlock *LastBypassBlock = BypassBlock;
|
|
|
|
// Generate code to check that the loops trip count that we computed by adding
|
|
// one to the backedge-taken count will not overflow.
|
|
{
|
|
auto PastOverflowCheck =
|
|
std::next(BasicBlock::iterator(OverflowCheckAnchor));
|
|
BasicBlock *CheckBlock =
|
|
LastBypassBlock->splitBasicBlock(PastOverflowCheck, "overflow.checked");
|
|
if (ParentLoop)
|
|
ParentLoop->addBasicBlockToLoop(CheckBlock, *LI);
|
|
LoopBypassBlocks.push_back(CheckBlock);
|
|
Instruction *OldTerm = LastBypassBlock->getTerminator();
|
|
BranchInst::Create(ScalarPH, CheckBlock, CheckBCOverflow, OldTerm);
|
|
OldTerm->eraseFromParent();
|
|
LastBypassBlock = CheckBlock;
|
|
}
|
|
|
|
// Generate the code to check that the strides we assumed to be one are really
|
|
// one. We want the new basic block to start at the first instruction in a
|
|
// sequence of instructions that form a check.
|
|
Instruction *StrideCheck;
|
|
Instruction *FirstCheckInst;
|
|
std::tie(FirstCheckInst, StrideCheck) =
|
|
addStrideCheck(LastBypassBlock->getTerminator());
|
|
if (StrideCheck) {
|
|
// Create a new block containing the stride check.
|
|
BasicBlock *CheckBlock =
|
|
LastBypassBlock->splitBasicBlock(FirstCheckInst, "vector.stridecheck");
|
|
if (ParentLoop)
|
|
ParentLoop->addBasicBlockToLoop(CheckBlock, *LI);
|
|
LoopBypassBlocks.push_back(CheckBlock);
|
|
|
|
// Replace the branch into the memory check block with a conditional branch
|
|
// for the "few elements case".
|
|
Instruction *OldTerm = LastBypassBlock->getTerminator();
|
|
BranchInst::Create(MiddleBlock, CheckBlock, Cmp, OldTerm);
|
|
OldTerm->eraseFromParent();
|
|
|
|
Cmp = StrideCheck;
|
|
LastBypassBlock = CheckBlock;
|
|
}
|
|
|
|
// Generate the code that checks in runtime if arrays overlap. We put the
|
|
// checks into a separate block to make the more common case of few elements
|
|
// faster.
|
|
Instruction *MemRuntimeCheck;
|
|
std::tie(FirstCheckInst, MemRuntimeCheck) =
|
|
Legal->getLAI()->addRuntimeCheck(LastBypassBlock->getTerminator());
|
|
if (MemRuntimeCheck) {
|
|
// Create a new block containing the memory check.
|
|
BasicBlock *CheckBlock =
|
|
LastBypassBlock->splitBasicBlock(FirstCheckInst, "vector.memcheck");
|
|
if (ParentLoop)
|
|
ParentLoop->addBasicBlockToLoop(CheckBlock, *LI);
|
|
LoopBypassBlocks.push_back(CheckBlock);
|
|
|
|
// Replace the branch into the memory check block with a conditional branch
|
|
// for the "few elements case".
|
|
Instruction *OldTerm = LastBypassBlock->getTerminator();
|
|
BranchInst::Create(MiddleBlock, CheckBlock, Cmp, OldTerm);
|
|
OldTerm->eraseFromParent();
|
|
|
|
Cmp = MemRuntimeCheck;
|
|
LastBypassBlock = CheckBlock;
|
|
}
|
|
|
|
LastBypassBlock->getTerminator()->eraseFromParent();
|
|
BranchInst::Create(MiddleBlock, VectorPH, Cmp,
|
|
LastBypassBlock);
|
|
|
|
// We are going to resume the execution of the scalar loop.
|
|
// Go over all of the induction variables that we found and fix the
|
|
// PHIs that are left in the scalar version of the loop.
|
|
// The starting values of PHI nodes depend on the counter of the last
|
|
// iteration in the vectorized loop.
|
|
// If we come from a bypass edge then we need to start from the original
|
|
// start value.
|
|
|
|
// This variable saves the new starting index for the scalar loop.
|
|
PHINode *ResumeIndex = nullptr;
|
|
LoopVectorizationLegality::InductionList::iterator I, E;
|
|
LoopVectorizationLegality::InductionList *List = Legal->getInductionVars();
|
|
// Set builder to point to last bypass block.
|
|
BypassBuilder.SetInsertPoint(LoopBypassBlocks.back()->getTerminator());
|
|
for (I = List->begin(), E = List->end(); I != E; ++I) {
|
|
PHINode *OrigPhi = I->first;
|
|
LoopVectorizationLegality::InductionInfo II = I->second;
|
|
|
|
Type *ResumeValTy = (OrigPhi == OldInduction) ? IdxTy : OrigPhi->getType();
|
|
PHINode *ResumeVal = PHINode::Create(ResumeValTy, 2, "resume.val",
|
|
MiddleBlock->getTerminator());
|
|
// We might have extended the type of the induction variable but we need a
|
|
// truncated version for the scalar loop.
|
|
PHINode *TruncResumeVal = (OrigPhi == OldInduction) ?
|
|
PHINode::Create(OrigPhi->getType(), 2, "trunc.resume.val",
|
|
MiddleBlock->getTerminator()) : nullptr;
|
|
|
|
// Create phi nodes to merge from the backedge-taken check block.
|
|
PHINode *BCResumeVal = PHINode::Create(ResumeValTy, 3, "bc.resume.val",
|
|
ScalarPH->getTerminator());
|
|
BCResumeVal->addIncoming(ResumeVal, MiddleBlock);
|
|
|
|
PHINode *BCTruncResumeVal = nullptr;
|
|
if (OrigPhi == OldInduction) {
|
|
BCTruncResumeVal =
|
|
PHINode::Create(OrigPhi->getType(), 2, "bc.trunc.resume.val",
|
|
ScalarPH->getTerminator());
|
|
BCTruncResumeVal->addIncoming(TruncResumeVal, MiddleBlock);
|
|
}
|
|
|
|
Value *EndValue = nullptr;
|
|
switch (II.IK) {
|
|
case LoopVectorizationLegality::IK_NoInduction:
|
|
llvm_unreachable("Unknown induction");
|
|
case LoopVectorizationLegality::IK_IntInduction: {
|
|
// Handle the integer induction counter.
|
|
assert(OrigPhi->getType()->isIntegerTy() && "Invalid type");
|
|
|
|
// We have the canonical induction variable.
|
|
if (OrigPhi == OldInduction) {
|
|
// Create a truncated version of the resume value for the scalar loop,
|
|
// we might have promoted the type to a larger width.
|
|
EndValue =
|
|
BypassBuilder.CreateTrunc(IdxEndRoundDown, OrigPhi->getType());
|
|
// The new PHI merges the original incoming value, in case of a bypass,
|
|
// or the value at the end of the vectorized loop.
|
|
for (unsigned I = 1, E = LoopBypassBlocks.size(); I != E; ++I)
|
|
TruncResumeVal->addIncoming(II.StartValue, LoopBypassBlocks[I]);
|
|
TruncResumeVal->addIncoming(EndValue, VecBody);
|
|
|
|
BCTruncResumeVal->addIncoming(II.StartValue, LoopBypassBlocks[0]);
|
|
|
|
// We know what the end value is.
|
|
EndValue = IdxEndRoundDown;
|
|
// We also know which PHI node holds it.
|
|
ResumeIndex = ResumeVal;
|
|
break;
|
|
}
|
|
|
|
// Not the canonical induction variable - add the vector loop count to the
|
|
// start value.
|
|
Value *CRD = BypassBuilder.CreateSExtOrTrunc(CountRoundDown,
|
|
II.StartValue->getType(),
|
|
"cast.crd");
|
|
EndValue = II.transform(BypassBuilder, CRD);
|
|
EndValue->setName("ind.end");
|
|
break;
|
|
}
|
|
case LoopVectorizationLegality::IK_PtrInduction: {
|
|
EndValue = II.transform(BypassBuilder, CountRoundDown);
|
|
EndValue->setName("ptr.ind.end");
|
|
break;
|
|
}
|
|
}// end of case
|
|
|
|
// The new PHI merges the original incoming value, in case of a bypass,
|
|
// or the value at the end of the vectorized loop.
|
|
for (unsigned I = 1, E = LoopBypassBlocks.size(); I != E; ++I) {
|
|
if (OrigPhi == OldInduction)
|
|
ResumeVal->addIncoming(StartIdx, LoopBypassBlocks[I]);
|
|
else
|
|
ResumeVal->addIncoming(II.StartValue, LoopBypassBlocks[I]);
|
|
}
|
|
ResumeVal->addIncoming(EndValue, VecBody);
|
|
|
|
// Fix the scalar body counter (PHI node).
|
|
unsigned BlockIdx = OrigPhi->getBasicBlockIndex(ScalarPH);
|
|
|
|
// The old induction's phi node in the scalar body needs the truncated
|
|
// value.
|
|
if (OrigPhi == OldInduction) {
|
|
BCResumeVal->addIncoming(StartIdx, LoopBypassBlocks[0]);
|
|
OrigPhi->setIncomingValue(BlockIdx, BCTruncResumeVal);
|
|
} else {
|
|
BCResumeVal->addIncoming(II.StartValue, LoopBypassBlocks[0]);
|
|
OrigPhi->setIncomingValue(BlockIdx, BCResumeVal);
|
|
}
|
|
}
|
|
|
|
// If we are generating a new induction variable then we also need to
|
|
// generate the code that calculates the exit value. This value is not
|
|
// simply the end of the counter because we may skip the vectorized body
|
|
// in case of a runtime check.
|
|
if (!OldInduction){
|
|
assert(!ResumeIndex && "Unexpected resume value found");
|
|
ResumeIndex = PHINode::Create(IdxTy, 2, "new.indc.resume.val",
|
|
MiddleBlock->getTerminator());
|
|
for (unsigned I = 1, E = LoopBypassBlocks.size(); I != E; ++I)
|
|
ResumeIndex->addIncoming(StartIdx, LoopBypassBlocks[I]);
|
|
ResumeIndex->addIncoming(IdxEndRoundDown, VecBody);
|
|
}
|
|
|
|
// Make sure that we found the index where scalar loop needs to continue.
|
|
assert(ResumeIndex && ResumeIndex->getType()->isIntegerTy() &&
|
|
"Invalid resume Index");
|
|
|
|
// Add a check in the middle block to see if we have completed
|
|
// all of the iterations in the first vector loop.
|
|
// If (N - N%VF) == N, then we *don't* need to run the remainder.
|
|
Value *CmpN = CmpInst::Create(Instruction::ICmp, CmpInst::ICMP_EQ, IdxEnd,
|
|
ResumeIndex, "cmp.n",
|
|
MiddleBlock->getTerminator());
|
|
|
|
BranchInst::Create(ExitBlock, ScalarPH, CmpN, MiddleBlock->getTerminator());
|
|
// Remove the old terminator.
|
|
MiddleBlock->getTerminator()->eraseFromParent();
|
|
|
|
// Create i+1 and fill the PHINode.
|
|
Value *NextIdx = Builder.CreateAdd(Induction, Step, "index.next");
|
|
Induction->addIncoming(StartIdx, VectorPH);
|
|
Induction->addIncoming(NextIdx, VecBody);
|
|
// Create the compare.
|
|
Value *ICmp = Builder.CreateICmpEQ(NextIdx, IdxEndRoundDown);
|
|
Builder.CreateCondBr(ICmp, MiddleBlock, VecBody);
|
|
|
|
// Now we have two terminators. Remove the old one from the block.
|
|
VecBody->getTerminator()->eraseFromParent();
|
|
|
|
// Get ready to start creating new instructions into the vectorized body.
|
|
Builder.SetInsertPoint(VecBody->getFirstInsertionPt());
|
|
|
|
// Save the state.
|
|
LoopVectorPreHeader = VectorPH;
|
|
LoopScalarPreHeader = ScalarPH;
|
|
LoopMiddleBlock = MiddleBlock;
|
|
LoopExitBlock = ExitBlock;
|
|
LoopVectorBody.push_back(VecBody);
|
|
LoopScalarBody = OldBasicBlock;
|
|
|
|
LoopVectorizeHints Hints(Lp, true);
|
|
Hints.setAlreadyVectorized();
|
|
}
|
|
|
|
/// This function returns the identity element (or neutral element) for
|
|
/// the operation K.
|
|
Constant*
|
|
LoopVectorizationLegality::getReductionIdentity(ReductionKind K, Type *Tp) {
|
|
switch (K) {
|
|
case RK_IntegerXor:
|
|
case RK_IntegerAdd:
|
|
case RK_IntegerOr:
|
|
// Adding, Xoring, Oring zero to a number does not change it.
|
|
return ConstantInt::get(Tp, 0);
|
|
case RK_IntegerMult:
|
|
// Multiplying a number by 1 does not change it.
|
|
return ConstantInt::get(Tp, 1);
|
|
case RK_IntegerAnd:
|
|
// AND-ing a number with an all-1 value does not change it.
|
|
return ConstantInt::get(Tp, -1, true);
|
|
case RK_FloatMult:
|
|
// Multiplying a number by 1 does not change it.
|
|
return ConstantFP::get(Tp, 1.0L);
|
|
case RK_FloatAdd:
|
|
// Adding zero to a number does not change it.
|
|
return ConstantFP::get(Tp, 0.0L);
|
|
default:
|
|
llvm_unreachable("Unknown reduction kind");
|
|
}
|
|
}
|
|
|
|
/// This function translates the reduction kind to an LLVM binary operator.
|
|
static unsigned
|
|
getReductionBinOp(LoopVectorizationLegality::ReductionKind Kind) {
|
|
switch (Kind) {
|
|
case LoopVectorizationLegality::RK_IntegerAdd:
|
|
return Instruction::Add;
|
|
case LoopVectorizationLegality::RK_IntegerMult:
|
|
return Instruction::Mul;
|
|
case LoopVectorizationLegality::RK_IntegerOr:
|
|
return Instruction::Or;
|
|
case LoopVectorizationLegality::RK_IntegerAnd:
|
|
return Instruction::And;
|
|
case LoopVectorizationLegality::RK_IntegerXor:
|
|
return Instruction::Xor;
|
|
case LoopVectorizationLegality::RK_FloatMult:
|
|
return Instruction::FMul;
|
|
case LoopVectorizationLegality::RK_FloatAdd:
|
|
return Instruction::FAdd;
|
|
case LoopVectorizationLegality::RK_IntegerMinMax:
|
|
return Instruction::ICmp;
|
|
case LoopVectorizationLegality::RK_FloatMinMax:
|
|
return Instruction::FCmp;
|
|
default:
|
|
llvm_unreachable("Unknown reduction operation");
|
|
}
|
|
}
|
|
|
|
Value *createMinMaxOp(IRBuilder<> &Builder,
|
|
LoopVectorizationLegality::MinMaxReductionKind RK,
|
|
Value *Left,
|
|
Value *Right) {
|
|
CmpInst::Predicate P = CmpInst::ICMP_NE;
|
|
switch (RK) {
|
|
default:
|
|
llvm_unreachable("Unknown min/max reduction kind");
|
|
case LoopVectorizationLegality::MRK_UIntMin:
|
|
P = CmpInst::ICMP_ULT;
|
|
break;
|
|
case LoopVectorizationLegality::MRK_UIntMax:
|
|
P = CmpInst::ICMP_UGT;
|
|
break;
|
|
case LoopVectorizationLegality::MRK_SIntMin:
|
|
P = CmpInst::ICMP_SLT;
|
|
break;
|
|
case LoopVectorizationLegality::MRK_SIntMax:
|
|
P = CmpInst::ICMP_SGT;
|
|
break;
|
|
case LoopVectorizationLegality::MRK_FloatMin:
|
|
P = CmpInst::FCMP_OLT;
|
|
break;
|
|
case LoopVectorizationLegality::MRK_FloatMax:
|
|
P = CmpInst::FCMP_OGT;
|
|
break;
|
|
}
|
|
|
|
Value *Cmp;
|
|
if (RK == LoopVectorizationLegality::MRK_FloatMin ||
|
|
RK == LoopVectorizationLegality::MRK_FloatMax)
|
|
Cmp = Builder.CreateFCmp(P, Left, Right, "rdx.minmax.cmp");
|
|
else
|
|
Cmp = Builder.CreateICmp(P, Left, Right, "rdx.minmax.cmp");
|
|
|
|
Value *Select = Builder.CreateSelect(Cmp, Left, Right, "rdx.minmax.select");
|
|
return Select;
|
|
}
|
|
|
|
namespace {
|
|
struct CSEDenseMapInfo {
|
|
static bool canHandle(Instruction *I) {
|
|
return isa<InsertElementInst>(I) || isa<ExtractElementInst>(I) ||
|
|
isa<ShuffleVectorInst>(I) || isa<GetElementPtrInst>(I);
|
|
}
|
|
static inline Instruction *getEmptyKey() {
|
|
return DenseMapInfo<Instruction *>::getEmptyKey();
|
|
}
|
|
static inline Instruction *getTombstoneKey() {
|
|
return DenseMapInfo<Instruction *>::getTombstoneKey();
|
|
}
|
|
static unsigned getHashValue(Instruction *I) {
|
|
assert(canHandle(I) && "Unknown instruction!");
|
|
return hash_combine(I->getOpcode(), hash_combine_range(I->value_op_begin(),
|
|
I->value_op_end()));
|
|
}
|
|
static bool isEqual(Instruction *LHS, Instruction *RHS) {
|
|
if (LHS == getEmptyKey() || RHS == getEmptyKey() ||
|
|
LHS == getTombstoneKey() || RHS == getTombstoneKey())
|
|
return LHS == RHS;
|
|
return LHS->isIdenticalTo(RHS);
|
|
}
|
|
};
|
|
}
|
|
|
|
/// \brief Check whether this block is a predicated block.
|
|
/// Due to if predication of stores we might create a sequence of "if(pred) a[i]
|
|
/// = ...; " blocks. We start with one vectorized basic block. For every
|
|
/// conditional block we split this vectorized block. Therefore, every second
|
|
/// block will be a predicated one.
|
|
static bool isPredicatedBlock(unsigned BlockNum) {
|
|
return BlockNum % 2;
|
|
}
|
|
|
|
///\brief Perform cse of induction variable instructions.
|
|
static void cse(SmallVector<BasicBlock *, 4> &BBs) {
|
|
// Perform simple cse.
|
|
SmallDenseMap<Instruction *, Instruction *, 4, CSEDenseMapInfo> CSEMap;
|
|
for (unsigned i = 0, e = BBs.size(); i != e; ++i) {
|
|
BasicBlock *BB = BBs[i];
|
|
for (BasicBlock::iterator I = BB->begin(), E = BB->end(); I != E;) {
|
|
Instruction *In = I++;
|
|
|
|
if (!CSEDenseMapInfo::canHandle(In))
|
|
continue;
|
|
|
|
// Check if we can replace this instruction with any of the
|
|
// visited instructions.
|
|
if (Instruction *V = CSEMap.lookup(In)) {
|
|
In->replaceAllUsesWith(V);
|
|
In->eraseFromParent();
|
|
continue;
|
|
}
|
|
// Ignore instructions in conditional blocks. We create "if (pred) a[i] =
|
|
// ...;" blocks for predicated stores. Every second block is a predicated
|
|
// block.
|
|
if (isPredicatedBlock(i))
|
|
continue;
|
|
|
|
CSEMap[In] = In;
|
|
}
|
|
}
|
|
}
|
|
|
|
/// \brief Adds a 'fast' flag to floating point operations.
|
|
static Value *addFastMathFlag(Value *V) {
|
|
if (isa<FPMathOperator>(V)){
|
|
FastMathFlags Flags;
|
|
Flags.setUnsafeAlgebra();
|
|
cast<Instruction>(V)->setFastMathFlags(Flags);
|
|
}
|
|
return V;
|
|
}
|
|
|
|
void InnerLoopVectorizer::vectorizeLoop() {
|
|
//===------------------------------------------------===//
|
|
//
|
|
// Notice: any optimization or new instruction that go
|
|
// into the code below should be also be implemented in
|
|
// the cost-model.
|
|
//
|
|
//===------------------------------------------------===//
|
|
Constant *Zero = Builder.getInt32(0);
|
|
|
|
// In order to support reduction variables we need to be able to vectorize
|
|
// Phi nodes. Phi nodes have cycles, so we need to vectorize them in two
|
|
// stages. First, we create a new vector PHI node with no incoming edges.
|
|
// We use this value when we vectorize all of the instructions that use the
|
|
// PHI. Next, after all of the instructions in the block are complete we
|
|
// add the new incoming edges to the PHI. At this point all of the
|
|
// instructions in the basic block are vectorized, so we can use them to
|
|
// construct the PHI.
|
|
PhiVector RdxPHIsToFix;
|
|
|
|
// Scan the loop in a topological order to ensure that defs are vectorized
|
|
// before users.
|
|
LoopBlocksDFS DFS(OrigLoop);
|
|
DFS.perform(LI);
|
|
|
|
// Vectorize all of the blocks in the original loop.
|
|
for (LoopBlocksDFS::RPOIterator bb = DFS.beginRPO(),
|
|
be = DFS.endRPO(); bb != be; ++bb)
|
|
vectorizeBlockInLoop(*bb, &RdxPHIsToFix);
|
|
|
|
// At this point every instruction in the original loop is widened to
|
|
// a vector form. We are almost done. Now, we need to fix the PHI nodes
|
|
// that we vectorized. The PHI nodes are currently empty because we did
|
|
// not want to introduce cycles. Notice that the remaining PHI nodes
|
|
// that we need to fix are reduction variables.
|
|
|
|
// Create the 'reduced' values for each of the induction vars.
|
|
// The reduced values are the vector values that we scalarize and combine
|
|
// after the loop is finished.
|
|
for (PhiVector::iterator it = RdxPHIsToFix.begin(), e = RdxPHIsToFix.end();
|
|
it != e; ++it) {
|
|
PHINode *RdxPhi = *it;
|
|
assert(RdxPhi && "Unable to recover vectorized PHI");
|
|
|
|
// Find the reduction variable descriptor.
|
|
assert(Legal->getReductionVars()->count(RdxPhi) &&
|
|
"Unable to find the reduction variable");
|
|
LoopVectorizationLegality::ReductionDescriptor RdxDesc =
|
|
(*Legal->getReductionVars())[RdxPhi];
|
|
|
|
setDebugLocFromInst(Builder, RdxDesc.StartValue);
|
|
|
|
// We need to generate a reduction vector from the incoming scalar.
|
|
// To do so, we need to generate the 'identity' vector and override
|
|
// one of the elements with the incoming scalar reduction. We need
|
|
// to do it in the vector-loop preheader.
|
|
Builder.SetInsertPoint(LoopBypassBlocks[1]->getTerminator());
|
|
|
|
// This is the vector-clone of the value that leaves the loop.
|
|
VectorParts &VectorExit = getVectorValue(RdxDesc.LoopExitInstr);
|
|
Type *VecTy = VectorExit[0]->getType();
|
|
|
|
// Find the reduction identity variable. Zero for addition, or, xor,
|
|
// one for multiplication, -1 for And.
|
|
Value *Identity;
|
|
Value *VectorStart;
|
|
if (RdxDesc.Kind == LoopVectorizationLegality::RK_IntegerMinMax ||
|
|
RdxDesc.Kind == LoopVectorizationLegality::RK_FloatMinMax) {
|
|
// MinMax reduction have the start value as their identify.
|
|
if (VF == 1) {
|
|
VectorStart = Identity = RdxDesc.StartValue;
|
|
} else {
|
|
VectorStart = Identity = Builder.CreateVectorSplat(VF,
|
|
RdxDesc.StartValue,
|
|
"minmax.ident");
|
|
}
|
|
} else {
|
|
// Handle other reduction kinds:
|
|
Constant *Iden =
|
|
LoopVectorizationLegality::getReductionIdentity(RdxDesc.Kind,
|
|
VecTy->getScalarType());
|
|
if (VF == 1) {
|
|
Identity = Iden;
|
|
// This vector is the Identity vector where the first element is the
|
|
// incoming scalar reduction.
|
|
VectorStart = RdxDesc.StartValue;
|
|
} else {
|
|
Identity = ConstantVector::getSplat(VF, Iden);
|
|
|
|
// This vector is the Identity vector where the first element is the
|
|
// incoming scalar reduction.
|
|
VectorStart = Builder.CreateInsertElement(Identity,
|
|
RdxDesc.StartValue, Zero);
|
|
}
|
|
}
|
|
|
|
// Fix the vector-loop phi.
|
|
|
|
// Reductions do not have to start at zero. They can start with
|
|
// any loop invariant values.
|
|
VectorParts &VecRdxPhi = WidenMap.get(RdxPhi);
|
|
BasicBlock *Latch = OrigLoop->getLoopLatch();
|
|
Value *LoopVal = RdxPhi->getIncomingValueForBlock(Latch);
|
|
VectorParts &Val = getVectorValue(LoopVal);
|
|
for (unsigned part = 0; part < UF; ++part) {
|
|
// Make sure to add the reduction stat value only to the
|
|
// first unroll part.
|
|
Value *StartVal = (part == 0) ? VectorStart : Identity;
|
|
cast<PHINode>(VecRdxPhi[part])->addIncoming(StartVal,
|
|
LoopVectorPreHeader);
|
|
cast<PHINode>(VecRdxPhi[part])->addIncoming(Val[part],
|
|
LoopVectorBody.back());
|
|
}
|
|
|
|
// Before each round, move the insertion point right between
|
|
// the PHIs and the values we are going to write.
|
|
// This allows us to write both PHINodes and the extractelement
|
|
// instructions.
|
|
Builder.SetInsertPoint(LoopMiddleBlock->getFirstInsertionPt());
|
|
|
|
VectorParts RdxParts;
|
|
setDebugLocFromInst(Builder, RdxDesc.LoopExitInstr);
|
|
for (unsigned part = 0; part < UF; ++part) {
|
|
// This PHINode contains the vectorized reduction variable, or
|
|
// the initial value vector, if we bypass the vector loop.
|
|
VectorParts &RdxExitVal = getVectorValue(RdxDesc.LoopExitInstr);
|
|
PHINode *NewPhi = Builder.CreatePHI(VecTy, 2, "rdx.vec.exit.phi");
|
|
Value *StartVal = (part == 0) ? VectorStart : Identity;
|
|
for (unsigned I = 1, E = LoopBypassBlocks.size(); I != E; ++I)
|
|
NewPhi->addIncoming(StartVal, LoopBypassBlocks[I]);
|
|
NewPhi->addIncoming(RdxExitVal[part],
|
|
LoopVectorBody.back());
|
|
RdxParts.push_back(NewPhi);
|
|
}
|
|
|
|
// Reduce all of the unrolled parts into a single vector.
|
|
Value *ReducedPartRdx = RdxParts[0];
|
|
unsigned Op = getReductionBinOp(RdxDesc.Kind);
|
|
setDebugLocFromInst(Builder, ReducedPartRdx);
|
|
for (unsigned part = 1; part < UF; ++part) {
|
|
if (Op != Instruction::ICmp && Op != Instruction::FCmp)
|
|
// Floating point operations had to be 'fast' to enable the reduction.
|
|
ReducedPartRdx = addFastMathFlag(
|
|
Builder.CreateBinOp((Instruction::BinaryOps)Op, RdxParts[part],
|
|
ReducedPartRdx, "bin.rdx"));
|
|
else
|
|
ReducedPartRdx = createMinMaxOp(Builder, RdxDesc.MinMaxKind,
|
|
ReducedPartRdx, RdxParts[part]);
|
|
}
|
|
|
|
if (VF > 1) {
|
|
// VF is a power of 2 so we can emit the reduction using log2(VF) shuffles
|
|
// and vector ops, reducing the set of values being computed by half each
|
|
// round.
|
|
assert(isPowerOf2_32(VF) &&
|
|
"Reduction emission only supported for pow2 vectors!");
|
|
Value *TmpVec = ReducedPartRdx;
|
|
SmallVector<Constant*, 32> ShuffleMask(VF, nullptr);
|
|
for (unsigned i = VF; i != 1; i >>= 1) {
|
|
// Move the upper half of the vector to the lower half.
|
|
for (unsigned j = 0; j != i/2; ++j)
|
|
ShuffleMask[j] = Builder.getInt32(i/2 + j);
|
|
|
|
// Fill the rest of the mask with undef.
|
|
std::fill(&ShuffleMask[i/2], ShuffleMask.end(),
|
|
UndefValue::get(Builder.getInt32Ty()));
|
|
|
|
Value *Shuf =
|
|
Builder.CreateShuffleVector(TmpVec,
|
|
UndefValue::get(TmpVec->getType()),
|
|
ConstantVector::get(ShuffleMask),
|
|
"rdx.shuf");
|
|
|
|
if (Op != Instruction::ICmp && Op != Instruction::FCmp)
|
|
// Floating point operations had to be 'fast' to enable the reduction.
|
|
TmpVec = addFastMathFlag(Builder.CreateBinOp(
|
|
(Instruction::BinaryOps)Op, TmpVec, Shuf, "bin.rdx"));
|
|
else
|
|
TmpVec = createMinMaxOp(Builder, RdxDesc.MinMaxKind, TmpVec, Shuf);
|
|
}
|
|
|
|
// The result is in the first element of the vector.
|
|
ReducedPartRdx = Builder.CreateExtractElement(TmpVec,
|
|
Builder.getInt32(0));
|
|
}
|
|
|
|
// Create a phi node that merges control-flow from the backedge-taken check
|
|
// block and the middle block.
|
|
PHINode *BCBlockPhi = PHINode::Create(RdxPhi->getType(), 2, "bc.merge.rdx",
|
|
LoopScalarPreHeader->getTerminator());
|
|
BCBlockPhi->addIncoming(RdxDesc.StartValue, LoopBypassBlocks[0]);
|
|
BCBlockPhi->addIncoming(ReducedPartRdx, LoopMiddleBlock);
|
|
|
|
// Now, we need to fix the users of the reduction variable
|
|
// inside and outside of the scalar remainder loop.
|
|
// We know that the loop is in LCSSA form. We need to update the
|
|
// PHI nodes in the exit blocks.
|
|
for (BasicBlock::iterator LEI = LoopExitBlock->begin(),
|
|
LEE = LoopExitBlock->end(); LEI != LEE; ++LEI) {
|
|
PHINode *LCSSAPhi = dyn_cast<PHINode>(LEI);
|
|
if (!LCSSAPhi) break;
|
|
|
|
// All PHINodes need to have a single entry edge, or two if
|
|
// we already fixed them.
|
|
assert(LCSSAPhi->getNumIncomingValues() < 3 && "Invalid LCSSA PHI");
|
|
|
|
// We found our reduction value exit-PHI. Update it with the
|
|
// incoming bypass edge.
|
|
if (LCSSAPhi->getIncomingValue(0) == RdxDesc.LoopExitInstr) {
|
|
// Add an edge coming from the bypass.
|
|
LCSSAPhi->addIncoming(ReducedPartRdx, LoopMiddleBlock);
|
|
break;
|
|
}
|
|
}// end of the LCSSA phi scan.
|
|
|
|
// Fix the scalar loop reduction variable with the incoming reduction sum
|
|
// from the vector body and from the backedge value.
|
|
int IncomingEdgeBlockIdx =
|
|
(RdxPhi)->getBasicBlockIndex(OrigLoop->getLoopLatch());
|
|
assert(IncomingEdgeBlockIdx >= 0 && "Invalid block index");
|
|
// Pick the other block.
|
|
int SelfEdgeBlockIdx = (IncomingEdgeBlockIdx ? 0 : 1);
|
|
(RdxPhi)->setIncomingValue(SelfEdgeBlockIdx, BCBlockPhi);
|
|
(RdxPhi)->setIncomingValue(IncomingEdgeBlockIdx, RdxDesc.LoopExitInstr);
|
|
}// end of for each redux variable.
|
|
|
|
fixLCSSAPHIs();
|
|
|
|
// Remove redundant induction instructions.
|
|
cse(LoopVectorBody);
|
|
}
|
|
|
|
void InnerLoopVectorizer::fixLCSSAPHIs() {
|
|
for (BasicBlock::iterator LEI = LoopExitBlock->begin(),
|
|
LEE = LoopExitBlock->end(); LEI != LEE; ++LEI) {
|
|
PHINode *LCSSAPhi = dyn_cast<PHINode>(LEI);
|
|
if (!LCSSAPhi) break;
|
|
if (LCSSAPhi->getNumIncomingValues() == 1)
|
|
LCSSAPhi->addIncoming(UndefValue::get(LCSSAPhi->getType()),
|
|
LoopMiddleBlock);
|
|
}
|
|
}
|
|
|
|
InnerLoopVectorizer::VectorParts
|
|
InnerLoopVectorizer::createEdgeMask(BasicBlock *Src, BasicBlock *Dst) {
|
|
assert(std::find(pred_begin(Dst), pred_end(Dst), Src) != pred_end(Dst) &&
|
|
"Invalid edge");
|
|
|
|
// Look for cached value.
|
|
std::pair<BasicBlock*, BasicBlock*> Edge(Src, Dst);
|
|
EdgeMaskCache::iterator ECEntryIt = MaskCache.find(Edge);
|
|
if (ECEntryIt != MaskCache.end())
|
|
return ECEntryIt->second;
|
|
|
|
VectorParts SrcMask = createBlockInMask(Src);
|
|
|
|
// The terminator has to be a branch inst!
|
|
BranchInst *BI = dyn_cast<BranchInst>(Src->getTerminator());
|
|
assert(BI && "Unexpected terminator found");
|
|
|
|
if (BI->isConditional()) {
|
|
VectorParts EdgeMask = getVectorValue(BI->getCondition());
|
|
|
|
if (BI->getSuccessor(0) != Dst)
|
|
for (unsigned part = 0; part < UF; ++part)
|
|
EdgeMask[part] = Builder.CreateNot(EdgeMask[part]);
|
|
|
|
for (unsigned part = 0; part < UF; ++part)
|
|
EdgeMask[part] = Builder.CreateAnd(EdgeMask[part], SrcMask[part]);
|
|
|
|
MaskCache[Edge] = EdgeMask;
|
|
return EdgeMask;
|
|
}
|
|
|
|
MaskCache[Edge] = SrcMask;
|
|
return SrcMask;
|
|
}
|
|
|
|
InnerLoopVectorizer::VectorParts
|
|
InnerLoopVectorizer::createBlockInMask(BasicBlock *BB) {
|
|
assert(OrigLoop->contains(BB) && "Block is not a part of a loop");
|
|
|
|
// Loop incoming mask is all-one.
|
|
if (OrigLoop->getHeader() == BB) {
|
|
Value *C = ConstantInt::get(IntegerType::getInt1Ty(BB->getContext()), 1);
|
|
return getVectorValue(C);
|
|
}
|
|
|
|
// This is the block mask. We OR all incoming edges, and with zero.
|
|
Value *Zero = ConstantInt::get(IntegerType::getInt1Ty(BB->getContext()), 0);
|
|
VectorParts BlockMask = getVectorValue(Zero);
|
|
|
|
// For each pred:
|
|
for (pred_iterator it = pred_begin(BB), e = pred_end(BB); it != e; ++it) {
|
|
VectorParts EM = createEdgeMask(*it, BB);
|
|
for (unsigned part = 0; part < UF; ++part)
|
|
BlockMask[part] = Builder.CreateOr(BlockMask[part], EM[part]);
|
|
}
|
|
|
|
return BlockMask;
|
|
}
|
|
|
|
void InnerLoopVectorizer::widenPHIInstruction(Instruction *PN,
|
|
InnerLoopVectorizer::VectorParts &Entry,
|
|
unsigned UF, unsigned VF, PhiVector *PV) {
|
|
PHINode* P = cast<PHINode>(PN);
|
|
// Handle reduction variables:
|
|
if (Legal->getReductionVars()->count(P)) {
|
|
for (unsigned part = 0; part < UF; ++part) {
|
|
// This is phase one of vectorizing PHIs.
|
|
Type *VecTy = (VF == 1) ? PN->getType() :
|
|
VectorType::get(PN->getType(), VF);
|
|
Entry[part] = PHINode::Create(VecTy, 2, "vec.phi",
|
|
LoopVectorBody.back()-> getFirstInsertionPt());
|
|
}
|
|
PV->push_back(P);
|
|
return;
|
|
}
|
|
|
|
setDebugLocFromInst(Builder, P);
|
|
// Check for PHI nodes that are lowered to vector selects.
|
|
if (P->getParent() != OrigLoop->getHeader()) {
|
|
// We know that all PHIs in non-header blocks are converted into
|
|
// selects, so we don't have to worry about the insertion order and we
|
|
// can just use the builder.
|
|
// At this point we generate the predication tree. There may be
|
|
// duplications since this is a simple recursive scan, but future
|
|
// optimizations will clean it up.
|
|
|
|
unsigned NumIncoming = P->getNumIncomingValues();
|
|
|
|
// Generate a sequence of selects of the form:
|
|
// SELECT(Mask3, In3,
|
|
// SELECT(Mask2, In2,
|
|
// ( ...)))
|
|
for (unsigned In = 0; In < NumIncoming; In++) {
|
|
VectorParts Cond = createEdgeMask(P->getIncomingBlock(In),
|
|
P->getParent());
|
|
VectorParts &In0 = getVectorValue(P->getIncomingValue(In));
|
|
|
|
for (unsigned part = 0; part < UF; ++part) {
|
|
// We might have single edge PHIs (blocks) - use an identity
|
|
// 'select' for the first PHI operand.
|
|
if (In == 0)
|
|
Entry[part] = Builder.CreateSelect(Cond[part], In0[part],
|
|
In0[part]);
|
|
else
|
|
// Select between the current value and the previous incoming edge
|
|
// based on the incoming mask.
|
|
Entry[part] = Builder.CreateSelect(Cond[part], In0[part],
|
|
Entry[part], "predphi");
|
|
}
|
|
}
|
|
return;
|
|
}
|
|
|
|
// This PHINode must be an induction variable.
|
|
// Make sure that we know about it.
|
|
assert(Legal->getInductionVars()->count(P) &&
|
|
"Not an induction variable");
|
|
|
|
LoopVectorizationLegality::InductionInfo II =
|
|
Legal->getInductionVars()->lookup(P);
|
|
|
|
// FIXME: The newly created binary instructions should contain nsw/nuw flags,
|
|
// which can be found from the original scalar operations.
|
|
switch (II.IK) {
|
|
case LoopVectorizationLegality::IK_NoInduction:
|
|
llvm_unreachable("Unknown induction");
|
|
case LoopVectorizationLegality::IK_IntInduction: {
|
|
assert(P->getType() == II.StartValue->getType() && "Types must match");
|
|
Type *PhiTy = P->getType();
|
|
Value *Broadcasted;
|
|
if (P == OldInduction) {
|
|
// Handle the canonical induction variable. We might have had to
|
|
// extend the type.
|
|
Broadcasted = Builder.CreateTrunc(Induction, PhiTy);
|
|
} else {
|
|
// Handle other induction variables that are now based on the
|
|
// canonical one.
|
|
Value *NormalizedIdx = Builder.CreateSub(Induction, ExtendedIdx,
|
|
"normalized.idx");
|
|
NormalizedIdx = Builder.CreateSExtOrTrunc(NormalizedIdx, PhiTy);
|
|
Broadcasted = II.transform(Builder, NormalizedIdx);
|
|
Broadcasted->setName("offset.idx");
|
|
}
|
|
Broadcasted = getBroadcastInstrs(Broadcasted);
|
|
// After broadcasting the induction variable we need to make the vector
|
|
// consecutive by adding 0, 1, 2, etc.
|
|
for (unsigned part = 0; part < UF; ++part)
|
|
Entry[part] = getStepVector(Broadcasted, VF * part, II.StepValue);
|
|
return;
|
|
}
|
|
case LoopVectorizationLegality::IK_PtrInduction:
|
|
// Handle the pointer induction variable case.
|
|
assert(P->getType()->isPointerTy() && "Unexpected type.");
|
|
// This is the normalized GEP that starts counting at zero.
|
|
Value *NormalizedIdx =
|
|
Builder.CreateSub(Induction, ExtendedIdx, "normalized.idx");
|
|
// This is the vector of results. Notice that we don't generate
|
|
// vector geps because scalar geps result in better code.
|
|
for (unsigned part = 0; part < UF; ++part) {
|
|
if (VF == 1) {
|
|
int EltIndex = part;
|
|
Constant *Idx = ConstantInt::get(Induction->getType(), EltIndex);
|
|
Value *GlobalIdx = Builder.CreateAdd(NormalizedIdx, Idx);
|
|
Value *SclrGep = II.transform(Builder, GlobalIdx);
|
|
SclrGep->setName("next.gep");
|
|
Entry[part] = SclrGep;
|
|
continue;
|
|
}
|
|
|
|
Value *VecVal = UndefValue::get(VectorType::get(P->getType(), VF));
|
|
for (unsigned int i = 0; i < VF; ++i) {
|
|
int EltIndex = i + part * VF;
|
|
Constant *Idx = ConstantInt::get(Induction->getType(), EltIndex);
|
|
Value *GlobalIdx = Builder.CreateAdd(NormalizedIdx, Idx);
|
|
Value *SclrGep = II.transform(Builder, GlobalIdx);
|
|
SclrGep->setName("next.gep");
|
|
VecVal = Builder.CreateInsertElement(VecVal, SclrGep,
|
|
Builder.getInt32(i),
|
|
"insert.gep");
|
|
}
|
|
Entry[part] = VecVal;
|
|
}
|
|
return;
|
|
}
|
|
}
|
|
|
|
void InnerLoopVectorizer::vectorizeBlockInLoop(BasicBlock *BB, PhiVector *PV) {
|
|
// For each instruction in the old loop.
|
|
for (BasicBlock::iterator it = BB->begin(), e = BB->end(); it != e; ++it) {
|
|
VectorParts &Entry = WidenMap.get(it);
|
|
switch (it->getOpcode()) {
|
|
case Instruction::Br:
|
|
// Nothing to do for PHIs and BR, since we already took care of the
|
|
// loop control flow instructions.
|
|
continue;
|
|
case Instruction::PHI: {
|
|
// Vectorize PHINodes.
|
|
widenPHIInstruction(it, Entry, UF, VF, PV);
|
|
continue;
|
|
}// End of PHI.
|
|
|
|
case Instruction::Add:
|
|
case Instruction::FAdd:
|
|
case Instruction::Sub:
|
|
case Instruction::FSub:
|
|
case Instruction::Mul:
|
|
case Instruction::FMul:
|
|
case Instruction::UDiv:
|
|
case Instruction::SDiv:
|
|
case Instruction::FDiv:
|
|
case Instruction::URem:
|
|
case Instruction::SRem:
|
|
case Instruction::FRem:
|
|
case Instruction::Shl:
|
|
case Instruction::LShr:
|
|
case Instruction::AShr:
|
|
case Instruction::And:
|
|
case Instruction::Or:
|
|
case Instruction::Xor: {
|
|
// Just widen binops.
|
|
BinaryOperator *BinOp = dyn_cast<BinaryOperator>(it);
|
|
setDebugLocFromInst(Builder, BinOp);
|
|
VectorParts &A = getVectorValue(it->getOperand(0));
|
|
VectorParts &B = getVectorValue(it->getOperand(1));
|
|
|
|
// Use this vector value for all users of the original instruction.
|
|
for (unsigned Part = 0; Part < UF; ++Part) {
|
|
Value *V = Builder.CreateBinOp(BinOp->getOpcode(), A[Part], B[Part]);
|
|
|
|
if (BinaryOperator *VecOp = dyn_cast<BinaryOperator>(V))
|
|
VecOp->copyIRFlags(BinOp);
|
|
|
|
Entry[Part] = V;
|
|
}
|
|
|
|
propagateMetadata(Entry, it);
|
|
break;
|
|
}
|
|
case Instruction::Select: {
|
|
// Widen selects.
|
|
// If the selector is loop invariant we can create a select
|
|
// instruction with a scalar condition. Otherwise, use vector-select.
|
|
bool InvariantCond = SE->isLoopInvariant(SE->getSCEV(it->getOperand(0)),
|
|
OrigLoop);
|
|
setDebugLocFromInst(Builder, it);
|
|
|
|
// The condition can be loop invariant but still defined inside the
|
|
// loop. This means that we can't just use the original 'cond' value.
|
|
// We have to take the 'vectorized' value and pick the first lane.
|
|
// Instcombine will make this a no-op.
|
|
VectorParts &Cond = getVectorValue(it->getOperand(0));
|
|
VectorParts &Op0 = getVectorValue(it->getOperand(1));
|
|
VectorParts &Op1 = getVectorValue(it->getOperand(2));
|
|
|
|
Value *ScalarCond = (VF == 1) ? Cond[0] :
|
|
Builder.CreateExtractElement(Cond[0], Builder.getInt32(0));
|
|
|
|
for (unsigned Part = 0; Part < UF; ++Part) {
|
|
Entry[Part] = Builder.CreateSelect(
|
|
InvariantCond ? ScalarCond : Cond[Part],
|
|
Op0[Part],
|
|
Op1[Part]);
|
|
}
|
|
|
|
propagateMetadata(Entry, it);
|
|
break;
|
|
}
|
|
|
|
case Instruction::ICmp:
|
|
case Instruction::FCmp: {
|
|
// Widen compares. Generate vector compares.
|
|
bool FCmp = (it->getOpcode() == Instruction::FCmp);
|
|
CmpInst *Cmp = dyn_cast<CmpInst>(it);
|
|
setDebugLocFromInst(Builder, it);
|
|
VectorParts &A = getVectorValue(it->getOperand(0));
|
|
VectorParts &B = getVectorValue(it->getOperand(1));
|
|
for (unsigned Part = 0; Part < UF; ++Part) {
|
|
Value *C = nullptr;
|
|
if (FCmp)
|
|
C = Builder.CreateFCmp(Cmp->getPredicate(), A[Part], B[Part]);
|
|
else
|
|
C = Builder.CreateICmp(Cmp->getPredicate(), A[Part], B[Part]);
|
|
Entry[Part] = C;
|
|
}
|
|
|
|
propagateMetadata(Entry, it);
|
|
break;
|
|
}
|
|
|
|
case Instruction::Store:
|
|
case Instruction::Load:
|
|
vectorizeMemoryInstruction(it);
|
|
break;
|
|
case Instruction::ZExt:
|
|
case Instruction::SExt:
|
|
case Instruction::FPToUI:
|
|
case Instruction::FPToSI:
|
|
case Instruction::FPExt:
|
|
case Instruction::PtrToInt:
|
|
case Instruction::IntToPtr:
|
|
case Instruction::SIToFP:
|
|
case Instruction::UIToFP:
|
|
case Instruction::Trunc:
|
|
case Instruction::FPTrunc:
|
|
case Instruction::BitCast: {
|
|
CastInst *CI = dyn_cast<CastInst>(it);
|
|
setDebugLocFromInst(Builder, it);
|
|
/// Optimize the special case where the source is the induction
|
|
/// variable. Notice that we can only optimize the 'trunc' case
|
|
/// because: a. FP conversions lose precision, b. sext/zext may wrap,
|
|
/// c. other casts depend on pointer size.
|
|
if (CI->getOperand(0) == OldInduction &&
|
|
it->getOpcode() == Instruction::Trunc) {
|
|
Value *ScalarCast = Builder.CreateCast(CI->getOpcode(), Induction,
|
|
CI->getType());
|
|
Value *Broadcasted = getBroadcastInstrs(ScalarCast);
|
|
LoopVectorizationLegality::InductionInfo II =
|
|
Legal->getInductionVars()->lookup(OldInduction);
|
|
Constant *Step =
|
|
ConstantInt::getSigned(CI->getType(), II.StepValue->getSExtValue());
|
|
for (unsigned Part = 0; Part < UF; ++Part)
|
|
Entry[Part] = getStepVector(Broadcasted, VF * Part, Step);
|
|
propagateMetadata(Entry, it);
|
|
break;
|
|
}
|
|
/// Vectorize casts.
|
|
Type *DestTy = (VF == 1) ? CI->getType() :
|
|
VectorType::get(CI->getType(), VF);
|
|
|
|
VectorParts &A = getVectorValue(it->getOperand(0));
|
|
for (unsigned Part = 0; Part < UF; ++Part)
|
|
Entry[Part] = Builder.CreateCast(CI->getOpcode(), A[Part], DestTy);
|
|
propagateMetadata(Entry, it);
|
|
break;
|
|
}
|
|
|
|
case Instruction::Call: {
|
|
// Ignore dbg intrinsics.
|
|
if (isa<DbgInfoIntrinsic>(it))
|
|
break;
|
|
setDebugLocFromInst(Builder, it);
|
|
|
|
Module *M = BB->getParent()->getParent();
|
|
CallInst *CI = cast<CallInst>(it);
|
|
Intrinsic::ID ID = getIntrinsicIDForCall(CI, TLI);
|
|
assert(ID && "Not an intrinsic call!");
|
|
switch (ID) {
|
|
case Intrinsic::assume:
|
|
case Intrinsic::lifetime_end:
|
|
case Intrinsic::lifetime_start:
|
|
scalarizeInstruction(it);
|
|
break;
|
|
default:
|
|
bool HasScalarOpd = hasVectorInstrinsicScalarOpd(ID, 1);
|
|
for (unsigned Part = 0; Part < UF; ++Part) {
|
|
SmallVector<Value *, 4> Args;
|
|
for (unsigned i = 0, ie = CI->getNumArgOperands(); i != ie; ++i) {
|
|
if (HasScalarOpd && i == 1) {
|
|
Args.push_back(CI->getArgOperand(i));
|
|
continue;
|
|
}
|
|
VectorParts &Arg = getVectorValue(CI->getArgOperand(i));
|
|
Args.push_back(Arg[Part]);
|
|
}
|
|
Type *Tys[] = {CI->getType()};
|
|
if (VF > 1)
|
|
Tys[0] = VectorType::get(CI->getType()->getScalarType(), VF);
|
|
|
|
Function *F = Intrinsic::getDeclaration(M, ID, Tys);
|
|
Entry[Part] = Builder.CreateCall(F, Args);
|
|
}
|
|
|
|
propagateMetadata(Entry, it);
|
|
break;
|
|
}
|
|
break;
|
|
}
|
|
|
|
default:
|
|
// All other instructions are unsupported. Scalarize them.
|
|
scalarizeInstruction(it);
|
|
break;
|
|
}// end of switch.
|
|
}// end of for_each instr.
|
|
}
|
|
|
|
void InnerLoopVectorizer::updateAnalysis() {
|
|
// Forget the original basic block.
|
|
SE->forgetLoop(OrigLoop);
|
|
|
|
// Update the dominator tree information.
|
|
assert(DT->properlyDominates(LoopBypassBlocks.front(), LoopExitBlock) &&
|
|
"Entry does not dominate exit.");
|
|
|
|
for (unsigned I = 1, E = LoopBypassBlocks.size(); I != E; ++I)
|
|
DT->addNewBlock(LoopBypassBlocks[I], LoopBypassBlocks[I-1]);
|
|
DT->addNewBlock(LoopVectorPreHeader, LoopBypassBlocks.back());
|
|
|
|
// Due to if predication of stores we might create a sequence of "if(pred)
|
|
// a[i] = ...; " blocks.
|
|
for (unsigned i = 0, e = LoopVectorBody.size(); i != e; ++i) {
|
|
if (i == 0)
|
|
DT->addNewBlock(LoopVectorBody[0], LoopVectorPreHeader);
|
|
else if (isPredicatedBlock(i)) {
|
|
DT->addNewBlock(LoopVectorBody[i], LoopVectorBody[i-1]);
|
|
} else {
|
|
DT->addNewBlock(LoopVectorBody[i], LoopVectorBody[i-2]);
|
|
}
|
|
}
|
|
|
|
DT->addNewBlock(LoopMiddleBlock, LoopBypassBlocks[1]);
|
|
DT->addNewBlock(LoopScalarPreHeader, LoopBypassBlocks[0]);
|
|
DT->changeImmediateDominator(LoopScalarBody, LoopScalarPreHeader);
|
|
DT->changeImmediateDominator(LoopExitBlock, LoopBypassBlocks[0]);
|
|
|
|
DEBUG(DT->verifyDomTree());
|
|
}
|
|
|
|
/// \brief Check whether it is safe to if-convert this phi node.
|
|
///
|
|
/// Phi nodes with constant expressions that can trap are not safe to if
|
|
/// convert.
|
|
static bool canIfConvertPHINodes(BasicBlock *BB) {
|
|
for (BasicBlock::iterator I = BB->begin(), E = BB->end(); I != E; ++I) {
|
|
PHINode *Phi = dyn_cast<PHINode>(I);
|
|
if (!Phi)
|
|
return true;
|
|
for (unsigned p = 0, e = Phi->getNumIncomingValues(); p != e; ++p)
|
|
if (Constant *C = dyn_cast<Constant>(Phi->getIncomingValue(p)))
|
|
if (C->canTrap())
|
|
return false;
|
|
}
|
|
return true;
|
|
}
|
|
|
|
bool LoopVectorizationLegality::canVectorizeWithIfConvert() {
|
|
if (!EnableIfConversion) {
|
|
emitAnalysis(VectorizationReport() << "if-conversion is disabled");
|
|
return false;
|
|
}
|
|
|
|
assert(TheLoop->getNumBlocks() > 1 && "Single block loops are vectorizable");
|
|
|
|
// A list of pointers that we can safely read and write to.
|
|
SmallPtrSet<Value *, 8> SafePointes;
|
|
|
|
// Collect safe addresses.
|
|
for (Loop::block_iterator BI = TheLoop->block_begin(),
|
|
BE = TheLoop->block_end(); BI != BE; ++BI) {
|
|
BasicBlock *BB = *BI;
|
|
|
|
if (blockNeedsPredication(BB))
|
|
continue;
|
|
|
|
for (BasicBlock::iterator I = BB->begin(), E = BB->end(); I != E; ++I) {
|
|
if (LoadInst *LI = dyn_cast<LoadInst>(I))
|
|
SafePointes.insert(LI->getPointerOperand());
|
|
else if (StoreInst *SI = dyn_cast<StoreInst>(I))
|
|
SafePointes.insert(SI->getPointerOperand());
|
|
}
|
|
}
|
|
|
|
// Collect the blocks that need predication.
|
|
BasicBlock *Header = TheLoop->getHeader();
|
|
for (Loop::block_iterator BI = TheLoop->block_begin(),
|
|
BE = TheLoop->block_end(); BI != BE; ++BI) {
|
|
BasicBlock *BB = *BI;
|
|
|
|
// We don't support switch statements inside loops.
|
|
if (!isa<BranchInst>(BB->getTerminator())) {
|
|
emitAnalysis(VectorizationReport(BB->getTerminator())
|
|
<< "loop contains a switch statement");
|
|
return false;
|
|
}
|
|
|
|
// We must be able to predicate all blocks that need to be predicated.
|
|
if (blockNeedsPredication(BB)) {
|
|
if (!blockCanBePredicated(BB, SafePointes)) {
|
|
emitAnalysis(VectorizationReport(BB->getTerminator())
|
|
<< "control flow cannot be substituted for a select");
|
|
return false;
|
|
}
|
|
} else if (BB != Header && !canIfConvertPHINodes(BB)) {
|
|
emitAnalysis(VectorizationReport(BB->getTerminator())
|
|
<< "control flow cannot be substituted for a select");
|
|
return false;
|
|
}
|
|
}
|
|
|
|
// We can if-convert this loop.
|
|
return true;
|
|
}
|
|
|
|
bool LoopVectorizationLegality::canVectorize() {
|
|
// We must have a loop in canonical form. Loops with indirectbr in them cannot
|
|
// be canonicalized.
|
|
if (!TheLoop->getLoopPreheader()) {
|
|
emitAnalysis(
|
|
VectorizationReport() <<
|
|
"loop control flow is not understood by vectorizer");
|
|
return false;
|
|
}
|
|
|
|
// We can only vectorize innermost loops.
|
|
if (!TheLoop->getSubLoopsVector().empty()) {
|
|
emitAnalysis(VectorizationReport() << "loop is not the innermost loop");
|
|
return false;
|
|
}
|
|
|
|
// We must have a single backedge.
|
|
if (TheLoop->getNumBackEdges() != 1) {
|
|
emitAnalysis(
|
|
VectorizationReport() <<
|
|
"loop control flow is not understood by vectorizer");
|
|
return false;
|
|
}
|
|
|
|
// We must have a single exiting block.
|
|
if (!TheLoop->getExitingBlock()) {
|
|
emitAnalysis(
|
|
VectorizationReport() <<
|
|
"loop control flow is not understood by vectorizer");
|
|
return false;
|
|
}
|
|
|
|
// We only handle bottom-tested loops, i.e. loop in which the condition is
|
|
// checked at the end of each iteration. With that we can assume that all
|
|
// instructions in the loop are executed the same number of times.
|
|
if (TheLoop->getExitingBlock() != TheLoop->getLoopLatch()) {
|
|
emitAnalysis(
|
|
VectorizationReport() <<
|
|
"loop control flow is not understood by vectorizer");
|
|
return false;
|
|
}
|
|
|
|
// We need to have a loop header.
|
|
DEBUG(dbgs() << "LV: Found a loop: " <<
|
|
TheLoop->getHeader()->getName() << '\n');
|
|
|
|
// Check if we can if-convert non-single-bb loops.
|
|
unsigned NumBlocks = TheLoop->getNumBlocks();
|
|
if (NumBlocks != 1 && !canVectorizeWithIfConvert()) {
|
|
DEBUG(dbgs() << "LV: Can't if-convert the loop.\n");
|
|
return false;
|
|
}
|
|
|
|
// ScalarEvolution needs to be able to find the exit count.
|
|
const SCEV *ExitCount = SE->getBackedgeTakenCount(TheLoop);
|
|
if (ExitCount == SE->getCouldNotCompute()) {
|
|
emitAnalysis(VectorizationReport() <<
|
|
"could not determine number of loop iterations");
|
|
DEBUG(dbgs() << "LV: SCEV could not compute the loop exit count.\n");
|
|
return false;
|
|
}
|
|
|
|
// Check if we can vectorize the instructions and CFG in this loop.
|
|
if (!canVectorizeInstrs()) {
|
|
DEBUG(dbgs() << "LV: Can't vectorize the instructions or CFG\n");
|
|
return false;
|
|
}
|
|
|
|
// Go over each instruction and look at memory deps.
|
|
if (!canVectorizeMemory()) {
|
|
DEBUG(dbgs() << "LV: Can't vectorize due to memory conflicts\n");
|
|
return false;
|
|
}
|
|
|
|
// Collect all of the variables that remain uniform after vectorization.
|
|
collectLoopUniforms();
|
|
|
|
DEBUG(dbgs() << "LV: We can vectorize this loop"
|
|
<< (LAI.getRuntimePointerCheck()->Need
|
|
? " (with a runtime bound check)"
|
|
: "") << "!\n");
|
|
|
|
// Okay! We can vectorize. At this point we don't have any other mem analysis
|
|
// which may limit our maximum vectorization factor, so just return true with
|
|
// no restrictions.
|
|
return true;
|
|
}
|
|
|
|
static Type *convertPointerToIntegerType(const DataLayout &DL, Type *Ty) {
|
|
if (Ty->isPointerTy())
|
|
return DL.getIntPtrType(Ty);
|
|
|
|
// It is possible that char's or short's overflow when we ask for the loop's
|
|
// trip count, work around this by changing the type size.
|
|
if (Ty->getScalarSizeInBits() < 32)
|
|
return Type::getInt32Ty(Ty->getContext());
|
|
|
|
return Ty;
|
|
}
|
|
|
|
static Type* getWiderType(const DataLayout &DL, Type *Ty0, Type *Ty1) {
|
|
Ty0 = convertPointerToIntegerType(DL, Ty0);
|
|
Ty1 = convertPointerToIntegerType(DL, Ty1);
|
|
if (Ty0->getScalarSizeInBits() > Ty1->getScalarSizeInBits())
|
|
return Ty0;
|
|
return Ty1;
|
|
}
|
|
|
|
/// \brief Check that the instruction has outside loop users and is not an
|
|
/// identified reduction variable.
|
|
static bool hasOutsideLoopUser(const Loop *TheLoop, Instruction *Inst,
|
|
SmallPtrSetImpl<Value *> &Reductions) {
|
|
// Reduction instructions are allowed to have exit users. All other
|
|
// instructions must not have external users.
|
|
if (!Reductions.count(Inst))
|
|
//Check that all of the users of the loop are inside the BB.
|
|
for (User *U : Inst->users()) {
|
|
Instruction *UI = cast<Instruction>(U);
|
|
// This user may be a reduction exit value.
|
|
if (!TheLoop->contains(UI)) {
|
|
DEBUG(dbgs() << "LV: Found an outside user for : " << *UI << '\n');
|
|
return true;
|
|
}
|
|
}
|
|
return false;
|
|
}
|
|
|
|
bool LoopVectorizationLegality::canVectorizeInstrs() {
|
|
BasicBlock *PreHeader = TheLoop->getLoopPreheader();
|
|
BasicBlock *Header = TheLoop->getHeader();
|
|
|
|
// Look for the attribute signaling the absence of NaNs.
|
|
Function &F = *Header->getParent();
|
|
if (F.hasFnAttribute("no-nans-fp-math"))
|
|
HasFunNoNaNAttr =
|
|
F.getFnAttribute("no-nans-fp-math").getValueAsString() == "true";
|
|
|
|
// For each block in the loop.
|
|
for (Loop::block_iterator bb = TheLoop->block_begin(),
|
|
be = TheLoop->block_end(); bb != be; ++bb) {
|
|
|
|
// Scan the instructions in the block and look for hazards.
|
|
for (BasicBlock::iterator it = (*bb)->begin(), e = (*bb)->end(); it != e;
|
|
++it) {
|
|
|
|
if (PHINode *Phi = dyn_cast<PHINode>(it)) {
|
|
Type *PhiTy = Phi->getType();
|
|
// Check that this PHI type is allowed.
|
|
if (!PhiTy->isIntegerTy() &&
|
|
!PhiTy->isFloatingPointTy() &&
|
|
!PhiTy->isPointerTy()) {
|
|
emitAnalysis(VectorizationReport(it)
|
|
<< "loop control flow is not understood by vectorizer");
|
|
DEBUG(dbgs() << "LV: Found an non-int non-pointer PHI.\n");
|
|
return false;
|
|
}
|
|
|
|
// If this PHINode is not in the header block, then we know that we
|
|
// can convert it to select during if-conversion. No need to check if
|
|
// the PHIs in this block are induction or reduction variables.
|
|
if (*bb != Header) {
|
|
// Check that this instruction has no outside users or is an
|
|
// identified reduction value with an outside user.
|
|
if (!hasOutsideLoopUser(TheLoop, it, AllowedExit))
|
|
continue;
|
|
emitAnalysis(VectorizationReport(it) <<
|
|
"value could not be identified as "
|
|
"an induction or reduction variable");
|
|
return false;
|
|
}
|
|
|
|
// We only allow if-converted PHIs with exactly two incoming values.
|
|
if (Phi->getNumIncomingValues() != 2) {
|
|
emitAnalysis(VectorizationReport(it)
|
|
<< "control flow not understood by vectorizer");
|
|
DEBUG(dbgs() << "LV: Found an invalid PHI.\n");
|
|
return false;
|
|
}
|
|
|
|
// This is the value coming from the preheader.
|
|
Value *StartValue = Phi->getIncomingValueForBlock(PreHeader);
|
|
ConstantInt *StepValue = nullptr;
|
|
// Check if this is an induction variable.
|
|
InductionKind IK = isInductionVariable(Phi, StepValue);
|
|
|
|
if (IK_NoInduction != IK) {
|
|
// Get the widest type.
|
|
if (!WidestIndTy)
|
|
WidestIndTy = convertPointerToIntegerType(*DL, PhiTy);
|
|
else
|
|
WidestIndTy = getWiderType(*DL, PhiTy, WidestIndTy);
|
|
|
|
// Int inductions are special because we only allow one IV.
|
|
if (IK == IK_IntInduction && StepValue->isOne()) {
|
|
// Use the phi node with the widest type as induction. Use the last
|
|
// one if there are multiple (no good reason for doing this other
|
|
// than it is expedient).
|
|
if (!Induction || PhiTy == WidestIndTy)
|
|
Induction = Phi;
|
|
}
|
|
|
|
DEBUG(dbgs() << "LV: Found an induction variable.\n");
|
|
Inductions[Phi] = InductionInfo(StartValue, IK, StepValue);
|
|
|
|
// Until we explicitly handle the case of an induction variable with
|
|
// an outside loop user we have to give up vectorizing this loop.
|
|
if (hasOutsideLoopUser(TheLoop, it, AllowedExit)) {
|
|
emitAnalysis(VectorizationReport(it) <<
|
|
"use of induction value outside of the "
|
|
"loop is not handled by vectorizer");
|
|
return false;
|
|
}
|
|
|
|
continue;
|
|
}
|
|
|
|
if (AddReductionVar(Phi, RK_IntegerAdd)) {
|
|
DEBUG(dbgs() << "LV: Found an ADD reduction PHI."<< *Phi <<"\n");
|
|
continue;
|
|
}
|
|
if (AddReductionVar(Phi, RK_IntegerMult)) {
|
|
DEBUG(dbgs() << "LV: Found a MUL reduction PHI."<< *Phi <<"\n");
|
|
continue;
|
|
}
|
|
if (AddReductionVar(Phi, RK_IntegerOr)) {
|
|
DEBUG(dbgs() << "LV: Found an OR reduction PHI."<< *Phi <<"\n");
|
|
continue;
|
|
}
|
|
if (AddReductionVar(Phi, RK_IntegerAnd)) {
|
|
DEBUG(dbgs() << "LV: Found an AND reduction PHI."<< *Phi <<"\n");
|
|
continue;
|
|
}
|
|
if (AddReductionVar(Phi, RK_IntegerXor)) {
|
|
DEBUG(dbgs() << "LV: Found a XOR reduction PHI."<< *Phi <<"\n");
|
|
continue;
|
|
}
|
|
if (AddReductionVar(Phi, RK_IntegerMinMax)) {
|
|
DEBUG(dbgs() << "LV: Found a MINMAX reduction PHI."<< *Phi <<"\n");
|
|
continue;
|
|
}
|
|
if (AddReductionVar(Phi, RK_FloatMult)) {
|
|
DEBUG(dbgs() << "LV: Found an FMult reduction PHI."<< *Phi <<"\n");
|
|
continue;
|
|
}
|
|
if (AddReductionVar(Phi, RK_FloatAdd)) {
|
|
DEBUG(dbgs() << "LV: Found an FAdd reduction PHI."<< *Phi <<"\n");
|
|
continue;
|
|
}
|
|
if (AddReductionVar(Phi, RK_FloatMinMax)) {
|
|
DEBUG(dbgs() << "LV: Found an float MINMAX reduction PHI."<< *Phi <<
|
|
"\n");
|
|
continue;
|
|
}
|
|
|
|
emitAnalysis(VectorizationReport(it) <<
|
|
"value that could not be identified as "
|
|
"reduction is used outside the loop");
|
|
DEBUG(dbgs() << "LV: Found an unidentified PHI."<< *Phi <<"\n");
|
|
return false;
|
|
}// end of PHI handling
|
|
|
|
// We still don't handle functions. However, we can ignore dbg intrinsic
|
|
// calls and we do handle certain intrinsic and libm functions.
|
|
CallInst *CI = dyn_cast<CallInst>(it);
|
|
if (CI && !getIntrinsicIDForCall(CI, TLI) && !isa<DbgInfoIntrinsic>(CI)) {
|
|
emitAnalysis(VectorizationReport(it) <<
|
|
"call instruction cannot be vectorized");
|
|
DEBUG(dbgs() << "LV: Found a call site.\n");
|
|
return false;
|
|
}
|
|
|
|
// Intrinsics such as powi,cttz and ctlz are legal to vectorize if the
|
|
// second argument is the same (i.e. loop invariant)
|
|
if (CI &&
|
|
hasVectorInstrinsicScalarOpd(getIntrinsicIDForCall(CI, TLI), 1)) {
|
|
if (!SE->isLoopInvariant(SE->getSCEV(CI->getOperand(1)), TheLoop)) {
|
|
emitAnalysis(VectorizationReport(it)
|
|
<< "intrinsic instruction cannot be vectorized");
|
|
DEBUG(dbgs() << "LV: Found unvectorizable intrinsic " << *CI << "\n");
|
|
return false;
|
|
}
|
|
}
|
|
|
|
// Check that the instruction return type is vectorizable.
|
|
// Also, we can't vectorize extractelement instructions.
|
|
if ((!VectorType::isValidElementType(it->getType()) &&
|
|
!it->getType()->isVoidTy()) || isa<ExtractElementInst>(it)) {
|
|
emitAnalysis(VectorizationReport(it)
|
|
<< "instruction return type cannot be vectorized");
|
|
DEBUG(dbgs() << "LV: Found unvectorizable type.\n");
|
|
return false;
|
|
}
|
|
|
|
// Check that the stored type is vectorizable.
|
|
if (StoreInst *ST = dyn_cast<StoreInst>(it)) {
|
|
Type *T = ST->getValueOperand()->getType();
|
|
if (!VectorType::isValidElementType(T)) {
|
|
emitAnalysis(VectorizationReport(ST) <<
|
|
"store instruction cannot be vectorized");
|
|
return false;
|
|
}
|
|
if (EnableMemAccessVersioning)
|
|
collectStridedAccess(ST);
|
|
}
|
|
|
|
if (EnableMemAccessVersioning)
|
|
if (LoadInst *LI = dyn_cast<LoadInst>(it))
|
|
collectStridedAccess(LI);
|
|
|
|
// Reduction instructions are allowed to have exit users.
|
|
// All other instructions must not have external users.
|
|
if (hasOutsideLoopUser(TheLoop, it, AllowedExit)) {
|
|
emitAnalysis(VectorizationReport(it) <<
|
|
"value cannot be used outside the loop");
|
|
return false;
|
|
}
|
|
|
|
} // next instr.
|
|
|
|
}
|
|
|
|
if (!Induction) {
|
|
DEBUG(dbgs() << "LV: Did not find one integer induction var.\n");
|
|
if (Inductions.empty()) {
|
|
emitAnalysis(VectorizationReport()
|
|
<< "loop induction variable could not be identified");
|
|
return false;
|
|
}
|
|
}
|
|
|
|
return true;
|
|
}
|
|
|
|
///\brief Remove GEPs whose indices but the last one are loop invariant and
|
|
/// return the induction operand of the gep pointer.
|
|
static Value *stripGetElementPtr(Value *Ptr, ScalarEvolution *SE,
|
|
const DataLayout *DL, Loop *Lp) {
|
|
GetElementPtrInst *GEP = dyn_cast<GetElementPtrInst>(Ptr);
|
|
if (!GEP)
|
|
return Ptr;
|
|
|
|
unsigned InductionOperand = getGEPInductionOperand(DL, GEP);
|
|
|
|
// Check that all of the gep indices are uniform except for our induction
|
|
// operand.
|
|
for (unsigned i = 0, e = GEP->getNumOperands(); i != e; ++i)
|
|
if (i != InductionOperand &&
|
|
!SE->isLoopInvariant(SE->getSCEV(GEP->getOperand(i)), Lp))
|
|
return Ptr;
|
|
return GEP->getOperand(InductionOperand);
|
|
}
|
|
|
|
///\brief Look for a cast use of the passed value.
|
|
static Value *getUniqueCastUse(Value *Ptr, Loop *Lp, Type *Ty) {
|
|
Value *UniqueCast = nullptr;
|
|
for (User *U : Ptr->users()) {
|
|
CastInst *CI = dyn_cast<CastInst>(U);
|
|
if (CI && CI->getType() == Ty) {
|
|
if (!UniqueCast)
|
|
UniqueCast = CI;
|
|
else
|
|
return nullptr;
|
|
}
|
|
}
|
|
return UniqueCast;
|
|
}
|
|
|
|
///\brief Get the stride of a pointer access in a loop.
|
|
/// Looks for symbolic strides "a[i*stride]". Returns the symbolic stride as a
|
|
/// pointer to the Value, or null otherwise.
|
|
static Value *getStrideFromPointer(Value *Ptr, ScalarEvolution *SE,
|
|
const DataLayout *DL, Loop *Lp) {
|
|
const PointerType *PtrTy = dyn_cast<PointerType>(Ptr->getType());
|
|
if (!PtrTy || PtrTy->isAggregateType())
|
|
return nullptr;
|
|
|
|
// Try to remove a gep instruction to make the pointer (actually index at this
|
|
// point) easier analyzable. If OrigPtr is equal to Ptr we are analzying the
|
|
// pointer, otherwise, we are analyzing the index.
|
|
Value *OrigPtr = Ptr;
|
|
|
|
// The size of the pointer access.
|
|
int64_t PtrAccessSize = 1;
|
|
|
|
Ptr = stripGetElementPtr(Ptr, SE, DL, Lp);
|
|
const SCEV *V = SE->getSCEV(Ptr);
|
|
|
|
if (Ptr != OrigPtr)
|
|
// Strip off casts.
|
|
while (const SCEVCastExpr *C = dyn_cast<SCEVCastExpr>(V))
|
|
V = C->getOperand();
|
|
|
|
const SCEVAddRecExpr *S = dyn_cast<SCEVAddRecExpr>(V);
|
|
if (!S)
|
|
return nullptr;
|
|
|
|
V = S->getStepRecurrence(*SE);
|
|
if (!V)
|
|
return nullptr;
|
|
|
|
// Strip off the size of access multiplication if we are still analyzing the
|
|
// pointer.
|
|
if (OrigPtr == Ptr) {
|
|
DL->getTypeAllocSize(PtrTy->getElementType());
|
|
if (const SCEVMulExpr *M = dyn_cast<SCEVMulExpr>(V)) {
|
|
if (M->getOperand(0)->getSCEVType() != scConstant)
|
|
return nullptr;
|
|
|
|
const APInt &APStepVal =
|
|
cast<SCEVConstant>(M->getOperand(0))->getValue()->getValue();
|
|
|
|
// Huge step value - give up.
|
|
if (APStepVal.getBitWidth() > 64)
|
|
return nullptr;
|
|
|
|
int64_t StepVal = APStepVal.getSExtValue();
|
|
if (PtrAccessSize != StepVal)
|
|
return nullptr;
|
|
V = M->getOperand(1);
|
|
}
|
|
}
|
|
|
|
// Strip off casts.
|
|
Type *StripedOffRecurrenceCast = nullptr;
|
|
if (const SCEVCastExpr *C = dyn_cast<SCEVCastExpr>(V)) {
|
|
StripedOffRecurrenceCast = C->getType();
|
|
V = C->getOperand();
|
|
}
|
|
|
|
// Look for the loop invariant symbolic value.
|
|
const SCEVUnknown *U = dyn_cast<SCEVUnknown>(V);
|
|
if (!U)
|
|
return nullptr;
|
|
|
|
Value *Stride = U->getValue();
|
|
if (!Lp->isLoopInvariant(Stride))
|
|
return nullptr;
|
|
|
|
// If we have stripped off the recurrence cast we have to make sure that we
|
|
// return the value that is used in this loop so that we can replace it later.
|
|
if (StripedOffRecurrenceCast)
|
|
Stride = getUniqueCastUse(Stride, Lp, StripedOffRecurrenceCast);
|
|
|
|
return Stride;
|
|
}
|
|
|
|
void LoopVectorizationLegality::collectStridedAccess(Value *MemAccess) {
|
|
Value *Ptr = nullptr;
|
|
if (LoadInst *LI = dyn_cast<LoadInst>(MemAccess))
|
|
Ptr = LI->getPointerOperand();
|
|
else if (StoreInst *SI = dyn_cast<StoreInst>(MemAccess))
|
|
Ptr = SI->getPointerOperand();
|
|
else
|
|
return;
|
|
|
|
Value *Stride = getStrideFromPointer(Ptr, SE, DL, TheLoop);
|
|
if (!Stride)
|
|
return;
|
|
|
|
DEBUG(dbgs() << "LV: Found a strided access that we can version");
|
|
DEBUG(dbgs() << " Ptr: " << *Ptr << " Stride: " << *Stride << "\n");
|
|
Strides[Ptr] = Stride;
|
|
StrideSet.insert(Stride);
|
|
}
|
|
|
|
void LoopVectorizationLegality::collectLoopUniforms() {
|
|
// We now know that the loop is vectorizable!
|
|
// Collect variables that will remain uniform after vectorization.
|
|
std::vector<Value*> Worklist;
|
|
BasicBlock *Latch = TheLoop->getLoopLatch();
|
|
|
|
// Start with the conditional branch and walk up the block.
|
|
Worklist.push_back(Latch->getTerminator()->getOperand(0));
|
|
|
|
// Also add all consecutive pointer values; these values will be uniform
|
|
// after vectorization (and subsequent cleanup) and, until revectorization is
|
|
// supported, all dependencies must also be uniform.
|
|
for (Loop::block_iterator B = TheLoop->block_begin(),
|
|
BE = TheLoop->block_end(); B != BE; ++B)
|
|
for (BasicBlock::iterator I = (*B)->begin(), IE = (*B)->end();
|
|
I != IE; ++I)
|
|
if (I->getType()->isPointerTy() && isConsecutivePtr(I))
|
|
Worklist.insert(Worklist.end(), I->op_begin(), I->op_end());
|
|
|
|
while (!Worklist.empty()) {
|
|
Instruction *I = dyn_cast<Instruction>(Worklist.back());
|
|
Worklist.pop_back();
|
|
|
|
// Look at instructions inside this loop.
|
|
// Stop when reaching PHI nodes.
|
|
// TODO: we need to follow values all over the loop, not only in this block.
|
|
if (!I || !TheLoop->contains(I) || isa<PHINode>(I))
|
|
continue;
|
|
|
|
// This is a known uniform.
|
|
Uniforms.insert(I);
|
|
|
|
// Insert all operands.
|
|
Worklist.insert(Worklist.end(), I->op_begin(), I->op_end());
|
|
}
|
|
}
|
|
|
|
bool LoopVectorizationLegality::canVectorizeMemory() {
|
|
return LAI.canVectorizeMemory(Strides);
|
|
}
|
|
|
|
static bool hasMultipleUsesOf(Instruction *I,
|
|
SmallPtrSetImpl<Instruction *> &Insts) {
|
|
unsigned NumUses = 0;
|
|
for(User::op_iterator Use = I->op_begin(), E = I->op_end(); Use != E; ++Use) {
|
|
if (Insts.count(dyn_cast<Instruction>(*Use)))
|
|
++NumUses;
|
|
if (NumUses > 1)
|
|
return true;
|
|
}
|
|
|
|
return false;
|
|
}
|
|
|
|
static bool areAllUsesIn(Instruction *I, SmallPtrSetImpl<Instruction *> &Set) {
|
|
for(User::op_iterator Use = I->op_begin(), E = I->op_end(); Use != E; ++Use)
|
|
if (!Set.count(dyn_cast<Instruction>(*Use)))
|
|
return false;
|
|
return true;
|
|
}
|
|
|
|
bool LoopVectorizationLegality::AddReductionVar(PHINode *Phi,
|
|
ReductionKind Kind) {
|
|
if (Phi->getNumIncomingValues() != 2)
|
|
return false;
|
|
|
|
// Reduction variables are only found in the loop header block.
|
|
if (Phi->getParent() != TheLoop->getHeader())
|
|
return false;
|
|
|
|
// Obtain the reduction start value from the value that comes from the loop
|
|
// preheader.
|
|
Value *RdxStart = Phi->getIncomingValueForBlock(TheLoop->getLoopPreheader());
|
|
|
|
// ExitInstruction is the single value which is used outside the loop.
|
|
// We only allow for a single reduction value to be used outside the loop.
|
|
// This includes users of the reduction, variables (which form a cycle
|
|
// which ends in the phi node).
|
|
Instruction *ExitInstruction = nullptr;
|
|
// Indicates that we found a reduction operation in our scan.
|
|
bool FoundReduxOp = false;
|
|
|
|
// We start with the PHI node and scan for all of the users of this
|
|
// instruction. All users must be instructions that can be used as reduction
|
|
// variables (such as ADD). We must have a single out-of-block user. The cycle
|
|
// must include the original PHI.
|
|
bool FoundStartPHI = false;
|
|
|
|
// To recognize min/max patterns formed by a icmp select sequence, we store
|
|
// the number of instruction we saw from the recognized min/max pattern,
|
|
// to make sure we only see exactly the two instructions.
|
|
unsigned NumCmpSelectPatternInst = 0;
|
|
ReductionInstDesc ReduxDesc(false, nullptr);
|
|
|
|
SmallPtrSet<Instruction *, 8> VisitedInsts;
|
|
SmallVector<Instruction *, 8> Worklist;
|
|
Worklist.push_back(Phi);
|
|
VisitedInsts.insert(Phi);
|
|
|
|
// A value in the reduction can be used:
|
|
// - By the reduction:
|
|
// - Reduction operation:
|
|
// - One use of reduction value (safe).
|
|
// - Multiple use of reduction value (not safe).
|
|
// - PHI:
|
|
// - All uses of the PHI must be the reduction (safe).
|
|
// - Otherwise, not safe.
|
|
// - By one instruction outside of the loop (safe).
|
|
// - By further instructions outside of the loop (not safe).
|
|
// - By an instruction that is not part of the reduction (not safe).
|
|
// This is either:
|
|
// * An instruction type other than PHI or the reduction operation.
|
|
// * A PHI in the header other than the initial PHI.
|
|
while (!Worklist.empty()) {
|
|
Instruction *Cur = Worklist.back();
|
|
Worklist.pop_back();
|
|
|
|
// No Users.
|
|
// If the instruction has no users then this is a broken chain and can't be
|
|
// a reduction variable.
|
|
if (Cur->use_empty())
|
|
return false;
|
|
|
|
bool IsAPhi = isa<PHINode>(Cur);
|
|
|
|
// A header PHI use other than the original PHI.
|
|
if (Cur != Phi && IsAPhi && Cur->getParent() == Phi->getParent())
|
|
return false;
|
|
|
|
// Reductions of instructions such as Div, and Sub is only possible if the
|
|
// LHS is the reduction variable.
|
|
if (!Cur->isCommutative() && !IsAPhi && !isa<SelectInst>(Cur) &&
|
|
!isa<ICmpInst>(Cur) && !isa<FCmpInst>(Cur) &&
|
|
!VisitedInsts.count(dyn_cast<Instruction>(Cur->getOperand(0))))
|
|
return false;
|
|
|
|
// Any reduction instruction must be of one of the allowed kinds.
|
|
ReduxDesc = isReductionInstr(Cur, Kind, ReduxDesc);
|
|
if (!ReduxDesc.IsReduction)
|
|
return false;
|
|
|
|
// A reduction operation must only have one use of the reduction value.
|
|
if (!IsAPhi && Kind != RK_IntegerMinMax && Kind != RK_FloatMinMax &&
|
|
hasMultipleUsesOf(Cur, VisitedInsts))
|
|
return false;
|
|
|
|
// All inputs to a PHI node must be a reduction value.
|
|
if(IsAPhi && Cur != Phi && !areAllUsesIn(Cur, VisitedInsts))
|
|
return false;
|
|
|
|
if (Kind == RK_IntegerMinMax && (isa<ICmpInst>(Cur) ||
|
|
isa<SelectInst>(Cur)))
|
|
++NumCmpSelectPatternInst;
|
|
if (Kind == RK_FloatMinMax && (isa<FCmpInst>(Cur) ||
|
|
isa<SelectInst>(Cur)))
|
|
++NumCmpSelectPatternInst;
|
|
|
|
// Check whether we found a reduction operator.
|
|
FoundReduxOp |= !IsAPhi;
|
|
|
|
// Process users of current instruction. Push non-PHI nodes after PHI nodes
|
|
// onto the stack. This way we are going to have seen all inputs to PHI
|
|
// nodes once we get to them.
|
|
SmallVector<Instruction *, 8> NonPHIs;
|
|
SmallVector<Instruction *, 8> PHIs;
|
|
for (User *U : Cur->users()) {
|
|
Instruction *UI = cast<Instruction>(U);
|
|
|
|
// Check if we found the exit user.
|
|
BasicBlock *Parent = UI->getParent();
|
|
if (!TheLoop->contains(Parent)) {
|
|
// Exit if you find multiple outside users or if the header phi node is
|
|
// being used. In this case the user uses the value of the previous
|
|
// iteration, in which case we would loose "VF-1" iterations of the
|
|
// reduction operation if we vectorize.
|
|
if (ExitInstruction != nullptr || Cur == Phi)
|
|
return false;
|
|
|
|
// The instruction used by an outside user must be the last instruction
|
|
// before we feed back to the reduction phi. Otherwise, we loose VF-1
|
|
// operations on the value.
|
|
if (std::find(Phi->op_begin(), Phi->op_end(), Cur) == Phi->op_end())
|
|
return false;
|
|
|
|
ExitInstruction = Cur;
|
|
continue;
|
|
}
|
|
|
|
// Process instructions only once (termination). Each reduction cycle
|
|
// value must only be used once, except by phi nodes and min/max
|
|
// reductions which are represented as a cmp followed by a select.
|
|
ReductionInstDesc IgnoredVal(false, nullptr);
|
|
if (VisitedInsts.insert(UI).second) {
|
|
if (isa<PHINode>(UI))
|
|
PHIs.push_back(UI);
|
|
else
|
|
NonPHIs.push_back(UI);
|
|
} else if (!isa<PHINode>(UI) &&
|
|
((!isa<FCmpInst>(UI) &&
|
|
!isa<ICmpInst>(UI) &&
|
|
!isa<SelectInst>(UI)) ||
|
|
!isMinMaxSelectCmpPattern(UI, IgnoredVal).IsReduction))
|
|
return false;
|
|
|
|
// Remember that we completed the cycle.
|
|
if (UI == Phi)
|
|
FoundStartPHI = true;
|
|
}
|
|
Worklist.append(PHIs.begin(), PHIs.end());
|
|
Worklist.append(NonPHIs.begin(), NonPHIs.end());
|
|
}
|
|
|
|
// This means we have seen one but not the other instruction of the
|
|
// pattern or more than just a select and cmp.
|
|
if ((Kind == RK_IntegerMinMax || Kind == RK_FloatMinMax) &&
|
|
NumCmpSelectPatternInst != 2)
|
|
return false;
|
|
|
|
if (!FoundStartPHI || !FoundReduxOp || !ExitInstruction)
|
|
return false;
|
|
|
|
// We found a reduction var if we have reached the original phi node and we
|
|
// only have a single instruction with out-of-loop users.
|
|
|
|
// This instruction is allowed to have out-of-loop users.
|
|
AllowedExit.insert(ExitInstruction);
|
|
|
|
// Save the description of this reduction variable.
|
|
ReductionDescriptor RD(RdxStart, ExitInstruction, Kind,
|
|
ReduxDesc.MinMaxKind);
|
|
Reductions[Phi] = RD;
|
|
// We've ended the cycle. This is a reduction variable if we have an
|
|
// outside user and it has a binary op.
|
|
|
|
return true;
|
|
}
|
|
|
|
/// Returns true if the instruction is a Select(ICmp(X, Y), X, Y) instruction
|
|
/// pattern corresponding to a min(X, Y) or max(X, Y).
|
|
LoopVectorizationLegality::ReductionInstDesc
|
|
LoopVectorizationLegality::isMinMaxSelectCmpPattern(Instruction *I,
|
|
ReductionInstDesc &Prev) {
|
|
|
|
assert((isa<ICmpInst>(I) || isa<FCmpInst>(I) || isa<SelectInst>(I)) &&
|
|
"Expect a select instruction");
|
|
Instruction *Cmp = nullptr;
|
|
SelectInst *Select = nullptr;
|
|
|
|
// We must handle the select(cmp()) as a single instruction. Advance to the
|
|
// select.
|
|
if ((Cmp = dyn_cast<ICmpInst>(I)) || (Cmp = dyn_cast<FCmpInst>(I))) {
|
|
if (!Cmp->hasOneUse() || !(Select = dyn_cast<SelectInst>(*I->user_begin())))
|
|
return ReductionInstDesc(false, I);
|
|
return ReductionInstDesc(Select, Prev.MinMaxKind);
|
|
}
|
|
|
|
// Only handle single use cases for now.
|
|
if (!(Select = dyn_cast<SelectInst>(I)))
|
|
return ReductionInstDesc(false, I);
|
|
if (!(Cmp = dyn_cast<ICmpInst>(I->getOperand(0))) &&
|
|
!(Cmp = dyn_cast<FCmpInst>(I->getOperand(0))))
|
|
return ReductionInstDesc(false, I);
|
|
if (!Cmp->hasOneUse())
|
|
return ReductionInstDesc(false, I);
|
|
|
|
Value *CmpLeft;
|
|
Value *CmpRight;
|
|
|
|
// Look for a min/max pattern.
|
|
if (m_UMin(m_Value(CmpLeft), m_Value(CmpRight)).match(Select))
|
|
return ReductionInstDesc(Select, MRK_UIntMin);
|
|
else if (m_UMax(m_Value(CmpLeft), m_Value(CmpRight)).match(Select))
|
|
return ReductionInstDesc(Select, MRK_UIntMax);
|
|
else if (m_SMax(m_Value(CmpLeft), m_Value(CmpRight)).match(Select))
|
|
return ReductionInstDesc(Select, MRK_SIntMax);
|
|
else if (m_SMin(m_Value(CmpLeft), m_Value(CmpRight)).match(Select))
|
|
return ReductionInstDesc(Select, MRK_SIntMin);
|
|
else if (m_OrdFMin(m_Value(CmpLeft), m_Value(CmpRight)).match(Select))
|
|
return ReductionInstDesc(Select, MRK_FloatMin);
|
|
else if (m_OrdFMax(m_Value(CmpLeft), m_Value(CmpRight)).match(Select))
|
|
return ReductionInstDesc(Select, MRK_FloatMax);
|
|
else if (m_UnordFMin(m_Value(CmpLeft), m_Value(CmpRight)).match(Select))
|
|
return ReductionInstDesc(Select, MRK_FloatMin);
|
|
else if (m_UnordFMax(m_Value(CmpLeft), m_Value(CmpRight)).match(Select))
|
|
return ReductionInstDesc(Select, MRK_FloatMax);
|
|
|
|
return ReductionInstDesc(false, I);
|
|
}
|
|
|
|
LoopVectorizationLegality::ReductionInstDesc
|
|
LoopVectorizationLegality::isReductionInstr(Instruction *I,
|
|
ReductionKind Kind,
|
|
ReductionInstDesc &Prev) {
|
|
bool FP = I->getType()->isFloatingPointTy();
|
|
bool FastMath = FP && I->hasUnsafeAlgebra();
|
|
switch (I->getOpcode()) {
|
|
default:
|
|
return ReductionInstDesc(false, I);
|
|
case Instruction::PHI:
|
|
if (FP && (Kind != RK_FloatMult && Kind != RK_FloatAdd &&
|
|
Kind != RK_FloatMinMax))
|
|
return ReductionInstDesc(false, I);
|
|
return ReductionInstDesc(I, Prev.MinMaxKind);
|
|
case Instruction::Sub:
|
|
case Instruction::Add:
|
|
return ReductionInstDesc(Kind == RK_IntegerAdd, I);
|
|
case Instruction::Mul:
|
|
return ReductionInstDesc(Kind == RK_IntegerMult, I);
|
|
case Instruction::And:
|
|
return ReductionInstDesc(Kind == RK_IntegerAnd, I);
|
|
case Instruction::Or:
|
|
return ReductionInstDesc(Kind == RK_IntegerOr, I);
|
|
case Instruction::Xor:
|
|
return ReductionInstDesc(Kind == RK_IntegerXor, I);
|
|
case Instruction::FMul:
|
|
return ReductionInstDesc(Kind == RK_FloatMult && FastMath, I);
|
|
case Instruction::FSub:
|
|
case Instruction::FAdd:
|
|
return ReductionInstDesc(Kind == RK_FloatAdd && FastMath, I);
|
|
case Instruction::FCmp:
|
|
case Instruction::ICmp:
|
|
case Instruction::Select:
|
|
if (Kind != RK_IntegerMinMax &&
|
|
(!HasFunNoNaNAttr || Kind != RK_FloatMinMax))
|
|
return ReductionInstDesc(false, I);
|
|
return isMinMaxSelectCmpPattern(I, Prev);
|
|
}
|
|
}
|
|
|
|
LoopVectorizationLegality::InductionKind
|
|
LoopVectorizationLegality::isInductionVariable(PHINode *Phi,
|
|
ConstantInt *&StepValue) {
|
|
Type *PhiTy = Phi->getType();
|
|
// We only handle integer and pointer inductions variables.
|
|
if (!PhiTy->isIntegerTy() && !PhiTy->isPointerTy())
|
|
return IK_NoInduction;
|
|
|
|
// Check that the PHI is consecutive.
|
|
const SCEV *PhiScev = SE->getSCEV(Phi);
|
|
const SCEVAddRecExpr *AR = dyn_cast<SCEVAddRecExpr>(PhiScev);
|
|
if (!AR) {
|
|
DEBUG(dbgs() << "LV: PHI is not a poly recurrence.\n");
|
|
return IK_NoInduction;
|
|
}
|
|
|
|
const SCEV *Step = AR->getStepRecurrence(*SE);
|
|
// Calculate the pointer stride and check if it is consecutive.
|
|
const SCEVConstant *C = dyn_cast<SCEVConstant>(Step);
|
|
if (!C)
|
|
return IK_NoInduction;
|
|
|
|
ConstantInt *CV = C->getValue();
|
|
if (PhiTy->isIntegerTy()) {
|
|
StepValue = CV;
|
|
return IK_IntInduction;
|
|
}
|
|
|
|
assert(PhiTy->isPointerTy() && "The PHI must be a pointer");
|
|
Type *PointerElementType = PhiTy->getPointerElementType();
|
|
// The pointer stride cannot be determined if the pointer element type is not
|
|
// sized.
|
|
if (!PointerElementType->isSized())
|
|
return IK_NoInduction;
|
|
|
|
int64_t Size = static_cast<int64_t>(DL->getTypeAllocSize(PointerElementType));
|
|
int64_t CVSize = CV->getSExtValue();
|
|
if (CVSize % Size)
|
|
return IK_NoInduction;
|
|
StepValue = ConstantInt::getSigned(CV->getType(), CVSize / Size);
|
|
return IK_PtrInduction;
|
|
}
|
|
|
|
bool LoopVectorizationLegality::isInductionVariable(const Value *V) {
|
|
Value *In0 = const_cast<Value*>(V);
|
|
PHINode *PN = dyn_cast_or_null<PHINode>(In0);
|
|
if (!PN)
|
|
return false;
|
|
|
|
return Inductions.count(PN);
|
|
}
|
|
|
|
bool LoopVectorizationLegality::blockNeedsPredication(BasicBlock *BB) {
|
|
return LoopAccessInfo::blockNeedsPredication(BB, TheLoop, DT);
|
|
}
|
|
|
|
bool LoopVectorizationLegality::blockCanBePredicated(BasicBlock *BB,
|
|
SmallPtrSetImpl<Value *> &SafePtrs) {
|
|
|
|
for (BasicBlock::iterator it = BB->begin(), e = BB->end(); it != e; ++it) {
|
|
// Check that we don't have a constant expression that can trap as operand.
|
|
for (Instruction::op_iterator OI = it->op_begin(), OE = it->op_end();
|
|
OI != OE; ++OI) {
|
|
if (Constant *C = dyn_cast<Constant>(*OI))
|
|
if (C->canTrap())
|
|
return false;
|
|
}
|
|
// We might be able to hoist the load.
|
|
if (it->mayReadFromMemory()) {
|
|
LoadInst *LI = dyn_cast<LoadInst>(it);
|
|
if (!LI)
|
|
return false;
|
|
if (!SafePtrs.count(LI->getPointerOperand())) {
|
|
if (isLegalMaskedLoad(LI->getType(), LI->getPointerOperand())) {
|
|
MaskedOp.insert(LI);
|
|
continue;
|
|
}
|
|
return false;
|
|
}
|
|
}
|
|
|
|
// We don't predicate stores at the moment.
|
|
if (it->mayWriteToMemory()) {
|
|
StoreInst *SI = dyn_cast<StoreInst>(it);
|
|
// We only support predication of stores in basic blocks with one
|
|
// predecessor.
|
|
if (!SI)
|
|
return false;
|
|
|
|
bool isSafePtr = (SafePtrs.count(SI->getPointerOperand()) != 0);
|
|
bool isSinglePredecessor = SI->getParent()->getSinglePredecessor();
|
|
|
|
if (++NumPredStores > NumberOfStoresToPredicate || !isSafePtr ||
|
|
!isSinglePredecessor) {
|
|
// Build a masked store if it is legal for the target, otherwise scalarize
|
|
// the block.
|
|
bool isLegalMaskedOp =
|
|
isLegalMaskedStore(SI->getValueOperand()->getType(),
|
|
SI->getPointerOperand());
|
|
if (isLegalMaskedOp) {
|
|
--NumPredStores;
|
|
MaskedOp.insert(SI);
|
|
continue;
|
|
}
|
|
return false;
|
|
}
|
|
}
|
|
if (it->mayThrow())
|
|
return false;
|
|
|
|
// The instructions below can trap.
|
|
switch (it->getOpcode()) {
|
|
default: continue;
|
|
case Instruction::UDiv:
|
|
case Instruction::SDiv:
|
|
case Instruction::URem:
|
|
case Instruction::SRem:
|
|
return false;
|
|
}
|
|
}
|
|
|
|
return true;
|
|
}
|
|
|
|
LoopVectorizationCostModel::VectorizationFactor
|
|
LoopVectorizationCostModel::selectVectorizationFactor(bool OptForSize) {
|
|
// Width 1 means no vectorize
|
|
VectorizationFactor Factor = { 1U, 0U };
|
|
if (OptForSize && Legal->getRuntimePointerCheck()->Need) {
|
|
emitAnalysis(VectorizationReport() <<
|
|
"runtime pointer checks needed. Enable vectorization of this "
|
|
"loop with '#pragma clang loop vectorize(enable)' when "
|
|
"compiling with -Os");
|
|
DEBUG(dbgs() << "LV: Aborting. Runtime ptr check is required in Os.\n");
|
|
return Factor;
|
|
}
|
|
|
|
if (!EnableCondStoresVectorization && Legal->getNumPredStores()) {
|
|
emitAnalysis(VectorizationReport() <<
|
|
"store that is conditionally executed prevents vectorization");
|
|
DEBUG(dbgs() << "LV: No vectorization. There are conditional stores.\n");
|
|
return Factor;
|
|
}
|
|
|
|
// Find the trip count.
|
|
unsigned TC = SE->getSmallConstantTripCount(TheLoop);
|
|
DEBUG(dbgs() << "LV: Found trip count: " << TC << '\n');
|
|
|
|
unsigned WidestType = getWidestType();
|
|
unsigned WidestRegister = TTI.getRegisterBitWidth(true);
|
|
unsigned MaxSafeDepDist = -1U;
|
|
if (Legal->getMaxSafeDepDistBytes() != -1U)
|
|
MaxSafeDepDist = Legal->getMaxSafeDepDistBytes() * 8;
|
|
WidestRegister = ((WidestRegister < MaxSafeDepDist) ?
|
|
WidestRegister : MaxSafeDepDist);
|
|
unsigned MaxVectorSize = WidestRegister / WidestType;
|
|
DEBUG(dbgs() << "LV: The Widest type: " << WidestType << " bits.\n");
|
|
DEBUG(dbgs() << "LV: The Widest register is: "
|
|
<< WidestRegister << " bits.\n");
|
|
|
|
if (MaxVectorSize == 0) {
|
|
DEBUG(dbgs() << "LV: The target has no vector registers.\n");
|
|
MaxVectorSize = 1;
|
|
}
|
|
|
|
assert(MaxVectorSize <= 64 && "Did not expect to pack so many elements"
|
|
" into one vector!");
|
|
|
|
unsigned VF = MaxVectorSize;
|
|
|
|
// If we optimize the program for size, avoid creating the tail loop.
|
|
if (OptForSize) {
|
|
// If we are unable to calculate the trip count then don't try to vectorize.
|
|
if (TC < 2) {
|
|
emitAnalysis
|
|
(VectorizationReport() <<
|
|
"unable to calculate the loop count due to complex control flow");
|
|
DEBUG(dbgs() << "LV: Aborting. A tail loop is required in Os.\n");
|
|
return Factor;
|
|
}
|
|
|
|
// Find the maximum SIMD width that can fit within the trip count.
|
|
VF = TC % MaxVectorSize;
|
|
|
|
if (VF == 0)
|
|
VF = MaxVectorSize;
|
|
|
|
// If the trip count that we found modulo the vectorization factor is not
|
|
// zero then we require a tail.
|
|
if (VF < 2) {
|
|
emitAnalysis(VectorizationReport() <<
|
|
"cannot optimize for size and vectorize at the "
|
|
"same time. Enable vectorization of this loop "
|
|
"with '#pragma clang loop vectorize(enable)' "
|
|
"when compiling with -Os");
|
|
DEBUG(dbgs() << "LV: Aborting. A tail loop is required in Os.\n");
|
|
return Factor;
|
|
}
|
|
}
|
|
|
|
int UserVF = Hints->getWidth();
|
|
if (UserVF != 0) {
|
|
assert(isPowerOf2_32(UserVF) && "VF needs to be a power of two");
|
|
DEBUG(dbgs() << "LV: Using user VF " << UserVF << ".\n");
|
|
|
|
Factor.Width = UserVF;
|
|
return Factor;
|
|
}
|
|
|
|
float Cost = expectedCost(1);
|
|
#ifndef NDEBUG
|
|
const float ScalarCost = Cost;
|
|
#endif /* NDEBUG */
|
|
unsigned Width = 1;
|
|
DEBUG(dbgs() << "LV: Scalar loop costs: " << (int)ScalarCost << ".\n");
|
|
|
|
bool ForceVectorization = Hints->getForce() == LoopVectorizeHints::FK_Enabled;
|
|
// Ignore scalar width, because the user explicitly wants vectorization.
|
|
if (ForceVectorization && VF > 1) {
|
|
Width = 2;
|
|
Cost = expectedCost(Width) / (float)Width;
|
|
}
|
|
|
|
for (unsigned i=2; i <= VF; i*=2) {
|
|
// Notice that the vector loop needs to be executed less times, so
|
|
// we need to divide the cost of the vector loops by the width of
|
|
// the vector elements.
|
|
float VectorCost = expectedCost(i) / (float)i;
|
|
DEBUG(dbgs() << "LV: Vector loop of width " << i << " costs: " <<
|
|
(int)VectorCost << ".\n");
|
|
if (VectorCost < Cost) {
|
|
Cost = VectorCost;
|
|
Width = i;
|
|
}
|
|
}
|
|
|
|
DEBUG(if (ForceVectorization && Width > 1 && Cost >= ScalarCost) dbgs()
|
|
<< "LV: Vectorization seems to be not beneficial, "
|
|
<< "but was forced by a user.\n");
|
|
DEBUG(dbgs() << "LV: Selecting VF: "<< Width << ".\n");
|
|
Factor.Width = Width;
|
|
Factor.Cost = Width * Cost;
|
|
return Factor;
|
|
}
|
|
|
|
unsigned LoopVectorizationCostModel::getWidestType() {
|
|
unsigned MaxWidth = 8;
|
|
|
|
// For each block.
|
|
for (Loop::block_iterator bb = TheLoop->block_begin(),
|
|
be = TheLoop->block_end(); bb != be; ++bb) {
|
|
BasicBlock *BB = *bb;
|
|
|
|
// For each instruction in the loop.
|
|
for (BasicBlock::iterator it = BB->begin(), e = BB->end(); it != e; ++it) {
|
|
Type *T = it->getType();
|
|
|
|
// Ignore ephemeral values.
|
|
if (EphValues.count(it))
|
|
continue;
|
|
|
|
// Only examine Loads, Stores and PHINodes.
|
|
if (!isa<LoadInst>(it) && !isa<StoreInst>(it) && !isa<PHINode>(it))
|
|
continue;
|
|
|
|
// Examine PHI nodes that are reduction variables.
|
|
if (PHINode *PN = dyn_cast<PHINode>(it))
|
|
if (!Legal->getReductionVars()->count(PN))
|
|
continue;
|
|
|
|
// Examine the stored values.
|
|
if (StoreInst *ST = dyn_cast<StoreInst>(it))
|
|
T = ST->getValueOperand()->getType();
|
|
|
|
// Ignore loaded pointer types and stored pointer types that are not
|
|
// consecutive. However, we do want to take consecutive stores/loads of
|
|
// pointer vectors into account.
|
|
if (T->isPointerTy() && !isConsecutiveLoadOrStore(it))
|
|
continue;
|
|
|
|
MaxWidth = std::max(MaxWidth,
|
|
(unsigned)DL->getTypeSizeInBits(T->getScalarType()));
|
|
}
|
|
}
|
|
|
|
return MaxWidth;
|
|
}
|
|
|
|
unsigned
|
|
LoopVectorizationCostModel::selectUnrollFactor(bool OptForSize,
|
|
unsigned VF,
|
|
unsigned LoopCost) {
|
|
|
|
// -- The unroll heuristics --
|
|
// We unroll the loop in order to expose ILP and reduce the loop overhead.
|
|
// There are many micro-architectural considerations that we can't predict
|
|
// at this level. For example, frontend pressure (on decode or fetch) due to
|
|
// code size, or the number and capabilities of the execution ports.
|
|
//
|
|
// We use the following heuristics to select the unroll factor:
|
|
// 1. If the code has reductions, then we unroll in order to break the cross
|
|
// iteration dependency.
|
|
// 2. If the loop is really small, then we unroll in order to reduce the loop
|
|
// overhead.
|
|
// 3. We don't unroll if we think that we will spill registers to memory due
|
|
// to the increased register pressure.
|
|
|
|
// Use the user preference, unless 'auto' is selected.
|
|
int UserUF = Hints->getInterleave();
|
|
if (UserUF != 0)
|
|
return UserUF;
|
|
|
|
// When we optimize for size, we don't unroll.
|
|
if (OptForSize)
|
|
return 1;
|
|
|
|
// We used the distance for the unroll factor.
|
|
if (Legal->getMaxSafeDepDistBytes() != -1U)
|
|
return 1;
|
|
|
|
// Do not unroll loops with a relatively small trip count.
|
|
unsigned TC = SE->getSmallConstantTripCount(TheLoop);
|
|
if (TC > 1 && TC < TinyTripCountUnrollThreshold)
|
|
return 1;
|
|
|
|
unsigned TargetNumRegisters = TTI.getNumberOfRegisters(VF > 1);
|
|
DEBUG(dbgs() << "LV: The target has " << TargetNumRegisters <<
|
|
" registers\n");
|
|
|
|
if (VF == 1) {
|
|
if (ForceTargetNumScalarRegs.getNumOccurrences() > 0)
|
|
TargetNumRegisters = ForceTargetNumScalarRegs;
|
|
} else {
|
|
if (ForceTargetNumVectorRegs.getNumOccurrences() > 0)
|
|
TargetNumRegisters = ForceTargetNumVectorRegs;
|
|
}
|
|
|
|
LoopVectorizationCostModel::RegisterUsage R = calculateRegisterUsage();
|
|
// We divide by these constants so assume that we have at least one
|
|
// instruction that uses at least one register.
|
|
R.MaxLocalUsers = std::max(R.MaxLocalUsers, 1U);
|
|
R.NumInstructions = std::max(R.NumInstructions, 1U);
|
|
|
|
// We calculate the unroll factor using the following formula.
|
|
// Subtract the number of loop invariants from the number of available
|
|
// registers. These registers are used by all of the unrolled instances.
|
|
// Next, divide the remaining registers by the number of registers that is
|
|
// required by the loop, in order to estimate how many parallel instances
|
|
// fit without causing spills. All of this is rounded down if necessary to be
|
|
// a power of two. We want power of two unroll factors to simplify any
|
|
// addressing operations or alignment considerations.
|
|
unsigned UF = PowerOf2Floor((TargetNumRegisters - R.LoopInvariantRegs) /
|
|
R.MaxLocalUsers);
|
|
|
|
// Don't count the induction variable as unrolled.
|
|
if (EnableIndVarRegisterHeur)
|
|
UF = PowerOf2Floor((TargetNumRegisters - R.LoopInvariantRegs - 1) /
|
|
std::max(1U, (R.MaxLocalUsers - 1)));
|
|
|
|
// Clamp the unroll factor ranges to reasonable factors.
|
|
unsigned MaxInterleaveSize = TTI.getMaxInterleaveFactor();
|
|
|
|
// Check if the user has overridden the unroll max.
|
|
if (VF == 1) {
|
|
if (ForceTargetMaxScalarInterleaveFactor.getNumOccurrences() > 0)
|
|
MaxInterleaveSize = ForceTargetMaxScalarInterleaveFactor;
|
|
} else {
|
|
if (ForceTargetMaxVectorInterleaveFactor.getNumOccurrences() > 0)
|
|
MaxInterleaveSize = ForceTargetMaxVectorInterleaveFactor;
|
|
}
|
|
|
|
// If we did not calculate the cost for VF (because the user selected the VF)
|
|
// then we calculate the cost of VF here.
|
|
if (LoopCost == 0)
|
|
LoopCost = expectedCost(VF);
|
|
|
|
// Clamp the calculated UF to be between the 1 and the max unroll factor
|
|
// that the target allows.
|
|
if (UF > MaxInterleaveSize)
|
|
UF = MaxInterleaveSize;
|
|
else if (UF < 1)
|
|
UF = 1;
|
|
|
|
// Unroll if we vectorized this loop and there is a reduction that could
|
|
// benefit from unrolling.
|
|
if (VF > 1 && Legal->getReductionVars()->size()) {
|
|
DEBUG(dbgs() << "LV: Unrolling because of reductions.\n");
|
|
return UF;
|
|
}
|
|
|
|
// Note that if we've already vectorized the loop we will have done the
|
|
// runtime check and so unrolling won't require further checks.
|
|
bool UnrollingRequiresRuntimePointerCheck =
|
|
(VF == 1 && Legal->getRuntimePointerCheck()->Need);
|
|
|
|
// We want to unroll small loops in order to reduce the loop overhead and
|
|
// potentially expose ILP opportunities.
|
|
DEBUG(dbgs() << "LV: Loop cost is " << LoopCost << '\n');
|
|
if (!UnrollingRequiresRuntimePointerCheck &&
|
|
LoopCost < SmallLoopCost) {
|
|
// We assume that the cost overhead is 1 and we use the cost model
|
|
// to estimate the cost of the loop and unroll until the cost of the
|
|
// loop overhead is about 5% of the cost of the loop.
|
|
unsigned SmallUF = std::min(UF, (unsigned)PowerOf2Floor(SmallLoopCost / LoopCost));
|
|
|
|
// Unroll until store/load ports (estimated by max unroll factor) are
|
|
// saturated.
|
|
unsigned NumStores = Legal->getNumStores();
|
|
unsigned NumLoads = Legal->getNumLoads();
|
|
unsigned StoresUF = UF / (NumStores ? NumStores : 1);
|
|
unsigned LoadsUF = UF / (NumLoads ? NumLoads : 1);
|
|
|
|
// If we have a scalar reduction (vector reductions are already dealt with
|
|
// by this point), we can increase the critical path length if the loop
|
|
// we're unrolling is inside another loop. Limit, by default to 2, so the
|
|
// critical path only gets increased by one reduction operation.
|
|
if (Legal->getReductionVars()->size() &&
|
|
TheLoop->getLoopDepth() > 1) {
|
|
unsigned F = static_cast<unsigned>(MaxNestedScalarReductionUF);
|
|
SmallUF = std::min(SmallUF, F);
|
|
StoresUF = std::min(StoresUF, F);
|
|
LoadsUF = std::min(LoadsUF, F);
|
|
}
|
|
|
|
if (EnableLoadStoreRuntimeUnroll && std::max(StoresUF, LoadsUF) > SmallUF) {
|
|
DEBUG(dbgs() << "LV: Unrolling to saturate store or load ports.\n");
|
|
return std::max(StoresUF, LoadsUF);
|
|
}
|
|
|
|
DEBUG(dbgs() << "LV: Unrolling to reduce branch cost.\n");
|
|
return SmallUF;
|
|
}
|
|
|
|
DEBUG(dbgs() << "LV: Not Unrolling.\n");
|
|
return 1;
|
|
}
|
|
|
|
LoopVectorizationCostModel::RegisterUsage
|
|
LoopVectorizationCostModel::calculateRegisterUsage() {
|
|
// This function calculates the register usage by measuring the highest number
|
|
// of values that are alive at a single location. Obviously, this is a very
|
|
// rough estimation. We scan the loop in a topological order in order and
|
|
// assign a number to each instruction. We use RPO to ensure that defs are
|
|
// met before their users. We assume that each instruction that has in-loop
|
|
// users starts an interval. We record every time that an in-loop value is
|
|
// used, so we have a list of the first and last occurrences of each
|
|
// instruction. Next, we transpose this data structure into a multi map that
|
|
// holds the list of intervals that *end* at a specific location. This multi
|
|
// map allows us to perform a linear search. We scan the instructions linearly
|
|
// and record each time that a new interval starts, by placing it in a set.
|
|
// If we find this value in the multi-map then we remove it from the set.
|
|
// The max register usage is the maximum size of the set.
|
|
// We also search for instructions that are defined outside the loop, but are
|
|
// used inside the loop. We need this number separately from the max-interval
|
|
// usage number because when we unroll, loop-invariant values do not take
|
|
// more register.
|
|
LoopBlocksDFS DFS(TheLoop);
|
|
DFS.perform(LI);
|
|
|
|
RegisterUsage R;
|
|
R.NumInstructions = 0;
|
|
|
|
// Each 'key' in the map opens a new interval. The values
|
|
// of the map are the index of the 'last seen' usage of the
|
|
// instruction that is the key.
|
|
typedef DenseMap<Instruction*, unsigned> IntervalMap;
|
|
// Maps instruction to its index.
|
|
DenseMap<unsigned, Instruction*> IdxToInstr;
|
|
// Marks the end of each interval.
|
|
IntervalMap EndPoint;
|
|
// Saves the list of instruction indices that are used in the loop.
|
|
SmallSet<Instruction*, 8> Ends;
|
|
// Saves the list of values that are used in the loop but are
|
|
// defined outside the loop, such as arguments and constants.
|
|
SmallPtrSet<Value*, 8> LoopInvariants;
|
|
|
|
unsigned Index = 0;
|
|
for (LoopBlocksDFS::RPOIterator bb = DFS.beginRPO(),
|
|
be = DFS.endRPO(); bb != be; ++bb) {
|
|
R.NumInstructions += (*bb)->size();
|
|
for (BasicBlock::iterator it = (*bb)->begin(), e = (*bb)->end(); it != e;
|
|
++it) {
|
|
Instruction *I = it;
|
|
IdxToInstr[Index++] = I;
|
|
|
|
// Save the end location of each USE.
|
|
for (unsigned i = 0; i < I->getNumOperands(); ++i) {
|
|
Value *U = I->getOperand(i);
|
|
Instruction *Instr = dyn_cast<Instruction>(U);
|
|
|
|
// Ignore non-instruction values such as arguments, constants, etc.
|
|
if (!Instr) continue;
|
|
|
|
// If this instruction is outside the loop then record it and continue.
|
|
if (!TheLoop->contains(Instr)) {
|
|
LoopInvariants.insert(Instr);
|
|
continue;
|
|
}
|
|
|
|
// Overwrite previous end points.
|
|
EndPoint[Instr] = Index;
|
|
Ends.insert(Instr);
|
|
}
|
|
}
|
|
}
|
|
|
|
// Saves the list of intervals that end with the index in 'key'.
|
|
typedef SmallVector<Instruction*, 2> InstrList;
|
|
DenseMap<unsigned, InstrList> TransposeEnds;
|
|
|
|
// Transpose the EndPoints to a list of values that end at each index.
|
|
for (IntervalMap::iterator it = EndPoint.begin(), e = EndPoint.end();
|
|
it != e; ++it)
|
|
TransposeEnds[it->second].push_back(it->first);
|
|
|
|
SmallSet<Instruction*, 8> OpenIntervals;
|
|
unsigned MaxUsage = 0;
|
|
|
|
|
|
DEBUG(dbgs() << "LV(REG): Calculating max register usage:\n");
|
|
for (unsigned int i = 0; i < Index; ++i) {
|
|
Instruction *I = IdxToInstr[i];
|
|
// Ignore instructions that are never used within the loop.
|
|
if (!Ends.count(I)) continue;
|
|
|
|
// Ignore ephemeral values.
|
|
if (EphValues.count(I))
|
|
continue;
|
|
|
|
// Remove all of the instructions that end at this location.
|
|
InstrList &List = TransposeEnds[i];
|
|
for (unsigned int j=0, e = List.size(); j < e; ++j)
|
|
OpenIntervals.erase(List[j]);
|
|
|
|
// Count the number of live interals.
|
|
MaxUsage = std::max(MaxUsage, OpenIntervals.size());
|
|
|
|
DEBUG(dbgs() << "LV(REG): At #" << i << " Interval # " <<
|
|
OpenIntervals.size() << '\n');
|
|
|
|
// Add the current instruction to the list of open intervals.
|
|
OpenIntervals.insert(I);
|
|
}
|
|
|
|
unsigned Invariant = LoopInvariants.size();
|
|
DEBUG(dbgs() << "LV(REG): Found max usage: " << MaxUsage << '\n');
|
|
DEBUG(dbgs() << "LV(REG): Found invariant usage: " << Invariant << '\n');
|
|
DEBUG(dbgs() << "LV(REG): LoopSize: " << R.NumInstructions << '\n');
|
|
|
|
R.LoopInvariantRegs = Invariant;
|
|
R.MaxLocalUsers = MaxUsage;
|
|
return R;
|
|
}
|
|
|
|
unsigned LoopVectorizationCostModel::expectedCost(unsigned VF) {
|
|
unsigned Cost = 0;
|
|
|
|
// For each block.
|
|
for (Loop::block_iterator bb = TheLoop->block_begin(),
|
|
be = TheLoop->block_end(); bb != be; ++bb) {
|
|
unsigned BlockCost = 0;
|
|
BasicBlock *BB = *bb;
|
|
|
|
// For each instruction in the old loop.
|
|
for (BasicBlock::iterator it = BB->begin(), e = BB->end(); it != e; ++it) {
|
|
// Skip dbg intrinsics.
|
|
if (isa<DbgInfoIntrinsic>(it))
|
|
continue;
|
|
|
|
// Ignore ephemeral values.
|
|
if (EphValues.count(it))
|
|
continue;
|
|
|
|
unsigned C = getInstructionCost(it, VF);
|
|
|
|
// Check if we should override the cost.
|
|
if (ForceTargetInstructionCost.getNumOccurrences() > 0)
|
|
C = ForceTargetInstructionCost;
|
|
|
|
BlockCost += C;
|
|
DEBUG(dbgs() << "LV: Found an estimated cost of " << C << " for VF " <<
|
|
VF << " For instruction: " << *it << '\n');
|
|
}
|
|
|
|
// We assume that if-converted blocks have a 50% chance of being executed.
|
|
// When the code is scalar then some of the blocks are avoided due to CF.
|
|
// When the code is vectorized we execute all code paths.
|
|
if (VF == 1 && Legal->blockNeedsPredication(*bb))
|
|
BlockCost /= 2;
|
|
|
|
Cost += BlockCost;
|
|
}
|
|
|
|
return Cost;
|
|
}
|
|
|
|
/// \brief Check whether the address computation for a non-consecutive memory
|
|
/// access looks like an unlikely candidate for being merged into the indexing
|
|
/// mode.
|
|
///
|
|
/// We look for a GEP which has one index that is an induction variable and all
|
|
/// other indices are loop invariant. If the stride of this access is also
|
|
/// within a small bound we decide that this address computation can likely be
|
|
/// merged into the addressing mode.
|
|
/// In all other cases, we identify the address computation as complex.
|
|
static bool isLikelyComplexAddressComputation(Value *Ptr,
|
|
LoopVectorizationLegality *Legal,
|
|
ScalarEvolution *SE,
|
|
const Loop *TheLoop) {
|
|
GetElementPtrInst *Gep = dyn_cast<GetElementPtrInst>(Ptr);
|
|
if (!Gep)
|
|
return true;
|
|
|
|
// We are looking for a gep with all loop invariant indices except for one
|
|
// which should be an induction variable.
|
|
unsigned NumOperands = Gep->getNumOperands();
|
|
for (unsigned i = 1; i < NumOperands; ++i) {
|
|
Value *Opd = Gep->getOperand(i);
|
|
if (!SE->isLoopInvariant(SE->getSCEV(Opd), TheLoop) &&
|
|
!Legal->isInductionVariable(Opd))
|
|
return true;
|
|
}
|
|
|
|
// Now we know we have a GEP ptr, %inv, %ind, %inv. Make sure that the step
|
|
// can likely be merged into the address computation.
|
|
unsigned MaxMergeDistance = 64;
|
|
|
|
const SCEVAddRecExpr *AddRec = dyn_cast<SCEVAddRecExpr>(SE->getSCEV(Ptr));
|
|
if (!AddRec)
|
|
return true;
|
|
|
|
// Check the step is constant.
|
|
const SCEV *Step = AddRec->getStepRecurrence(*SE);
|
|
// Calculate the pointer stride and check if it is consecutive.
|
|
const SCEVConstant *C = dyn_cast<SCEVConstant>(Step);
|
|
if (!C)
|
|
return true;
|
|
|
|
const APInt &APStepVal = C->getValue()->getValue();
|
|
|
|
// Huge step value - give up.
|
|
if (APStepVal.getBitWidth() > 64)
|
|
return true;
|
|
|
|
int64_t StepVal = APStepVal.getSExtValue();
|
|
|
|
return StepVal > MaxMergeDistance;
|
|
}
|
|
|
|
static bool isStrideMul(Instruction *I, LoopVectorizationLegality *Legal) {
|
|
if (Legal->hasStride(I->getOperand(0)) || Legal->hasStride(I->getOperand(1)))
|
|
return true;
|
|
return false;
|
|
}
|
|
|
|
unsigned
|
|
LoopVectorizationCostModel::getInstructionCost(Instruction *I, unsigned VF) {
|
|
// If we know that this instruction will remain uniform, check the cost of
|
|
// the scalar version.
|
|
if (Legal->isUniformAfterVectorization(I))
|
|
VF = 1;
|
|
|
|
Type *RetTy = I->getType();
|
|
Type *VectorTy = ToVectorTy(RetTy, VF);
|
|
|
|
// TODO: We need to estimate the cost of intrinsic calls.
|
|
switch (I->getOpcode()) {
|
|
case Instruction::GetElementPtr:
|
|
// We mark this instruction as zero-cost because the cost of GEPs in
|
|
// vectorized code depends on whether the corresponding memory instruction
|
|
// is scalarized or not. Therefore, we handle GEPs with the memory
|
|
// instruction cost.
|
|
return 0;
|
|
case Instruction::Br: {
|
|
return TTI.getCFInstrCost(I->getOpcode());
|
|
}
|
|
case Instruction::PHI:
|
|
//TODO: IF-converted IFs become selects.
|
|
return 0;
|
|
case Instruction::Add:
|
|
case Instruction::FAdd:
|
|
case Instruction::Sub:
|
|
case Instruction::FSub:
|
|
case Instruction::Mul:
|
|
case Instruction::FMul:
|
|
case Instruction::UDiv:
|
|
case Instruction::SDiv:
|
|
case Instruction::FDiv:
|
|
case Instruction::URem:
|
|
case Instruction::SRem:
|
|
case Instruction::FRem:
|
|
case Instruction::Shl:
|
|
case Instruction::LShr:
|
|
case Instruction::AShr:
|
|
case Instruction::And:
|
|
case Instruction::Or:
|
|
case Instruction::Xor: {
|
|
// Since we will replace the stride by 1 the multiplication should go away.
|
|
if (I->getOpcode() == Instruction::Mul && isStrideMul(I, Legal))
|
|
return 0;
|
|
// Certain instructions can be cheaper to vectorize if they have a constant
|
|
// second vector operand. One example of this are shifts on x86.
|
|
TargetTransformInfo::OperandValueKind Op1VK =
|
|
TargetTransformInfo::OK_AnyValue;
|
|
TargetTransformInfo::OperandValueKind Op2VK =
|
|
TargetTransformInfo::OK_AnyValue;
|
|
TargetTransformInfo::OperandValueProperties Op1VP =
|
|
TargetTransformInfo::OP_None;
|
|
TargetTransformInfo::OperandValueProperties Op2VP =
|
|
TargetTransformInfo::OP_None;
|
|
Value *Op2 = I->getOperand(1);
|
|
|
|
// Check for a splat of a constant or for a non uniform vector of constants.
|
|
if (isa<ConstantInt>(Op2)) {
|
|
ConstantInt *CInt = cast<ConstantInt>(Op2);
|
|
if (CInt && CInt->getValue().isPowerOf2())
|
|
Op2VP = TargetTransformInfo::OP_PowerOf2;
|
|
Op2VK = TargetTransformInfo::OK_UniformConstantValue;
|
|
} else if (isa<ConstantVector>(Op2) || isa<ConstantDataVector>(Op2)) {
|
|
Op2VK = TargetTransformInfo::OK_NonUniformConstantValue;
|
|
Constant *SplatValue = cast<Constant>(Op2)->getSplatValue();
|
|
if (SplatValue) {
|
|
ConstantInt *CInt = dyn_cast<ConstantInt>(SplatValue);
|
|
if (CInt && CInt->getValue().isPowerOf2())
|
|
Op2VP = TargetTransformInfo::OP_PowerOf2;
|
|
Op2VK = TargetTransformInfo::OK_UniformConstantValue;
|
|
}
|
|
}
|
|
|
|
return TTI.getArithmeticInstrCost(I->getOpcode(), VectorTy, Op1VK, Op2VK,
|
|
Op1VP, Op2VP);
|
|
}
|
|
case Instruction::Select: {
|
|
SelectInst *SI = cast<SelectInst>(I);
|
|
const SCEV *CondSCEV = SE->getSCEV(SI->getCondition());
|
|
bool ScalarCond = (SE->isLoopInvariant(CondSCEV, TheLoop));
|
|
Type *CondTy = SI->getCondition()->getType();
|
|
if (!ScalarCond)
|
|
CondTy = VectorType::get(CondTy, VF);
|
|
|
|
return TTI.getCmpSelInstrCost(I->getOpcode(), VectorTy, CondTy);
|
|
}
|
|
case Instruction::ICmp:
|
|
case Instruction::FCmp: {
|
|
Type *ValTy = I->getOperand(0)->getType();
|
|
VectorTy = ToVectorTy(ValTy, VF);
|
|
return TTI.getCmpSelInstrCost(I->getOpcode(), VectorTy);
|
|
}
|
|
case Instruction::Store:
|
|
case Instruction::Load: {
|
|
StoreInst *SI = dyn_cast<StoreInst>(I);
|
|
LoadInst *LI = dyn_cast<LoadInst>(I);
|
|
Type *ValTy = (SI ? SI->getValueOperand()->getType() :
|
|
LI->getType());
|
|
VectorTy = ToVectorTy(ValTy, VF);
|
|
|
|
unsigned Alignment = SI ? SI->getAlignment() : LI->getAlignment();
|
|
unsigned AS = SI ? SI->getPointerAddressSpace() :
|
|
LI->getPointerAddressSpace();
|
|
Value *Ptr = SI ? SI->getPointerOperand() : LI->getPointerOperand();
|
|
// We add the cost of address computation here instead of with the gep
|
|
// instruction because only here we know whether the operation is
|
|
// scalarized.
|
|
if (VF == 1)
|
|
return TTI.getAddressComputationCost(VectorTy) +
|
|
TTI.getMemoryOpCost(I->getOpcode(), VectorTy, Alignment, AS);
|
|
|
|
// Scalarized loads/stores.
|
|
int ConsecutiveStride = Legal->isConsecutivePtr(Ptr);
|
|
bool Reverse = ConsecutiveStride < 0;
|
|
unsigned ScalarAllocatedSize = DL->getTypeAllocSize(ValTy);
|
|
unsigned VectorElementSize = DL->getTypeStoreSize(VectorTy)/VF;
|
|
if (!ConsecutiveStride || ScalarAllocatedSize != VectorElementSize) {
|
|
bool IsComplexComputation =
|
|
isLikelyComplexAddressComputation(Ptr, Legal, SE, TheLoop);
|
|
unsigned Cost = 0;
|
|
// The cost of extracting from the value vector and pointer vector.
|
|
Type *PtrTy = ToVectorTy(Ptr->getType(), VF);
|
|
for (unsigned i = 0; i < VF; ++i) {
|
|
// The cost of extracting the pointer operand.
|
|
Cost += TTI.getVectorInstrCost(Instruction::ExtractElement, PtrTy, i);
|
|
// In case of STORE, the cost of ExtractElement from the vector.
|
|
// In case of LOAD, the cost of InsertElement into the returned
|
|
// vector.
|
|
Cost += TTI.getVectorInstrCost(SI ? Instruction::ExtractElement :
|
|
Instruction::InsertElement,
|
|
VectorTy, i);
|
|
}
|
|
|
|
// The cost of the scalar loads/stores.
|
|
Cost += VF * TTI.getAddressComputationCost(PtrTy, IsComplexComputation);
|
|
Cost += VF * TTI.getMemoryOpCost(I->getOpcode(), ValTy->getScalarType(),
|
|
Alignment, AS);
|
|
return Cost;
|
|
}
|
|
|
|
// Wide load/stores.
|
|
unsigned Cost = TTI.getAddressComputationCost(VectorTy);
|
|
if (Legal->isMaskRequired(I))
|
|
Cost += TTI.getMaskedMemoryOpCost(I->getOpcode(), VectorTy, Alignment,
|
|
AS);
|
|
else
|
|
Cost += TTI.getMemoryOpCost(I->getOpcode(), VectorTy, Alignment, AS);
|
|
|
|
if (Reverse)
|
|
Cost += TTI.getShuffleCost(TargetTransformInfo::SK_Reverse,
|
|
VectorTy, 0);
|
|
return Cost;
|
|
}
|
|
case Instruction::ZExt:
|
|
case Instruction::SExt:
|
|
case Instruction::FPToUI:
|
|
case Instruction::FPToSI:
|
|
case Instruction::FPExt:
|
|
case Instruction::PtrToInt:
|
|
case Instruction::IntToPtr:
|
|
case Instruction::SIToFP:
|
|
case Instruction::UIToFP:
|
|
case Instruction::Trunc:
|
|
case Instruction::FPTrunc:
|
|
case Instruction::BitCast: {
|
|
// We optimize the truncation of induction variable.
|
|
// The cost of these is the same as the scalar operation.
|
|
if (I->getOpcode() == Instruction::Trunc &&
|
|
Legal->isInductionVariable(I->getOperand(0)))
|
|
return TTI.getCastInstrCost(I->getOpcode(), I->getType(),
|
|
I->getOperand(0)->getType());
|
|
|
|
Type *SrcVecTy = ToVectorTy(I->getOperand(0)->getType(), VF);
|
|
return TTI.getCastInstrCost(I->getOpcode(), VectorTy, SrcVecTy);
|
|
}
|
|
case Instruction::Call: {
|
|
CallInst *CI = cast<CallInst>(I);
|
|
Intrinsic::ID ID = getIntrinsicIDForCall(CI, TLI);
|
|
assert(ID && "Not an intrinsic call!");
|
|
Type *RetTy = ToVectorTy(CI->getType(), VF);
|
|
SmallVector<Type*, 4> Tys;
|
|
for (unsigned i = 0, ie = CI->getNumArgOperands(); i != ie; ++i)
|
|
Tys.push_back(ToVectorTy(CI->getArgOperand(i)->getType(), VF));
|
|
return TTI.getIntrinsicInstrCost(ID, RetTy, Tys);
|
|
}
|
|
default: {
|
|
// We are scalarizing the instruction. Return the cost of the scalar
|
|
// instruction, plus the cost of insert and extract into vector
|
|
// elements, times the vector width.
|
|
unsigned Cost = 0;
|
|
|
|
if (!RetTy->isVoidTy() && VF != 1) {
|
|
unsigned InsCost = TTI.getVectorInstrCost(Instruction::InsertElement,
|
|
VectorTy);
|
|
unsigned ExtCost = TTI.getVectorInstrCost(Instruction::ExtractElement,
|
|
VectorTy);
|
|
|
|
// The cost of inserting the results plus extracting each one of the
|
|
// operands.
|
|
Cost += VF * (InsCost + ExtCost * I->getNumOperands());
|
|
}
|
|
|
|
// The cost of executing VF copies of the scalar instruction. This opcode
|
|
// is unknown. Assume that it is the same as 'mul'.
|
|
Cost += VF * TTI.getArithmeticInstrCost(Instruction::Mul, VectorTy);
|
|
return Cost;
|
|
}
|
|
}// end of switch.
|
|
}
|
|
|
|
Type* LoopVectorizationCostModel::ToVectorTy(Type *Scalar, unsigned VF) {
|
|
if (Scalar->isVoidTy() || VF == 1)
|
|
return Scalar;
|
|
return VectorType::get(Scalar, VF);
|
|
}
|
|
|
|
char LoopVectorize::ID = 0;
|
|
static const char lv_name[] = "Loop Vectorization";
|
|
INITIALIZE_PASS_BEGIN(LoopVectorize, LV_NAME, lv_name, false, false)
|
|
INITIALIZE_PASS_DEPENDENCY(TargetTransformInfoWrapperPass)
|
|
INITIALIZE_AG_DEPENDENCY(AliasAnalysis)
|
|
INITIALIZE_PASS_DEPENDENCY(AssumptionCacheTracker)
|
|
INITIALIZE_PASS_DEPENDENCY(BlockFrequencyInfo)
|
|
INITIALIZE_PASS_DEPENDENCY(DominatorTreeWrapperPass)
|
|
INITIALIZE_PASS_DEPENDENCY(ScalarEvolution)
|
|
INITIALIZE_PASS_DEPENDENCY(LCSSA)
|
|
INITIALIZE_PASS_DEPENDENCY(LoopInfoWrapperPass)
|
|
INITIALIZE_PASS_DEPENDENCY(LoopSimplify)
|
|
INITIALIZE_PASS_END(LoopVectorize, LV_NAME, lv_name, false, false)
|
|
|
|
namespace llvm {
|
|
Pass *createLoopVectorizePass(bool NoUnrolling, bool AlwaysVectorize) {
|
|
return new LoopVectorize(NoUnrolling, AlwaysVectorize);
|
|
}
|
|
}
|
|
|
|
bool LoopVectorizationCostModel::isConsecutiveLoadOrStore(Instruction *Inst) {
|
|
// Check for a store.
|
|
if (StoreInst *ST = dyn_cast<StoreInst>(Inst))
|
|
return Legal->isConsecutivePtr(ST->getPointerOperand()) != 0;
|
|
|
|
// Check for a load.
|
|
if (LoadInst *LI = dyn_cast<LoadInst>(Inst))
|
|
return Legal->isConsecutivePtr(LI->getPointerOperand()) != 0;
|
|
|
|
return false;
|
|
}
|
|
|
|
|
|
void InnerLoopUnroller::scalarizeInstruction(Instruction *Instr,
|
|
bool IfPredicateStore) {
|
|
assert(!Instr->getType()->isAggregateType() && "Can't handle vectors");
|
|
// Holds vector parameters or scalars, in case of uniform vals.
|
|
SmallVector<VectorParts, 4> Params;
|
|
|
|
setDebugLocFromInst(Builder, Instr);
|
|
|
|
// Find all of the vectorized parameters.
|
|
for (unsigned op = 0, e = Instr->getNumOperands(); op != e; ++op) {
|
|
Value *SrcOp = Instr->getOperand(op);
|
|
|
|
// If we are accessing the old induction variable, use the new one.
|
|
if (SrcOp == OldInduction) {
|
|
Params.push_back(getVectorValue(SrcOp));
|
|
continue;
|
|
}
|
|
|
|
// Try using previously calculated values.
|
|
Instruction *SrcInst = dyn_cast<Instruction>(SrcOp);
|
|
|
|
// If the src is an instruction that appeared earlier in the basic block
|
|
// then it should already be vectorized.
|
|
if (SrcInst && OrigLoop->contains(SrcInst)) {
|
|
assert(WidenMap.has(SrcInst) && "Source operand is unavailable");
|
|
// The parameter is a vector value from earlier.
|
|
Params.push_back(WidenMap.get(SrcInst));
|
|
} else {
|
|
// The parameter is a scalar from outside the loop. Maybe even a constant.
|
|
VectorParts Scalars;
|
|
Scalars.append(UF, SrcOp);
|
|
Params.push_back(Scalars);
|
|
}
|
|
}
|
|
|
|
assert(Params.size() == Instr->getNumOperands() &&
|
|
"Invalid number of operands");
|
|
|
|
// Does this instruction return a value ?
|
|
bool IsVoidRetTy = Instr->getType()->isVoidTy();
|
|
|
|
Value *UndefVec = IsVoidRetTy ? nullptr :
|
|
UndefValue::get(Instr->getType());
|
|
// Create a new entry in the WidenMap and initialize it to Undef or Null.
|
|
VectorParts &VecResults = WidenMap.splat(Instr, UndefVec);
|
|
|
|
Instruction *InsertPt = Builder.GetInsertPoint();
|
|
BasicBlock *IfBlock = Builder.GetInsertBlock();
|
|
BasicBlock *CondBlock = nullptr;
|
|
|
|
VectorParts Cond;
|
|
Loop *VectorLp = nullptr;
|
|
if (IfPredicateStore) {
|
|
assert(Instr->getParent()->getSinglePredecessor() &&
|
|
"Only support single predecessor blocks");
|
|
Cond = createEdgeMask(Instr->getParent()->getSinglePredecessor(),
|
|
Instr->getParent());
|
|
VectorLp = LI->getLoopFor(IfBlock);
|
|
assert(VectorLp && "Must have a loop for this block");
|
|
}
|
|
|
|
// For each vector unroll 'part':
|
|
for (unsigned Part = 0; Part < UF; ++Part) {
|
|
// For each scalar that we create:
|
|
|
|
// Start an "if (pred) a[i] = ..." block.
|
|
Value *Cmp = nullptr;
|
|
if (IfPredicateStore) {
|
|
if (Cond[Part]->getType()->isVectorTy())
|
|
Cond[Part] =
|
|
Builder.CreateExtractElement(Cond[Part], Builder.getInt32(0));
|
|
Cmp = Builder.CreateICmp(ICmpInst::ICMP_EQ, Cond[Part],
|
|
ConstantInt::get(Cond[Part]->getType(), 1));
|
|
CondBlock = IfBlock->splitBasicBlock(InsertPt, "cond.store");
|
|
LoopVectorBody.push_back(CondBlock);
|
|
VectorLp->addBasicBlockToLoop(CondBlock, *LI);
|
|
// Update Builder with newly created basic block.
|
|
Builder.SetInsertPoint(InsertPt);
|
|
}
|
|
|
|
Instruction *Cloned = Instr->clone();
|
|
if (!IsVoidRetTy)
|
|
Cloned->setName(Instr->getName() + ".cloned");
|
|
// Replace the operands of the cloned instructions with extracted scalars.
|
|
for (unsigned op = 0, e = Instr->getNumOperands(); op != e; ++op) {
|
|
Value *Op = Params[op][Part];
|
|
Cloned->setOperand(op, Op);
|
|
}
|
|
|
|
// Place the cloned scalar in the new loop.
|
|
Builder.Insert(Cloned);
|
|
|
|
// If the original scalar returns a value we need to place it in a vector
|
|
// so that future users will be able to use it.
|
|
if (!IsVoidRetTy)
|
|
VecResults[Part] = Cloned;
|
|
|
|
// End if-block.
|
|
if (IfPredicateStore) {
|
|
BasicBlock *NewIfBlock = CondBlock->splitBasicBlock(InsertPt, "else");
|
|
LoopVectorBody.push_back(NewIfBlock);
|
|
VectorLp->addBasicBlockToLoop(NewIfBlock, *LI);
|
|
Builder.SetInsertPoint(InsertPt);
|
|
Instruction *OldBr = IfBlock->getTerminator();
|
|
BranchInst::Create(CondBlock, NewIfBlock, Cmp, OldBr);
|
|
OldBr->eraseFromParent();
|
|
IfBlock = NewIfBlock;
|
|
}
|
|
}
|
|
}
|
|
|
|
void InnerLoopUnroller::vectorizeMemoryInstruction(Instruction *Instr) {
|
|
StoreInst *SI = dyn_cast<StoreInst>(Instr);
|
|
bool IfPredicateStore = (SI && Legal->blockNeedsPredication(SI->getParent()));
|
|
|
|
return scalarizeInstruction(Instr, IfPredicateStore);
|
|
}
|
|
|
|
Value *InnerLoopUnroller::reverseVector(Value *Vec) {
|
|
return Vec;
|
|
}
|
|
|
|
Value *InnerLoopUnroller::getBroadcastInstrs(Value *V) {
|
|
return V;
|
|
}
|
|
|
|
Value *InnerLoopUnroller::getStepVector(Value *Val, int StartIdx, Value *Step) {
|
|
// When unrolling and the VF is 1, we only need to add a simple scalar.
|
|
Type *ITy = Val->getType();
|
|
assert(!ITy->isVectorTy() && "Val must be a scalar");
|
|
Constant *C = ConstantInt::get(ITy, StartIdx);
|
|
return Builder.CreateAdd(Val, Builder.CreateMul(C, Step), "induction");
|
|
}
|