mirror of
https://github.com/c64scene-ar/llvm-6502.git
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git-svn-id: https://llvm.org/svn/llvm-project/llvm/trunk@185263 91177308-0d34-0410-b5e6-96231b3b80d8
4604 lines
171 KiB
C++
4604 lines
171 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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#define LV_NAME "loop-vectorize"
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#define DEBUG_TYPE LV_NAME
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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/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/StringExtras.h"
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#include "llvm/Analysis/AliasAnalysis.h"
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#include "llvm/Analysis/Dominators.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/Analysis/Verifier.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/DerivedTypes.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/Type.h"
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#include "llvm/IR/Value.h"
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#include "llvm/Pass.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/PatternMatch.h"
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#include "llvm/Support/raw_ostream.h"
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#include "llvm/Support/ValueHandle.h"
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#include "llvm/Target/TargetLibraryInfo.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 <algorithm>
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#include <map>
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using namespace llvm;
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using namespace llvm::PatternMatch;
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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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VectorizationUnroll("force-vector-unroll", cl::init(0), cl::Hidden,
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cl::desc("Sets the vectorization unroll 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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/// 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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/// Maximum vectorization unroll count.
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static const unsigned MaxUnrollFactor = 16;
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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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/// 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, 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()), Induction(0),
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OldInduction(0), WidenMap(UnrollFactor) {}
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// Perform the actual loop widening (vectorization).
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void vectorize(LoopVectorizationLegality *Legal) {
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// Create a new empty loop. Unlink the old loop and connect the new one.
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createEmptyLoop(Legal);
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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(Legal);
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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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private:
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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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/// Add code that checks at runtime if the accessed arrays overlap.
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/// Returns the comparator value or NULL if no check is needed.
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Instruction *addRuntimeCheck(LoopVectorizationLegality *Legal,
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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(LoopVectorizationLegality *Legal);
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/// Copy and widen the instructions from the old loop.
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void vectorizeLoop(LoopVectorizationLegality *Legal);
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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(LoopVectorizationLegality *Legal, BasicBlock *BB,
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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.
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void scalarizeInstruction(Instruction *Instr);
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/// Vectorize Load and Store instructions,
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void vectorizeMemoryInstruction(Instruction *Instr,
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LoopVectorizationLegality *Legal);
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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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Value *getBroadcastInstrs(Value *V);
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/// This function adds 0, 1, 2 ... to each vector element, starting at zero.
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/// If Negate is set then negative numbers are added e.g. (0, -1, -2, ...).
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/// The sequence starts at StartIndex.
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Value *getConsecutiveVector(Value* Val, int StartIdx, bool Negate);
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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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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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/// Data Layout.
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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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/// 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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BasicBlock *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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};
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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;
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if (I->getDebugLoc() != Empty)
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return I;
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for (User::op_iterator OI = I->op_begin(), OE = I->op_end(); OI != OE; ++OI) {
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if (Instruction *OpInst = dyn_cast<Instruction>(*OI))
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if (OpInst->getDebugLoc() != Empty)
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return OpInst;
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}
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return I;
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}
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/// \brief Set the debug location in the builder using the debug location in the
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/// instruction.
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static void setDebugLocFromInst(IRBuilder<> &B, const Value *Ptr) {
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if (const Instruction *Inst = dyn_cast_or_null<Instruction>(Ptr))
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B.SetCurrentDebugLocation(Inst->getDebugLoc());
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else
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B.SetCurrentDebugLocation(DebugLoc());
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}
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/// LoopVectorizationLegality checks if it is legal to vectorize a loop, and
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/// to what vectorization factor.
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/// This class does not look at the profitability of vectorization, only the
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/// legality. This class has two main kinds of checks:
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/// * Memory checks - The code in canVectorizeMemory checks if vectorization
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/// will change the order of memory accesses in a way that will change the
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/// correctness of the program.
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/// * Scalars checks - The code in canVectorizeInstrs and canVectorizeMemory
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/// checks for a number of different conditions, such as the availability of a
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/// single induction variable, that all types are supported and vectorize-able,
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/// etc. This code reflects the capabilities of InnerLoopVectorizer.
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/// This class is also used by InnerLoopVectorizer for identifying
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/// induction variable and the different reduction variables.
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class LoopVectorizationLegality {
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public:
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LoopVectorizationLegality(Loop *L, ScalarEvolution *SE, DataLayout *DL,
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DominatorTree *DT, TargetLibraryInfo *TLI)
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: TheLoop(L), SE(SE), DL(DL), DT(DT), TLI(TLI),
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Induction(0), WidestIndTy(0), HasFunNoNaNAttr(false),
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MaxSafeDepDistBytes(-1U) {}
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/// This enum represents the kinds of reductions that we support.
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enum ReductionKind {
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RK_NoReduction, ///< Not a reduction.
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RK_IntegerAdd, ///< Sum of integers.
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RK_IntegerMult, ///< Product of integers.
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RK_IntegerOr, ///< Bitwise or logical OR of numbers.
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RK_IntegerAnd, ///< Bitwise or logical AND of numbers.
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RK_IntegerXor, ///< Bitwise or logical XOR of numbers.
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RK_IntegerMinMax, ///< Min/max implemented in terms of select(cmp()).
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RK_FloatAdd, ///< Sum of floats.
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RK_FloatMult, ///< Product of floats.
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RK_FloatMinMax ///< Min/max implemented in terms of select(cmp()).
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};
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/// This enum represents the kinds of inductions that we support.
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enum InductionKind {
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IK_NoInduction, ///< Not an induction variable.
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IK_IntInduction, ///< Integer induction variable. Step = 1.
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IK_ReverseIntInduction, ///< Reverse int induction variable. Step = -1.
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IK_PtrInduction, ///< Pointer induction var. Step = sizeof(elem).
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IK_ReversePtrInduction ///< Reverse ptr indvar. Step = - sizeof(elem).
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};
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// This enum represents the kind of minmax reduction.
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enum MinMaxReductionKind {
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MRK_Invalid,
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MRK_UIntMin,
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MRK_UIntMax,
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MRK_SIntMin,
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MRK_SIntMax,
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MRK_FloatMin,
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MRK_FloatMax
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};
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/// This POD struct holds information about reduction variables.
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struct ReductionDescriptor {
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ReductionDescriptor() : StartValue(0), LoopExitInstr(0),
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Kind(RK_NoReduction), MinMaxKind(MRK_Invalid) {}
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ReductionDescriptor(Value *Start, Instruction *Exit, ReductionKind K,
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MinMaxReductionKind MK)
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: StartValue(Start), LoopExitInstr(Exit), Kind(K), MinMaxKind(MK) {}
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// The starting value of the reduction.
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// It does not have to be zero!
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TrackingVH<Value> StartValue;
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// The instruction who's value is used outside the loop.
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Instruction *LoopExitInstr;
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// The kind of the reduction.
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ReductionKind Kind;
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// If this a min/max reduction the kind of reduction.
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MinMaxReductionKind MinMaxKind;
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};
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/// This POD struct holds information about a potential reduction operation.
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struct ReductionInstDesc {
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ReductionInstDesc(bool IsRedux, Instruction *I) :
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IsReduction(IsRedux), PatternLastInst(I), MinMaxKind(MRK_Invalid) {}
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ReductionInstDesc(Instruction *I, MinMaxReductionKind K) :
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IsReduction(true), PatternLastInst(I), MinMaxKind(K) {}
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// Is this instruction a reduction candidate.
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bool IsReduction;
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// The last instruction in a min/max pattern (select of the select(icmp())
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// pattern), or the current reduction instruction otherwise.
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Instruction *PatternLastInst;
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// If this is a min/max pattern the comparison predicate.
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MinMaxReductionKind MinMaxKind;
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};
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// This POD struct holds information about the memory runtime legality
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// check that a group of pointers do not overlap.
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struct RuntimePointerCheck {
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RuntimePointerCheck() : Need(false) {}
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/// Reset the state of the pointer runtime information.
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void reset() {
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Need = false;
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Pointers.clear();
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Starts.clear();
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Ends.clear();
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}
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/// Insert a pointer and calculate the start and end SCEVs.
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void insert(ScalarEvolution *SE, Loop *Lp, Value *Ptr, bool WritePtr,
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unsigned DepSetId);
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/// This flag indicates if we need to add the runtime check.
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bool Need;
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/// Holds the pointers that we need to check.
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SmallVector<TrackingVH<Value>, 2> Pointers;
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/// Holds the pointer value at the beginning of the loop.
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SmallVector<const SCEV*, 2> Starts;
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/// Holds the pointer value at the end of the loop.
|
|
SmallVector<const SCEV*, 2> Ends;
|
|
/// Holds the information if this pointer is used for writing to memory.
|
|
SmallVector<bool, 2> IsWritePtr;
|
|
/// Holds the id of the set of pointers that could be dependent because of a
|
|
/// shared underlying object.
|
|
SmallVector<unsigned, 2> DependencySetId;
|
|
};
|
|
|
|
/// A POD for saving information about induction variables.
|
|
struct InductionInfo {
|
|
InductionInfo(Value *Start, InductionKind K) : StartValue(Start), IK(K) {}
|
|
InductionInfo() : StartValue(0), IK(IK_NoInduction) {}
|
|
/// Start value.
|
|
TrackingVH<Value> StartValue;
|
|
/// Induction kind.
|
|
InductionKind IK;
|
|
};
|
|
|
|
/// 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.
|
|
RuntimePointerCheck *getRuntimePointerCheck() { return &PtrRtCheck; }
|
|
|
|
/// This function returns the identity element (or neutral element) for
|
|
/// the operation K.
|
|
static Constant *getReductionIdentity(ReductionKind K, Type *Tp);
|
|
|
|
unsigned getMaxSafeDepDistBytes() { return MaxSafeDepDistBytes; }
|
|
|
|
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, SmallPtrSet<Value *, 8>& 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. This function may return NoInduction
|
|
/// if the PHI is not an induction variable.
|
|
InductionKind isInductionVariable(PHINode *Phi);
|
|
|
|
/// The loop that we evaluate.
|
|
Loop *TheLoop;
|
|
/// Scev analysis.
|
|
ScalarEvolution *SE;
|
|
/// DataLayout analysis.
|
|
DataLayout *DL;
|
|
/// Dominators.
|
|
DominatorTree *DT;
|
|
/// Target Library Info.
|
|
TargetLibraryInfo *TLI;
|
|
|
|
// --- 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;
|
|
/// We need to check that all of the pointers in this list are disjoint
|
|
/// at runtime.
|
|
RuntimePointerCheck PtrRtCheck;
|
|
/// Can we assume the absence of NaNs.
|
|
bool HasFunNoNaNAttr;
|
|
|
|
unsigned MaxSafeDepDistBytes;
|
|
};
|
|
|
|
/// 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,
|
|
DataLayout *DL, const TargetLibraryInfo *TLI)
|
|
: TheLoop(L), SE(SE), LI(LI), Legal(Legal), TTI(TTI), DL(DL), TLI(TLI) {}
|
|
|
|
/// 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,
|
|
unsigned UserVF);
|
|
|
|
/// \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 UserUF, 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);
|
|
|
|
/// 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.
|
|
DataLayout *DL;
|
|
/// Target Library Info.
|
|
const TargetLibraryInfo *TLI;
|
|
};
|
|
|
|
/// Utility class for getting and setting loop vectorizer hints in the form
|
|
/// of loop metadata.
|
|
struct LoopVectorizeHints {
|
|
/// Vectorization width.
|
|
unsigned Width;
|
|
/// Vectorization unroll factor.
|
|
unsigned Unroll;
|
|
|
|
LoopVectorizeHints(const Loop *L)
|
|
: Width(VectorizationFactor)
|
|
, Unroll(VectorizationUnroll)
|
|
, LoopID(L->getLoopID()) {
|
|
getHints(L);
|
|
// The command line options override any loop metadata except for when
|
|
// width == 1 which is used to indicate the loop is already vectorized.
|
|
if (VectorizationFactor.getNumOccurrences() > 0 && Width != 1)
|
|
Width = VectorizationFactor;
|
|
if (VectorizationUnroll.getNumOccurrences() > 0)
|
|
Unroll = VectorizationUnroll;
|
|
}
|
|
|
|
/// Return the loop vectorizer metadata prefix.
|
|
static StringRef Prefix() { return "llvm.vectorizer."; }
|
|
|
|
MDNode *createHint(LLVMContext &Context, StringRef Name, unsigned V) {
|
|
SmallVector<Value*, 2> Vals;
|
|
Vals.push_back(MDString::get(Context, Name));
|
|
Vals.push_back(ConstantInt::get(Type::getInt32Ty(Context), V));
|
|
return MDNode::get(Context, Vals);
|
|
}
|
|
|
|
/// Mark the loop L as already vectorized by setting the width to 1.
|
|
void setAlreadyVectorized(Loop *L) {
|
|
LLVMContext &Context = L->getHeader()->getContext();
|
|
|
|
Width = 1;
|
|
|
|
// Create a new loop id with one more operand for the already_vectorized
|
|
// hint. If the loop already has a loop id then copy the existing operands.
|
|
SmallVector<Value*, 4> Vals(1);
|
|
if (LoopID)
|
|
for (unsigned i = 1, ie = LoopID->getNumOperands(); i < ie; ++i)
|
|
Vals.push_back(LoopID->getOperand(i));
|
|
|
|
Vals.push_back(createHint(Context, Twine(Prefix(), "width").str(), Width));
|
|
|
|
MDNode *NewLoopID = MDNode::get(Context, Vals);
|
|
// Set operand 0 to refer to the loop id itself.
|
|
NewLoopID->replaceOperandWith(0, NewLoopID);
|
|
|
|
L->setLoopID(NewLoopID);
|
|
if (LoopID)
|
|
LoopID->replaceAllUsesWith(NewLoopID);
|
|
|
|
LoopID = NewLoopID;
|
|
}
|
|
|
|
private:
|
|
MDNode *LoopID;
|
|
|
|
/// Find hints specified in the loop metadata.
|
|
void getHints(const Loop *L) {
|
|
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 = 0;
|
|
SmallVector<Value*, 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 vectorizer prefix.
|
|
StringRef Hint = S->getString();
|
|
if (!Hint.startswith(Prefix()))
|
|
continue;
|
|
// Remove the prefix.
|
|
Hint = Hint.substr(Prefix().size(), StringRef::npos);
|
|
|
|
if (Args.size() == 1)
|
|
getHint(Hint, Args[0]);
|
|
}
|
|
}
|
|
|
|
// Check string hint with one operand.
|
|
void getHint(StringRef Hint, Value *Arg) {
|
|
const ConstantInt *C = dyn_cast<ConstantInt>(Arg);
|
|
if (!C) return;
|
|
unsigned Val = C->getZExtValue();
|
|
|
|
if (Hint == "width") {
|
|
assert(isPowerOf2_32(Val) && Val <= MaxVectorWidth &&
|
|
"Invalid width metadata");
|
|
Width = Val;
|
|
} else if (Hint == "unroll") {
|
|
assert(isPowerOf2_32(Val) && Val <= MaxUnrollFactor &&
|
|
"Invalid unroll metadata");
|
|
Unroll = Val;
|
|
} else
|
|
DEBUG(dbgs() << "LV: ignoring unknown hint " << Hint);
|
|
}
|
|
};
|
|
|
|
/// The LoopVectorize Pass.
|
|
struct LoopVectorize : public LoopPass {
|
|
/// Pass identification, replacement for typeid
|
|
static char ID;
|
|
|
|
explicit LoopVectorize() : LoopPass(ID) {
|
|
initializeLoopVectorizePass(*PassRegistry::getPassRegistry());
|
|
}
|
|
|
|
ScalarEvolution *SE;
|
|
DataLayout *DL;
|
|
LoopInfo *LI;
|
|
TargetTransformInfo *TTI;
|
|
DominatorTree *DT;
|
|
TargetLibraryInfo *TLI;
|
|
|
|
virtual bool runOnLoop(Loop *L, LPPassManager &LPM) {
|
|
// We only vectorize innermost loops.
|
|
if (!L->empty())
|
|
return false;
|
|
|
|
SE = &getAnalysis<ScalarEvolution>();
|
|
DL = getAnalysisIfAvailable<DataLayout>();
|
|
LI = &getAnalysis<LoopInfo>();
|
|
TTI = &getAnalysis<TargetTransformInfo>();
|
|
DT = &getAnalysis<DominatorTree>();
|
|
TLI = getAnalysisIfAvailable<TargetLibraryInfo>();
|
|
|
|
if (DL == NULL) {
|
|
DEBUG(dbgs() << "LV: Not vectorizing because of missing data layout");
|
|
return false;
|
|
}
|
|
|
|
DEBUG(dbgs() << "LV: Checking a loop in \"" <<
|
|
L->getHeader()->getParent()->getName() << "\"\n");
|
|
|
|
LoopVectorizeHints Hints(L);
|
|
|
|
if (Hints.Width == 1) {
|
|
DEBUG(dbgs() << "LV: Not vectorizing.\n");
|
|
return false;
|
|
}
|
|
|
|
// Check if it is legal to vectorize the loop.
|
|
LoopVectorizationLegality LVL(L, SE, DL, DT, TLI);
|
|
if (!LVL.canVectorize()) {
|
|
DEBUG(dbgs() << "LV: Not vectorizing.\n");
|
|
return false;
|
|
}
|
|
|
|
// Use the cost model.
|
|
LoopVectorizationCostModel CM(L, SE, LI, &LVL, *TTI, DL, TLI);
|
|
|
|
// Check the function attributes to find out if this function should be
|
|
// optimized for size.
|
|
Function *F = L->getHeader()->getParent();
|
|
Attribute::AttrKind SzAttr = Attribute::OptimizeForSize;
|
|
Attribute::AttrKind FlAttr = Attribute::NoImplicitFloat;
|
|
unsigned FnIndex = AttributeSet::FunctionIndex;
|
|
bool OptForSize = F->getAttributes().hasAttribute(FnIndex, SzAttr);
|
|
bool NoFloat = F->getAttributes().hasAttribute(FnIndex, FlAttr);
|
|
|
|
if (NoFloat) {
|
|
DEBUG(dbgs() << "LV: Can't vectorize when the NoImplicitFloat"
|
|
"attribute is used.\n");
|
|
return false;
|
|
}
|
|
|
|
// Select the optimal vectorization factor.
|
|
LoopVectorizationCostModel::VectorizationFactor VF;
|
|
VF = CM.selectVectorizationFactor(OptForSize, Hints.Width);
|
|
// Select the unroll factor.
|
|
unsigned UF = CM.selectUnrollFactor(OptForSize, Hints.Unroll, VF.Width,
|
|
VF.Cost);
|
|
|
|
if (VF.Width == 1) {
|
|
DEBUG(dbgs() << "LV: Vectorization is possible but not beneficial.\n");
|
|
return false;
|
|
}
|
|
|
|
DEBUG(dbgs() << "LV: Found a vectorizable loop ("<< VF.Width << ") in "<<
|
|
F->getParent()->getModuleIdentifier()<<"\n");
|
|
DEBUG(dbgs() << "LV: Unroll Factor is " << UF << "\n");
|
|
|
|
// 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);
|
|
|
|
// Mark the loop as already vectorized to avoid vectorizing again.
|
|
Hints.setAlreadyVectorized(L);
|
|
|
|
DEBUG(verifyFunction(*L->getHeader()->getParent()));
|
|
return true;
|
|
}
|
|
|
|
virtual void getAnalysisUsage(AnalysisUsage &AU) const {
|
|
LoopPass::getAnalysisUsage(AU);
|
|
AU.addRequiredID(LoopSimplifyID);
|
|
AU.addRequiredID(LCSSAID);
|
|
AU.addRequired<DominatorTree>();
|
|
AU.addRequired<LoopInfo>();
|
|
AU.addRequired<ScalarEvolution>();
|
|
AU.addRequired<TargetTransformInfo>();
|
|
AU.addPreserved<LoopInfo>();
|
|
AU.addPreserved<DominatorTree>();
|
|
}
|
|
|
|
};
|
|
|
|
} // end anonymous namespace
|
|
|
|
//===----------------------------------------------------------------------===//
|
|
// Implementation of LoopVectorizationLegality, InnerLoopVectorizer and
|
|
// LoopVectorizationCostModel.
|
|
//===----------------------------------------------------------------------===//
|
|
|
|
void
|
|
LoopVectorizationLegality::RuntimePointerCheck::insert(ScalarEvolution *SE,
|
|
Loop *Lp, Value *Ptr,
|
|
bool WritePtr,
|
|
unsigned DepSetId) {
|
|
const SCEV *Sc = SE->getSCEV(Ptr);
|
|
const SCEVAddRecExpr *AR = dyn_cast<SCEVAddRecExpr>(Sc);
|
|
assert(AR && "Invalid addrec expression");
|
|
const SCEV *Ex = SE->getBackedgeTakenCount(Lp);
|
|
const SCEV *ScEnd = AR->evaluateAtIteration(Ex, *SE);
|
|
Pointers.push_back(Ptr);
|
|
Starts.push_back(AR->getStart());
|
|
Ends.push_back(ScEnd);
|
|
IsWritePtr.push_back(WritePtr);
|
|
DependencySetId.push_back(DepSetId);
|
|
}
|
|
|
|
Value *InnerLoopVectorizer::getBroadcastInstrs(Value *V) {
|
|
// Save the current insertion location.
|
|
Instruction *Loc = Builder.GetInsertPoint();
|
|
|
|
// We need to place the broadcast of invariant variables outside the loop.
|
|
Instruction *Instr = dyn_cast<Instruction>(V);
|
|
bool NewInstr = (Instr && Instr->getParent() == LoopVectorBody);
|
|
bool Invariant = OrigLoop->isLoopInvariant(V) && !NewInstr;
|
|
|
|
// Place the code for broadcasting invariant variables in the new preheader.
|
|
if (Invariant)
|
|
Builder.SetInsertPoint(LoopVectorPreHeader->getTerminator());
|
|
|
|
// Broadcast the scalar into all locations in the vector.
|
|
Value *Shuf = Builder.CreateVectorSplat(VF, V, "broadcast");
|
|
|
|
// Restore the builder insertion point.
|
|
if (Invariant)
|
|
Builder.SetInsertPoint(Loc);
|
|
|
|
return Shuf;
|
|
}
|
|
|
|
Value *InnerLoopVectorizer::getConsecutiveVector(Value* Val, int StartIdx,
|
|
bool Negate) {
|
|
assert(Val->getType()->isVectorTy() && "Must be a vector");
|
|
assert(Val->getType()->getScalarType()->isIntegerTy() &&
|
|
"Elem must be an integer");
|
|
// 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) {
|
|
int64_t Idx = Negate ? (-i) : i;
|
|
Indices.push_back(ConstantInt::get(ITy, StartIdx + Idx, Negate));
|
|
}
|
|
|
|
// Add the consecutive indices to the vector value.
|
|
Constant *Cv = ConstantVector::get(Indices);
|
|
assert(Cv->getType() == Val->getType() && "Invalid consecutive vec");
|
|
return Builder.CreateAdd(Val, Cv, "induction");
|
|
}
|
|
|
|
int LoopVectorizationLegality::isConsecutivePtr(Value *Ptr) {
|
|
assert(Ptr->getType()->isPointerTy() && "Unexpected non ptr");
|
|
// Make sure that the pointer does not point to structs.
|
|
if (cast<PointerType>(Ptr->getType())->getElementType()->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];
|
|
if (IK_PtrInduction == II.IK)
|
|
return 1;
|
|
else if (IK_ReversePtrInduction == II.IK)
|
|
return -1;
|
|
}
|
|
|
|
GetElementPtrInst *Gep = dyn_cast_or_null<GetElementPtrInst>(Ptr);
|
|
if (!Gep)
|
|
return 0;
|
|
|
|
unsigned NumOperands = Gep->getNumOperands();
|
|
Value *LastIndex = Gep->getOperand(NumOperands - 1);
|
|
|
|
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];
|
|
if (IK_PtrInduction == II.IK)
|
|
return 1;
|
|
else if (IK_ReversePtrInduction == II.IK)
|
|
return -1;
|
|
}
|
|
|
|
// Check that all of the gep indices are uniform except for the last.
|
|
for (unsigned i = 0; i < NumOperands - 1; ++i)
|
|
if (!SE->isLoopInvariant(SE->getSCEV(Gep->getOperand(i)), TheLoop))
|
|
return 0;
|
|
|
|
// We can emit wide load/stores only if the last index is the induction
|
|
// variable.
|
|
const SCEV *Last = SE->getSCEV(LastIndex);
|
|
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 (SE->isLoopInvariant(SE->getSCEV(V), TheLoop));
|
|
}
|
|
|
|
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 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,
|
|
LoopVectorizationLegality *Legal) {
|
|
// 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();
|
|
unsigned AddressSpace = Ptr->getType()->getPointerAddressSpace();
|
|
unsigned ScalarAllocatedSize = DL->getTypeAllocSize(ScalarDataTy);
|
|
unsigned VectorElementSize = DL->getTypeStoreSize(DataTy)/VF;
|
|
|
|
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 LastOperand = NumOperands - 1;
|
|
// 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 == LastOperand ||
|
|
(GepOperandInst && OrigLoop->contains(GepOperandInst))) {
|
|
assert((i == LastOperand ||
|
|
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);
|
|
}
|
|
|
|
// 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));
|
|
}
|
|
|
|
Value *VecPtr = Builder.CreateBitCast(PartPtr, DataTy->getPointerTo(AddressSpace));
|
|
Builder.CreateStore(StoredVal[Part], VecPtr)->setAlignment(Alignment);
|
|
}
|
|
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 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));
|
|
}
|
|
|
|
Value *VecPtr = Builder.CreateBitCast(PartPtr, DataTy->getPointerTo(AddressSpace));
|
|
Value *LI = Builder.CreateLoad(VecPtr, "wide.load");
|
|
cast<LoadInst>(LI)->setAlignment(Alignment);
|
|
Entry[Part] = Reverse ? reverseVector(LI) : LI;
|
|
}
|
|
}
|
|
|
|
void InnerLoopVectorizer::scalarizeInstruction(Instruction *Instr) {
|
|
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 ? 0 :
|
|
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);
|
|
|
|
// 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) {
|
|
Instruction *Cloned = Instr->clone();
|
|
if (!IsVoidRetTy)
|
|
Cloned->setName(Instr->getName() + ".cloned");
|
|
// Replace the operands of the cloned instrucions 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));
|
|
}
|
|
}
|
|
}
|
|
|
|
Instruction *
|
|
InnerLoopVectorizer::addRuntimeCheck(LoopVectorizationLegality *Legal,
|
|
Instruction *Loc) {
|
|
LoopVectorizationLegality::RuntimePointerCheck *PtrRtCheck =
|
|
Legal->getRuntimePointerCheck();
|
|
|
|
if (!PtrRtCheck->Need)
|
|
return NULL;
|
|
|
|
unsigned NumPointers = PtrRtCheck->Pointers.size();
|
|
SmallVector<TrackingVH<Value> , 2> Starts;
|
|
SmallVector<TrackingVH<Value> , 2> Ends;
|
|
|
|
SCEVExpander Exp(*SE, "induction");
|
|
|
|
// Use this type for pointer arithmetic.
|
|
Type* PtrArithTy = Type::getInt8PtrTy(Loc->getContext(), 0);
|
|
|
|
for (unsigned i = 0; i < NumPointers; ++i) {
|
|
Value *Ptr = PtrRtCheck->Pointers[i];
|
|
const SCEV *Sc = SE->getSCEV(Ptr);
|
|
|
|
if (SE->isLoopInvariant(Sc, OrigLoop)) {
|
|
DEBUG(dbgs() << "LV: Adding RT check for a loop invariant ptr:" <<
|
|
*Ptr <<"\n");
|
|
Starts.push_back(Ptr);
|
|
Ends.push_back(Ptr);
|
|
} else {
|
|
DEBUG(dbgs() << "LV: Adding RT check for range:" << *Ptr <<"\n");
|
|
|
|
Value *Start = Exp.expandCodeFor(PtrRtCheck->Starts[i], PtrArithTy, Loc);
|
|
Value *End = Exp.expandCodeFor(PtrRtCheck->Ends[i], PtrArithTy, Loc);
|
|
Starts.push_back(Start);
|
|
Ends.push_back(End);
|
|
}
|
|
}
|
|
|
|
IRBuilder<> ChkBuilder(Loc);
|
|
// Our instructions might fold to a constant.
|
|
Value *MemoryRuntimeCheck = 0;
|
|
for (unsigned i = 0; i < NumPointers; ++i) {
|
|
for (unsigned j = i+1; j < NumPointers; ++j) {
|
|
// No need to check if two readonly pointers intersect.
|
|
if (!PtrRtCheck->IsWritePtr[i] && !PtrRtCheck->IsWritePtr[j])
|
|
continue;
|
|
|
|
// Only need to check pointers between two different dependency sets.
|
|
if (PtrRtCheck->DependencySetId[i] == PtrRtCheck->DependencySetId[j])
|
|
continue;
|
|
|
|
Value *Start0 = ChkBuilder.CreateBitCast(Starts[i], PtrArithTy, "bc");
|
|
Value *Start1 = ChkBuilder.CreateBitCast(Starts[j], PtrArithTy, "bc");
|
|
Value *End0 = ChkBuilder.CreateBitCast(Ends[i], PtrArithTy, "bc");
|
|
Value *End1 = ChkBuilder.CreateBitCast(Ends[j], PtrArithTy, "bc");
|
|
|
|
Value *Cmp0 = ChkBuilder.CreateICmpULE(Start0, End1, "bound0");
|
|
Value *Cmp1 = ChkBuilder.CreateICmpULE(Start1, End0, "bound1");
|
|
Value *IsConflict = ChkBuilder.CreateAnd(Cmp0, Cmp1, "found.conflict");
|
|
if (MemoryRuntimeCheck)
|
|
IsConflict = ChkBuilder.CreateOr(MemoryRuntimeCheck, IsConflict,
|
|
"conflict.rdx");
|
|
MemoryRuntimeCheck = IsConflict;
|
|
}
|
|
}
|
|
|
|
// 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 * Check = BinaryOperator::CreateAnd(MemoryRuntimeCheck,
|
|
ConstantInt::getTrue(Ctx));
|
|
ChkBuilder.Insert(Check, "memcheck.conflict");
|
|
return Check;
|
|
}
|
|
|
|
void
|
|
InnerLoopVectorizer::createEmptyLoop(LoopVectorizationLegality *Legal) {
|
|
/*
|
|
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.
|
|
|
|
[ ] <-- 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(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");
|
|
|
|
// Get the total trip count from the count by adding 1.
|
|
ExitCount = SE->getAddExpr(ExitCount,
|
|
SE->getConstant(ExitCount->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");
|
|
|
|
// Count holds the overall loop count (N).
|
|
Value *Count = Exp.expandCodeFor(ExitCount, ExitCount->getType(),
|
|
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);
|
|
|
|
assert(BypassBlock && "Invalid loop structure");
|
|
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");
|
|
|
|
// Use this IR builder to create the loop instructions (Phi, Br, Cmp)
|
|
// inside the loop.
|
|
Builder.SetInsertPoint(VecBody->getFirstInsertionPt());
|
|
|
|
// 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 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 = addRuntimeCheck(Legal,
|
|
BypassBlock->getTerminator());
|
|
if (MemRuntimeCheck) {
|
|
// Create a new block containing the memory check.
|
|
BasicBlock *CheckBlock = BypassBlock->splitBasicBlock(MemRuntimeCheck,
|
|
"vector.memcheck");
|
|
LoopBypassBlocks.push_back(CheckBlock);
|
|
|
|
// Replace the branch into the memory check block with a conditional branch
|
|
// for the "few elements case".
|
|
Instruction *OldTerm = BypassBlock->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 = 0;
|
|
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()) : 0;
|
|
|
|
Value *EndValue = 0;
|
|
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 = 0, E = LoopBypassBlocks.size(); I != E; ++I)
|
|
TruncResumeVal->addIncoming(II.StartValue, LoopBypassBlocks[I]);
|
|
TruncResumeVal->addIncoming(EndValue, VecBody);
|
|
|
|
// 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 = BypassBuilder.CreateAdd(CRD, II.StartValue , "ind.end");
|
|
break;
|
|
}
|
|
case LoopVectorizationLegality::IK_ReverseIntInduction: {
|
|
// Convert the CountRoundDown variable to the PHI size.
|
|
Value *CRD = BypassBuilder.CreateSExtOrTrunc(CountRoundDown,
|
|
II.StartValue->getType(),
|
|
"cast.crd");
|
|
// Handle reverse integer induction counter.
|
|
EndValue = BypassBuilder.CreateSub(II.StartValue, CRD, "rev.ind.end");
|
|
break;
|
|
}
|
|
case LoopVectorizationLegality::IK_PtrInduction: {
|
|
// For pointer induction variables, calculate the offset using
|
|
// the end index.
|
|
EndValue = BypassBuilder.CreateGEP(II.StartValue, CountRoundDown,
|
|
"ptr.ind.end");
|
|
break;
|
|
}
|
|
case LoopVectorizationLegality::IK_ReversePtrInduction: {
|
|
// The value at the end of the loop for the reverse pointer is calculated
|
|
// by creating a GEP with a negative index starting from the start value.
|
|
Value *Zero = ConstantInt::get(CountRoundDown->getType(), 0);
|
|
Value *NegIdx = BypassBuilder.CreateSub(Zero, CountRoundDown,
|
|
"rev.ind.end");
|
|
EndValue = BypassBuilder.CreateGEP(II.StartValue, NegIdx,
|
|
"rev.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 = 0, 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 inductions phi node in the scalar body needs the truncated value.
|
|
if (OrigPhi == OldInduction)
|
|
OrigPhi->setIncomingValue(BlockIdx, TruncResumeVal);
|
|
else
|
|
OrigPhi->setIncomingValue(BlockIdx, ResumeVal);
|
|
}
|
|
|
|
// 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 = 0, 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());
|
|
|
|
// 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.
|
|
if (ParentLoop) {
|
|
ParentLoop->addChildLoop(Lp);
|
|
for (unsigned I = 1, E = LoopBypassBlocks.size(); I != E; ++I)
|
|
ParentLoop->addBasicBlockToLoop(LoopBypassBlocks[I], LI->getBase());
|
|
ParentLoop->addBasicBlockToLoop(ScalarPH, LI->getBase());
|
|
ParentLoop->addBasicBlockToLoop(VectorPH, LI->getBase());
|
|
ParentLoop->addBasicBlockToLoop(MiddleBlock, LI->getBase());
|
|
} else {
|
|
LI->addTopLevelLoop(Lp);
|
|
}
|
|
|
|
Lp->addBasicBlockToLoop(VecBody, LI->getBase());
|
|
|
|
// Save the state.
|
|
LoopVectorPreHeader = VectorPH;
|
|
LoopScalarPreHeader = ScalarPH;
|
|
LoopMiddleBlock = MiddleBlock;
|
|
LoopExitBlock = ExitBlock;
|
|
LoopVectorBody = VecBody;
|
|
LoopScalarBody = OldBasicBlock;
|
|
}
|
|
|
|
/// 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");
|
|
}
|
|
}
|
|
|
|
static Intrinsic::ID
|
|
getIntrinsicIDForCall(CallInst *CI, const TargetLibraryInfo *TLI) {
|
|
// If we have an intrinsic call, check if it is trivially vectorizable.
|
|
if (IntrinsicInst *II = dyn_cast<IntrinsicInst>(CI)) {
|
|
switch (II->getIntrinsicID()) {
|
|
case Intrinsic::sqrt:
|
|
case Intrinsic::sin:
|
|
case Intrinsic::cos:
|
|
case Intrinsic::exp:
|
|
case Intrinsic::exp2:
|
|
case Intrinsic::log:
|
|
case Intrinsic::log10:
|
|
case Intrinsic::log2:
|
|
case Intrinsic::fabs:
|
|
case Intrinsic::floor:
|
|
case Intrinsic::ceil:
|
|
case Intrinsic::trunc:
|
|
case Intrinsic::rint:
|
|
case Intrinsic::nearbyint:
|
|
case Intrinsic::pow:
|
|
case Intrinsic::fma:
|
|
case Intrinsic::fmuladd:
|
|
return II->getIntrinsicID();
|
|
default:
|
|
return Intrinsic::not_intrinsic;
|
|
}
|
|
}
|
|
|
|
if (!TLI)
|
|
return Intrinsic::not_intrinsic;
|
|
|
|
LibFunc::Func Func;
|
|
Function *F = CI->getCalledFunction();
|
|
// We're going to make assumptions on the semantics of the functions, check
|
|
// that the target knows that it's available in this environment.
|
|
if (!F || !TLI->getLibFunc(F->getName(), Func))
|
|
return Intrinsic::not_intrinsic;
|
|
|
|
// Otherwise check if we have a call to a function that can be turned into a
|
|
// vector intrinsic.
|
|
switch (Func) {
|
|
default:
|
|
break;
|
|
case LibFunc::sin:
|
|
case LibFunc::sinf:
|
|
case LibFunc::sinl:
|
|
return Intrinsic::sin;
|
|
case LibFunc::cos:
|
|
case LibFunc::cosf:
|
|
case LibFunc::cosl:
|
|
return Intrinsic::cos;
|
|
case LibFunc::exp:
|
|
case LibFunc::expf:
|
|
case LibFunc::expl:
|
|
return Intrinsic::exp;
|
|
case LibFunc::exp2:
|
|
case LibFunc::exp2f:
|
|
case LibFunc::exp2l:
|
|
return Intrinsic::exp2;
|
|
case LibFunc::log:
|
|
case LibFunc::logf:
|
|
case LibFunc::logl:
|
|
return Intrinsic::log;
|
|
case LibFunc::log10:
|
|
case LibFunc::log10f:
|
|
case LibFunc::log10l:
|
|
return Intrinsic::log10;
|
|
case LibFunc::log2:
|
|
case LibFunc::log2f:
|
|
case LibFunc::log2l:
|
|
return Intrinsic::log2;
|
|
case LibFunc::fabs:
|
|
case LibFunc::fabsf:
|
|
case LibFunc::fabsl:
|
|
return Intrinsic::fabs;
|
|
case LibFunc::floor:
|
|
case LibFunc::floorf:
|
|
case LibFunc::floorl:
|
|
return Intrinsic::floor;
|
|
case LibFunc::ceil:
|
|
case LibFunc::ceilf:
|
|
case LibFunc::ceill:
|
|
return Intrinsic::ceil;
|
|
case LibFunc::trunc:
|
|
case LibFunc::truncf:
|
|
case LibFunc::truncl:
|
|
return Intrinsic::trunc;
|
|
case LibFunc::rint:
|
|
case LibFunc::rintf:
|
|
case LibFunc::rintl:
|
|
return Intrinsic::rint;
|
|
case LibFunc::nearbyint:
|
|
case LibFunc::nearbyintf:
|
|
case LibFunc::nearbyintl:
|
|
return Intrinsic::nearbyint;
|
|
case LibFunc::pow:
|
|
case LibFunc::powf:
|
|
case LibFunc::powl:
|
|
return Intrinsic::pow;
|
|
}
|
|
|
|
return Intrinsic::not_intrinsic;
|
|
}
|
|
|
|
/// 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;
|
|
}
|
|
|
|
void
|
|
InnerLoopVectorizer::vectorizeLoop(LoopVectorizationLegality *Legal) {
|
|
//===------------------------------------------------===//
|
|
//
|
|
// 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(Legal, *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 overide
|
|
// one of the elements with the incoming scalar reduction. We need
|
|
// to do it in the vector-loop preheader.
|
|
Builder.SetInsertPoint(LoopBypassBlocks.front()->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.
|
|
VectorStart = Identity = Builder.CreateVectorSplat(VF, RdxDesc.StartValue,
|
|
"minmax.ident");
|
|
} else {
|
|
Constant *Iden =
|
|
LoopVectorizationLegality::getReductionIdentity(RdxDesc.Kind,
|
|
VecTy->getScalarType());
|
|
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.
|
|
// We created the induction variable so we know that the
|
|
// preheader is the first entry.
|
|
BasicBlock *VecPreheader = Induction->getIncomingBlock(0);
|
|
|
|
// 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, VecPreheader);
|
|
cast<PHINode>(VecRdxPhi[part])->addIncoming(Val[part], LoopVectorBody);
|
|
}
|
|
|
|
// 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 = 0, E = LoopBypassBlocks.size(); I != E; ++I)
|
|
NewPhi->addIncoming(StartVal, LoopBypassBlocks[I]);
|
|
NewPhi->addIncoming(RdxExitVal[part], LoopVectorBody);
|
|
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)
|
|
ReducedPartRdx = Builder.CreateBinOp((Instruction::BinaryOps)Op,
|
|
RdxParts[part], ReducedPartRdx,
|
|
"bin.rdx");
|
|
else
|
|
ReducedPartRdx = createMinMaxOp(Builder, RdxDesc.MinMaxKind,
|
|
ReducedPartRdx, RdxParts[part]);
|
|
}
|
|
|
|
// 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, 0);
|
|
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)
|
|
TmpVec = 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.
|
|
Value *Scalar0 = Builder.CreateExtractElement(TmpVec, Builder.getInt32(0));
|
|
|
|
// 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) continue;
|
|
|
|
// 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(Scalar0, 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, Scalar0);
|
|
(RdxPhi)->setIncomingValue(IncomingEdgeBlockIdx, RdxDesc.LoopExitInstr);
|
|
}// end of for each redux variable.
|
|
|
|
// The Loop exit block may have single value PHI nodes where the incoming
|
|
// value is 'undef'. While vectorizing we only handled real values that
|
|
// were defined inside the loop. Here we handle the 'undef case'.
|
|
// See PR14725.
|
|
for (BasicBlock::iterator LEI = LoopExitBlock->begin(),
|
|
LEE = LoopExitBlock->end(); LEI != LEE; ++LEI) {
|
|
PHINode *LCSSAPhi = dyn_cast<PHINode>(LEI);
|
|
if (!LCSSAPhi) continue;
|
|
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::vectorizeBlockInLoop(LoopVectorizationLegality *Legal,
|
|
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:{
|
|
PHINode* P = cast<PHINode>(it);
|
|
// Handle reduction variables:
|
|
if (Legal->getReductionVars()->count(P)) {
|
|
for (unsigned part = 0; part < UF; ++part) {
|
|
// This is phase one of vectorizing PHIs.
|
|
Type *VecTy = VectorType::get(it->getType(), VF);
|
|
Entry[part] = PHINode::Create(VecTy, 2, "vec.phi",
|
|
LoopVectorBody-> getFirstInsertionPt());
|
|
}
|
|
PV->push_back(P);
|
|
continue;
|
|
}
|
|
|
|
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");
|
|
}
|
|
}
|
|
continue;
|
|
}
|
|
|
|
// 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);
|
|
|
|
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 = Builder.CreateAdd(II.StartValue, NormalizedIdx,
|
|
"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] = getConsecutiveVector(Broadcasted, VF * part, false);
|
|
continue;
|
|
}
|
|
case LoopVectorizationLegality::IK_ReverseIntInduction:
|
|
case LoopVectorizationLegality::IK_PtrInduction:
|
|
case LoopVectorizationLegality::IK_ReversePtrInduction:
|
|
// Handle reverse integer and pointer inductions.
|
|
Value *StartIdx = ExtendedIdx;
|
|
// This is the normalized GEP that starts counting at zero.
|
|
Value *NormalizedIdx = Builder.CreateSub(Induction, StartIdx,
|
|
"normalized.idx");
|
|
|
|
// Handle the reverse integer induction variable case.
|
|
if (LoopVectorizationLegality::IK_ReverseIntInduction == II.IK) {
|
|
IntegerType *DstTy = cast<IntegerType>(II.StartValue->getType());
|
|
Value *CNI = Builder.CreateSExtOrTrunc(NormalizedIdx, DstTy,
|
|
"resize.norm.idx");
|
|
Value *ReverseInd = Builder.CreateSub(II.StartValue, CNI,
|
|
"reverse.idx");
|
|
|
|
// This is a new value so do not hoist it out.
|
|
Value *Broadcasted = getBroadcastInstrs(ReverseInd);
|
|
// After broadcasting the induction variable we need to make the
|
|
// vector consecutive by adding ... -3, -2, -1, 0.
|
|
for (unsigned part = 0; part < UF; ++part)
|
|
Entry[part] = getConsecutiveVector(Broadcasted, -(int)VF * part,
|
|
true);
|
|
continue;
|
|
}
|
|
|
|
// Handle the pointer induction variable case.
|
|
assert(P->getType()->isPointerTy() && "Unexpected type.");
|
|
|
|
// Is this a reverse induction ptr or a consecutive induction ptr.
|
|
bool Reverse = (LoopVectorizationLegality::IK_ReversePtrInduction ==
|
|
II.IK);
|
|
|
|
// 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) {
|
|
Value *VecVal = UndefValue::get(VectorType::get(P->getType(), VF));
|
|
for (unsigned int i = 0; i < VF; ++i) {
|
|
int EltIndex = (i + part * VF) * (Reverse ? -1 : 1);
|
|
Constant *Idx = ConstantInt::get(Induction->getType(), EltIndex);
|
|
Value *GlobalIdx;
|
|
if (!Reverse)
|
|
GlobalIdx = Builder.CreateAdd(NormalizedIdx, Idx, "gep.idx");
|
|
else
|
|
GlobalIdx = Builder.CreateSub(Idx, NormalizedIdx, "gep.ridx");
|
|
|
|
Value *SclrGep = Builder.CreateGEP(II.StartValue, GlobalIdx,
|
|
"next.gep");
|
|
VecVal = Builder.CreateInsertElement(VecVal, SclrGep,
|
|
Builder.getInt32(i),
|
|
"insert.gep");
|
|
}
|
|
Entry[part] = VecVal;
|
|
}
|
|
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]);
|
|
|
|
// Update the NSW, NUW and Exact flags. Notice: V can be an Undef.
|
|
BinaryOperator *VecOp = dyn_cast<BinaryOperator>(V);
|
|
if (VecOp && isa<OverflowingBinaryOperator>(BinOp)) {
|
|
VecOp->setHasNoSignedWrap(BinOp->hasNoSignedWrap());
|
|
VecOp->setHasNoUnsignedWrap(BinOp->hasNoUnsignedWrap());
|
|
}
|
|
if (VecOp && isa<PossiblyExactOperator>(VecOp))
|
|
VecOp->setIsExact(BinOp->isExact());
|
|
|
|
Entry[Part] = V;
|
|
}
|
|
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 = 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]);
|
|
}
|
|
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 = 0;
|
|
if (FCmp)
|
|
C = Builder.CreateFCmp(Cmp->getPredicate(), A[Part], B[Part]);
|
|
else
|
|
C = Builder.CreateICmp(Cmp->getPredicate(), A[Part], B[Part]);
|
|
Entry[Part] = C;
|
|
}
|
|
break;
|
|
}
|
|
|
|
case Instruction::Store:
|
|
case Instruction::Load:
|
|
vectorizeMemoryInstruction(it, Legal);
|
|
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);
|
|
for (unsigned Part = 0; Part < UF; ++Part)
|
|
Entry[Part] = getConsecutiveVector(Broadcasted, VF * Part, false);
|
|
break;
|
|
}
|
|
/// Vectorize casts.
|
|
Type *DestTy = VectorType::get(CI->getType()->getScalarType(), VF);
|
|
|
|
VectorParts &A = getVectorValue(it->getOperand(0));
|
|
for (unsigned Part = 0; Part < UF; ++Part)
|
|
Entry[Part] = Builder.CreateCast(CI->getOpcode(), A[Part], DestTy);
|
|
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!");
|
|
for (unsigned Part = 0; Part < UF; ++Part) {
|
|
SmallVector<Value*, 4> Args;
|
|
for (unsigned i = 0, ie = CI->getNumArgOperands(); i != ie; ++i) {
|
|
VectorParts &Arg = getVectorValue(CI->getArgOperand(i));
|
|
Args.push_back(Arg[Part]);
|
|
}
|
|
Type *Tys[] = { VectorType::get(CI->getType()->getScalarType(), VF) };
|
|
Function *F = Intrinsic::getDeclaration(M, ID, Tys);
|
|
Entry[Part] = Builder.CreateCall(F, Args);
|
|
}
|
|
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());
|
|
DT->addNewBlock(LoopVectorBody, LoopVectorPreHeader);
|
|
DT->addNewBlock(LoopMiddleBlock, LoopBypassBlocks.front());
|
|
DT->addNewBlock(LoopScalarPreHeader, LoopMiddleBlock);
|
|
DT->changeImmediateDominator(LoopScalarBody, LoopScalarPreHeader);
|
|
DT->changeImmediateDominator(LoopExitBlock, LoopMiddleBlock);
|
|
|
|
DEBUG(DT->verifyAnalysis());
|
|
}
|
|
|
|
bool LoopVectorizationLegality::canVectorizeWithIfConvert() {
|
|
if (!EnableIfConversion)
|
|
return false;
|
|
|
|
assert(TheLoop->getNumBlocks() > 1 && "Single block loops are vectorizable");
|
|
std::vector<BasicBlock*> &LoopBlocks = TheLoop->getBlocksVector();
|
|
|
|
// A list of pointers that we can safely read and write to.
|
|
SmallPtrSet<Value *, 8> SafePointes;
|
|
|
|
// Collect safe addresses.
|
|
for (unsigned i = 0, e = LoopBlocks.size(); i < e; ++i) {
|
|
BasicBlock *BB = LoopBlocks[i];
|
|
|
|
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.
|
|
for (unsigned i = 0, e = LoopBlocks.size(); i < e; ++i) {
|
|
BasicBlock *BB = LoopBlocks[i];
|
|
|
|
// We don't support switch statements inside loops.
|
|
if (!isa<BranchInst>(BB->getTerminator()))
|
|
return false;
|
|
|
|
// We must be able to predicate all blocks that need to be predicated.
|
|
if (blockNeedsPredication(BB) && !blockCanBePredicated(BB, SafePointes))
|
|
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())
|
|
return false;
|
|
|
|
// We can only vectorize innermost loops.
|
|
if (TheLoop->getSubLoopsVector().size())
|
|
return false;
|
|
|
|
// We must have a single backedge.
|
|
if (TheLoop->getNumBackEdges() != 1)
|
|
return false;
|
|
|
|
// We must have a single exiting block.
|
|
if (!TheLoop->getExitingBlock())
|
|
return false;
|
|
|
|
unsigned NumBlocks = TheLoop->getNumBlocks();
|
|
|
|
// Check if we can if-convert non single-bb loops.
|
|
if (NumBlocks != 1 && !canVectorizeWithIfConvert()) {
|
|
DEBUG(dbgs() << "LV: Can't if-convert the loop.\n");
|
|
return false;
|
|
}
|
|
|
|
// We need to have a loop header.
|
|
BasicBlock *Latch = TheLoop->getLoopLatch();
|
|
DEBUG(dbgs() << "LV: Found a loop: " <<
|
|
TheLoop->getHeader()->getName() << "\n");
|
|
|
|
// ScalarEvolution needs to be able to find the exit count.
|
|
const SCEV *ExitCount = SE->getBackedgeTakenCount(TheLoop);
|
|
if (ExitCount == SE->getCouldNotCompute()) {
|
|
DEBUG(dbgs() << "LV: SCEV could not compute the loop exit count.\n");
|
|
return false;
|
|
}
|
|
|
|
// Do not loop-vectorize loops with a tiny trip count.
|
|
unsigned TC = SE->getSmallConstantTripCount(TheLoop, Latch);
|
|
if (TC > 0u && TC < TinyTripCountVectorThreshold) {
|
|
DEBUG(dbgs() << "LV: Found a loop with a very small trip count. " <<
|
|
"This loop is not worth vectorizing.\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" <<
|
|
(PtrRtCheck.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(DataLayout &DL, Type *Ty) {
|
|
if (Ty->isPointerTy())
|
|
return DL.getIntPtrType(Ty->getContext());
|
|
return Ty;
|
|
}
|
|
|
|
static Type* getWiderType(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,
|
|
SmallPtrSet<Value *, 4> &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 (Value::use_iterator I = Inst->use_begin(), E = Inst->use_end();
|
|
I != E; ++I) {
|
|
Instruction *U = cast<Instruction>(*I);
|
|
// This user may be a reduction exit value.
|
|
if (!TheLoop->contains(U)) {
|
|
DEBUG(dbgs() << "LV: Found an outside user for : "<< *U << "\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.getAttributes().getAttribute(
|
|
AttributeSet::FunctionIndex,
|
|
"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()) {
|
|
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;
|
|
return false;
|
|
}
|
|
|
|
// We only allow if-converted PHIs with more than two incoming values.
|
|
if (Phi->getNumIncomingValues() != 2) {
|
|
DEBUG(dbgs() << "LV: Found an invalid PHI.\n");
|
|
return false;
|
|
}
|
|
|
|
// This is the value coming from the preheader.
|
|
Value *StartValue = Phi->getIncomingValueForBlock(PreHeader);
|
|
// Check if this is an induction variable.
|
|
InductionKind IK = isInductionVariable(Phi);
|
|
|
|
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) {
|
|
// 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);
|
|
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;
|
|
}
|
|
|
|
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)) {
|
|
DEBUG(dbgs() << "LV: Found a call site.\n");
|
|
return false;
|
|
}
|
|
|
|
// Check that the instruction return type is vectorizable.
|
|
if (!VectorType::isValidElementType(it->getType()) &&
|
|
!it->getType()->isVoidTy()) {
|
|
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))
|
|
return false;
|
|
}
|
|
|
|
// Reduction instructions are allowed to have exit users.
|
|
// All other instructions must not have external users.
|
|
if (hasOutsideLoopUser(TheLoop, it, AllowedExit))
|
|
return false;
|
|
|
|
} // next instr.
|
|
|
|
}
|
|
|
|
if (!Induction) {
|
|
DEBUG(dbgs() << "LV: Did not find one integer induction var.\n");
|
|
if (Inductions.empty())
|
|
return false;
|
|
}
|
|
|
|
return true;
|
|
}
|
|
|
|
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));
|
|
|
|
while (Worklist.size()) {
|
|
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());
|
|
}
|
|
}
|
|
|
|
namespace {
|
|
/// \brief Analyses memory accesses in a loop.
|
|
///
|
|
/// Checks whether run time pointer checks are needed and builds sets for data
|
|
/// dependence checking.
|
|
class AccessAnalysis {
|
|
public:
|
|
/// \brief Read or write access location.
|
|
typedef PointerIntPair<Value *, 1, bool> MemAccessInfo;
|
|
typedef SmallPtrSet<MemAccessInfo, 8> MemAccessInfoSet;
|
|
|
|
/// \brief Set of potential dependent memory accesses.
|
|
typedef EquivalenceClasses<MemAccessInfo> DepCandidates;
|
|
|
|
AccessAnalysis(DataLayout *Dl, DepCandidates &DA) :
|
|
DL(Dl), DepCands(DA), AreAllWritesIdentified(true),
|
|
AreAllReadsIdentified(true), IsRTCheckNeeded(false) {}
|
|
|
|
/// \brief Register a load and whether it is only read from.
|
|
void addLoad(Value *Ptr, bool IsReadOnly) {
|
|
Accesses.insert(MemAccessInfo(Ptr, false));
|
|
if (IsReadOnly)
|
|
ReadOnlyPtr.insert(Ptr);
|
|
}
|
|
|
|
/// \brief Register a store.
|
|
void addStore(Value *Ptr) {
|
|
Accesses.insert(MemAccessInfo(Ptr, true));
|
|
}
|
|
|
|
/// \brief Check whether we can check the pointers at runtime for
|
|
/// non-intersection.
|
|
bool canCheckPtrAtRT(LoopVectorizationLegality::RuntimePointerCheck &RtCheck,
|
|
unsigned &NumComparisons, ScalarEvolution *SE,
|
|
Loop *TheLoop);
|
|
|
|
/// \brief Goes over all memory accesses, checks whether a RT check is needed
|
|
/// and builds sets of dependent accesses.
|
|
void buildDependenceSets() {
|
|
// Process read-write pointers first.
|
|
processMemAccesses(false);
|
|
// Next, process read pointers.
|
|
processMemAccesses(true);
|
|
}
|
|
|
|
bool isRTCheckNeeded() { return IsRTCheckNeeded; }
|
|
|
|
bool isDependencyCheckNeeded() { return !CheckDeps.empty(); }
|
|
|
|
MemAccessInfoSet &getDependenciesToCheck() { return CheckDeps; }
|
|
|
|
private:
|
|
typedef SetVector<MemAccessInfo> PtrAccessSet;
|
|
typedef DenseMap<Value*, MemAccessInfo> UnderlyingObjToAccessMap;
|
|
|
|
/// \brief Go over all memory access or only the deferred ones if
|
|
/// \p UseDeferred is true and check whether runtime pointer checks are needed
|
|
/// and build sets of dependency check candidates.
|
|
void processMemAccesses(bool UseDeferred);
|
|
|
|
/// Set of all accesses.
|
|
PtrAccessSet Accesses;
|
|
|
|
/// Set of access to check after all writes have been processed.
|
|
PtrAccessSet DeferredAccesses;
|
|
|
|
/// Map of pointers to last access encountered.
|
|
UnderlyingObjToAccessMap ObjToLastAccess;
|
|
|
|
/// Set of accesses that need a further dependence check.
|
|
MemAccessInfoSet CheckDeps;
|
|
|
|
/// Set of pointers that are read only.
|
|
SmallPtrSet<Value*, 16> ReadOnlyPtr;
|
|
|
|
/// Set of underlying objects already written to.
|
|
SmallPtrSet<Value*, 16> WriteObjects;
|
|
|
|
DataLayout *DL;
|
|
|
|
/// Sets of potentially dependent accesses - members of one set share an
|
|
/// underlying pointer. The set "CheckDeps" identfies which sets really need a
|
|
/// dependence check.
|
|
DepCandidates &DepCands;
|
|
|
|
bool AreAllWritesIdentified;
|
|
bool AreAllReadsIdentified;
|
|
bool IsRTCheckNeeded;
|
|
};
|
|
|
|
} // end anonymous namespace
|
|
|
|
/// \brief Check whether a pointer can participate in a runtime bounds check.
|
|
static bool hasComputableBounds(ScalarEvolution *SE, Value *Ptr) {
|
|
const SCEV *PtrScev = SE->getSCEV(Ptr);
|
|
const SCEVAddRecExpr *AR = dyn_cast<SCEVAddRecExpr>(PtrScev);
|
|
if (!AR)
|
|
return false;
|
|
|
|
return AR->isAffine();
|
|
}
|
|
|
|
bool AccessAnalysis::canCheckPtrAtRT(
|
|
LoopVectorizationLegality::RuntimePointerCheck &RtCheck,
|
|
unsigned &NumComparisons, ScalarEvolution *SE,
|
|
Loop *TheLoop) {
|
|
// Find pointers with computable bounds. We are going to use this information
|
|
// to place a runtime bound check.
|
|
unsigned NumReadPtrChecks = 0;
|
|
unsigned NumWritePtrChecks = 0;
|
|
bool CanDoRT = true;
|
|
|
|
bool IsDepCheckNeeded = isDependencyCheckNeeded();
|
|
// We assign consecutive id to access from different dependence sets.
|
|
// Accesses within the same set don't need a runtime check.
|
|
unsigned RunningDepId = 1;
|
|
DenseMap<Value *, unsigned> DepSetId;
|
|
|
|
for (PtrAccessSet::iterator AI = Accesses.begin(), AE = Accesses.end();
|
|
AI != AE; ++AI) {
|
|
const MemAccessInfo &Access = *AI;
|
|
Value *Ptr = Access.getPointer();
|
|
bool IsWrite = Access.getInt();
|
|
|
|
// Just add write checks if we have both.
|
|
if (!IsWrite && Accesses.count(MemAccessInfo(Ptr, true)))
|
|
continue;
|
|
|
|
if (IsWrite)
|
|
++NumWritePtrChecks;
|
|
else
|
|
++NumReadPtrChecks;
|
|
|
|
if (hasComputableBounds(SE, Ptr)) {
|
|
// The id of the dependence set.
|
|
unsigned DepId;
|
|
|
|
if (IsDepCheckNeeded) {
|
|
Value *Leader = DepCands.getLeaderValue(Access).getPointer();
|
|
unsigned &LeaderId = DepSetId[Leader];
|
|
if (!LeaderId)
|
|
LeaderId = RunningDepId++;
|
|
DepId = LeaderId;
|
|
} else
|
|
// Each access has its own dependence set.
|
|
DepId = RunningDepId++;
|
|
|
|
RtCheck.insert(SE, TheLoop, Ptr, IsWrite, DepId);
|
|
|
|
DEBUG(dbgs() << "LV: Found a runtime check ptr:" << *Ptr <<"\n");
|
|
} else {
|
|
CanDoRT = false;
|
|
}
|
|
}
|
|
|
|
if (IsDepCheckNeeded && CanDoRT && RunningDepId == 2)
|
|
NumComparisons = 0; // Only one dependence set.
|
|
else
|
|
NumComparisons = (NumWritePtrChecks * (NumReadPtrChecks +
|
|
NumWritePtrChecks - 1));
|
|
return CanDoRT;
|
|
}
|
|
|
|
static bool isFunctionScopeIdentifiedObject(Value *Ptr) {
|
|
return isNoAliasArgument(Ptr) || isNoAliasCall(Ptr) || isa<AllocaInst>(Ptr);
|
|
}
|
|
|
|
void AccessAnalysis::processMemAccesses(bool UseDeferred) {
|
|
// We process the set twice: first we process read-write pointers, last we
|
|
// process read-only pointers. This allows us to skip dependence tests for
|
|
// read-only pointers.
|
|
|
|
PtrAccessSet &S = UseDeferred ? DeferredAccesses : Accesses;
|
|
for (PtrAccessSet::iterator AI = S.begin(), AE = S.end(); AI != AE; ++AI) {
|
|
const MemAccessInfo &Access = *AI;
|
|
Value *Ptr = Access.getPointer();
|
|
bool IsWrite = Access.getInt();
|
|
|
|
DepCands.insert(Access);
|
|
|
|
// Memorize read-only pointers for later processing and skip them in the
|
|
// first round (they need to be checked after we have seen all write
|
|
// pointers). Note: we also mark pointer that are not consecutive as
|
|
// "read-only" pointers (so that we check "a[b[i]] +="). Hence, we need the
|
|
// second check for "!IsWrite".
|
|
bool IsReadOnlyPtr = ReadOnlyPtr.count(Ptr) && !IsWrite;
|
|
if (!UseDeferred && IsReadOnlyPtr) {
|
|
DeferredAccesses.insert(Access);
|
|
continue;
|
|
}
|
|
|
|
bool NeedDepCheck = false;
|
|
// Check whether there is the possiblity of dependency because of underlying
|
|
// objects being the same.
|
|
typedef SmallVector<Value*, 16> ValueVector;
|
|
ValueVector TempObjects;
|
|
GetUnderlyingObjects(Ptr, TempObjects, DL);
|
|
for (ValueVector::iterator UI = TempObjects.begin(), UE = TempObjects.end();
|
|
UI != UE; ++UI) {
|
|
Value *UnderlyingObj = *UI;
|
|
|
|
// If this is a write then it needs to be an identified object. If this a
|
|
// read and all writes (so far) are identified function scope objects we
|
|
// don't need an identified underlying object but only an Argument (the
|
|
// next write is going to invalidate this assumption if it is
|
|
// unidentified).
|
|
// This is a micro-optimization for the case where all writes are
|
|
// identified and we have one argument pointer.
|
|
// Otherwise, we do need a runtime check.
|
|
if ((IsWrite && !isFunctionScopeIdentifiedObject(UnderlyingObj)) ||
|
|
(!IsWrite && (!AreAllWritesIdentified ||
|
|
!isa<Argument>(UnderlyingObj)) &&
|
|
!isIdentifiedObject(UnderlyingObj))) {
|
|
DEBUG(dbgs() << "LV: Found an unidentified " <<
|
|
(IsWrite ? "write" : "read" ) << " ptr:" << *UnderlyingObj <<
|
|
"\n");
|
|
IsRTCheckNeeded = (IsRTCheckNeeded ||
|
|
!isIdentifiedObject(UnderlyingObj) ||
|
|
!AreAllReadsIdentified);
|
|
|
|
if (IsWrite)
|
|
AreAllWritesIdentified = false;
|
|
if (!IsWrite)
|
|
AreAllReadsIdentified = false;
|
|
}
|
|
|
|
// If this is a write - check other reads and writes for conflicts. If
|
|
// this is a read only check other writes for conflicts (but only if there
|
|
// is no other write to the ptr - this is an optimization to catch "a[i] =
|
|
// a[i] + " without having to do a dependence check).
|
|
if ((IsWrite || IsReadOnlyPtr) && WriteObjects.count(UnderlyingObj))
|
|
NeedDepCheck = true;
|
|
|
|
if (IsWrite)
|
|
WriteObjects.insert(UnderlyingObj);
|
|
|
|
// Create sets of pointers connected by shared underlying objects.
|
|
UnderlyingObjToAccessMap::iterator Prev =
|
|
ObjToLastAccess.find(UnderlyingObj);
|
|
if (Prev != ObjToLastAccess.end())
|
|
DepCands.unionSets(Access, Prev->second);
|
|
|
|
ObjToLastAccess[UnderlyingObj] = Access;
|
|
}
|
|
|
|
if (NeedDepCheck)
|
|
CheckDeps.insert(Access);
|
|
}
|
|
}
|
|
|
|
namespace {
|
|
/// \brief Checks memory dependences among accesses to the same underlying
|
|
/// object to determine whether there vectorization is legal or not (and at
|
|
/// which vectorization factor).
|
|
///
|
|
/// This class works under the assumption that we already checked that memory
|
|
/// locations with different underlying pointers are "must-not alias".
|
|
/// We use the ScalarEvolution framework to symbolically evalutate access
|
|
/// functions pairs. Since we currently don't restructure the loop we can rely
|
|
/// on the program order of memory accesses to determine their safety.
|
|
/// At the moment we will only deem accesses as safe for:
|
|
/// * A negative constant distance assuming program order.
|
|
///
|
|
/// Safe: tmp = a[i + 1]; OR a[i + 1] = x;
|
|
/// a[i] = tmp; y = a[i];
|
|
///
|
|
/// The latter case is safe because later checks guarantuee that there can't
|
|
/// be a cycle through a phi node (that is, we check that "x" and "y" is not
|
|
/// the same variable: a header phi can only be an induction or a reduction, a
|
|
/// reduction can't have a memory sink, an induction can't have a memory
|
|
/// source). This is important and must not be violated (or we have to
|
|
/// resort to checking for cycles through memory).
|
|
///
|
|
/// * A positive constant distance assuming program order that is bigger
|
|
/// than the biggest memory access.
|
|
///
|
|
/// tmp = a[i] OR b[i] = x
|
|
/// a[i+2] = tmp y = b[i+2];
|
|
///
|
|
/// Safe distance: 2 x sizeof(a[0]), and 2 x sizeof(b[0]), respectively.
|
|
///
|
|
/// * Zero distances and all accesses have the same size.
|
|
///
|
|
class MemoryDepChecker {
|
|
public:
|
|
typedef PointerIntPair<Value *, 1, bool> MemAccessInfo;
|
|
typedef SmallPtrSet<MemAccessInfo, 8> MemAccessInfoSet;
|
|
|
|
MemoryDepChecker(ScalarEvolution *Se, DataLayout *Dl, const Loop *L) :
|
|
SE(Se), DL(Dl), InnermostLoop(L), AccessIdx(0) {}
|
|
|
|
/// \brief Register the location (instructions are given increasing numbers)
|
|
/// of a write access.
|
|
void addAccess(StoreInst *SI) {
|
|
Value *Ptr = SI->getPointerOperand();
|
|
Accesses[MemAccessInfo(Ptr, true)].push_back(AccessIdx);
|
|
InstMap.push_back(SI);
|
|
++AccessIdx;
|
|
}
|
|
|
|
/// \brief Register the location (instructions are given increasing numbers)
|
|
/// of a write access.
|
|
void addAccess(LoadInst *LI) {
|
|
Value *Ptr = LI->getPointerOperand();
|
|
Accesses[MemAccessInfo(Ptr, false)].push_back(AccessIdx);
|
|
InstMap.push_back(LI);
|
|
++AccessIdx;
|
|
}
|
|
|
|
/// \brief Check whether the dependencies between the accesses are safe.
|
|
///
|
|
/// Only checks sets with elements in \p CheckDeps.
|
|
bool areDepsSafe(AccessAnalysis::DepCandidates &AccessSets,
|
|
MemAccessInfoSet &CheckDeps);
|
|
|
|
/// \brief The maximum number of bytes of a vector register we can vectorize
|
|
/// the accesses safely with.
|
|
unsigned getMaxSafeDepDistBytes() { return MaxSafeDepDistBytes; }
|
|
|
|
private:
|
|
ScalarEvolution *SE;
|
|
DataLayout *DL;
|
|
const Loop *InnermostLoop;
|
|
|
|
/// \brief Maps access locations (ptr, read/write) to program order.
|
|
DenseMap<MemAccessInfo, std::vector<unsigned> > Accesses;
|
|
|
|
/// \brief Memory access instructions in program order.
|
|
SmallVector<Instruction *, 16> InstMap;
|
|
|
|
/// \brief The program order index to be used for the next instruction.
|
|
unsigned AccessIdx;
|
|
|
|
// We can access this many bytes in parallel safely.
|
|
unsigned MaxSafeDepDistBytes;
|
|
|
|
/// \brief Check whether there is a plausible dependence between the two
|
|
/// accesses.
|
|
///
|
|
/// Access \p A must happen before \p B in program order. The two indices
|
|
/// identify the index into the program order map.
|
|
///
|
|
/// This function checks whether there is a plausible dependence (or the
|
|
/// absence of such can't be proved) between the two accesses. If there is a
|
|
/// plausible dependence but the dependence distance is bigger than one
|
|
/// element access it records this distance in \p MaxSafeDepDistBytes (if this
|
|
/// distance is smaller than any other distance encountered so far).
|
|
/// Otherwise, this function returns true signaling a possible dependence.
|
|
bool isDependent(const MemAccessInfo &A, unsigned AIdx,
|
|
const MemAccessInfo &B, unsigned BIdx);
|
|
|
|
/// \brief Check whether the data dependence could prevent store-load
|
|
/// forwarding.
|
|
bool couldPreventStoreLoadForward(unsigned Distance, unsigned TypeByteSize);
|
|
};
|
|
|
|
} // end anonymous namespace
|
|
|
|
static bool isInBoundsGep(Value *Ptr) {
|
|
if (GetElementPtrInst *GEP = dyn_cast<GetElementPtrInst>(Ptr))
|
|
return GEP->isInBounds();
|
|
return false;
|
|
}
|
|
|
|
/// \brief Check whether the access through \p Ptr has a constant stride.
|
|
static int isStridedPtr(ScalarEvolution *SE, DataLayout *DL, Value *Ptr,
|
|
const Loop *Lp) {
|
|
const Type *PtrTy = Ptr->getType();
|
|
assert(PtrTy->isPointerTy() && "Unexpected non ptr");
|
|
|
|
// Make sure that the pointer does not point to aggregate types.
|
|
if (cast<PointerType>(Ptr->getType())->getElementType()->isAggregateType()) {
|
|
DEBUG(dbgs() << "LV: Bad stride - Not a pointer to a scalar type" << *Ptr
|
|
<< "\n");
|
|
return 0;
|
|
}
|
|
|
|
const SCEV *PtrScev = SE->getSCEV(Ptr);
|
|
const SCEVAddRecExpr *AR = dyn_cast<SCEVAddRecExpr>(PtrScev);
|
|
if (!AR) {
|
|
DEBUG(dbgs() << "LV: Bad stride - Not an AddRecExpr pointer "
|
|
<< *Ptr << " SCEV: " << *PtrScev << "\n");
|
|
return 0;
|
|
}
|
|
|
|
// The accesss function must stride over the innermost loop.
|
|
if (Lp != AR->getLoop()) {
|
|
DEBUG(dbgs() << "LV: Bad stride - Not striding over innermost loop " << *Ptr
|
|
<< " SCEV: " << *PtrScev << "\n");
|
|
}
|
|
|
|
// The address calculation must not wrap. Otherwise, a dependence could be
|
|
// inverted. An inbounds getelementptr that is a AddRec with a unit stride
|
|
// cannot wrap per definition. The unit stride requirement is checked later.
|
|
bool IsInBoundsGEP = isInBoundsGep(Ptr);
|
|
bool IsNoWrapAddRec = AR->getNoWrapFlags(SCEV::NoWrapMask);
|
|
if (!IsNoWrapAddRec && !IsInBoundsGEP) {
|
|
DEBUG(dbgs() << "LV: Bad stride - Pointer may wrap in the address space "
|
|
<< *Ptr << " SCEV: " << *PtrScev << "\n");
|
|
return 0;
|
|
}
|
|
|
|
// Check the step is constant.
|
|
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) {
|
|
DEBUG(dbgs() << "LV: Bad stride - Not a constant strided " << *Ptr <<
|
|
" SCEV: " << *PtrScev << "\n");
|
|
return 0;
|
|
}
|
|
|
|
int64_t Size = DL->getTypeAllocSize(PtrTy->getPointerElementType());
|
|
const APInt &APStepVal = C->getValue()->getValue();
|
|
|
|
// Huge step value - give up.
|
|
if (APStepVal.getBitWidth() > 64)
|
|
return 0;
|
|
|
|
int64_t StepVal = APStepVal.getSExtValue();
|
|
|
|
// Strided access.
|
|
int64_t Stride = StepVal / Size;
|
|
int64_t Rem = StepVal % Size;
|
|
if (Rem)
|
|
return 0;
|
|
|
|
// If the SCEV could wrap but we have an inbounds gep with a unit stride we
|
|
// know we can't "wrap around the address space".
|
|
if (!IsNoWrapAddRec && IsInBoundsGEP && Stride != 1 && Stride != -1)
|
|
return 0;
|
|
|
|
return Stride;
|
|
}
|
|
|
|
bool MemoryDepChecker::couldPreventStoreLoadForward(unsigned Distance,
|
|
unsigned TypeByteSize) {
|
|
// If loads occur at a distance that is not a multiple of a feasible vector
|
|
// factor store-load forwarding does not take place.
|
|
// Positive dependences might cause troubles because vectorizing them might
|
|
// prevent store-load forwarding making vectorized code run a lot slower.
|
|
// a[i] = a[i-3] ^ a[i-8];
|
|
// The stores to a[i:i+1] don't align with the stores to a[i-3:i-2] and
|
|
// hence on your typical architecture store-load forwarding does not take
|
|
// place. Vectorizing in such cases does not make sense.
|
|
// Store-load forwarding distance.
|
|
const unsigned NumCyclesForStoreLoadThroughMemory = 8*TypeByteSize;
|
|
// Maximum vector factor.
|
|
unsigned MaxVFWithoutSLForwardIssues = MaxVectorWidth*TypeByteSize;
|
|
if(MaxSafeDepDistBytes < MaxVFWithoutSLForwardIssues)
|
|
MaxVFWithoutSLForwardIssues = MaxSafeDepDistBytes;
|
|
|
|
for (unsigned vf = 2*TypeByteSize; vf <= MaxVFWithoutSLForwardIssues;
|
|
vf *= 2) {
|
|
if (Distance % vf && Distance / vf < NumCyclesForStoreLoadThroughMemory) {
|
|
MaxVFWithoutSLForwardIssues = (vf >>=1);
|
|
break;
|
|
}
|
|
}
|
|
|
|
if (MaxVFWithoutSLForwardIssues< 2*TypeByteSize) {
|
|
DEBUG(dbgs() << "LV: Distance " << Distance <<
|
|
" that could cause a store-load forwarding conflict\n");
|
|
return true;
|
|
}
|
|
|
|
if (MaxVFWithoutSLForwardIssues < MaxSafeDepDistBytes &&
|
|
MaxVFWithoutSLForwardIssues != MaxVectorWidth*TypeByteSize)
|
|
MaxSafeDepDistBytes = MaxVFWithoutSLForwardIssues;
|
|
return false;
|
|
}
|
|
|
|
bool MemoryDepChecker::isDependent(const MemAccessInfo &A, unsigned AIdx,
|
|
const MemAccessInfo &B, unsigned BIdx) {
|
|
assert (AIdx < BIdx && "Must pass arguments in program order");
|
|
|
|
Value *APtr = A.getPointer();
|
|
Value *BPtr = B.getPointer();
|
|
bool AIsWrite = A.getInt();
|
|
bool BIsWrite = B.getInt();
|
|
|
|
// Two reads are independent.
|
|
if (!AIsWrite && !BIsWrite)
|
|
return false;
|
|
|
|
const SCEV *AScev = SE->getSCEV(APtr);
|
|
const SCEV *BScev = SE->getSCEV(BPtr);
|
|
|
|
int StrideAPtr = isStridedPtr(SE, DL, APtr, InnermostLoop);
|
|
int StrideBPtr = isStridedPtr(SE, DL, BPtr, InnermostLoop);
|
|
|
|
const SCEV *Src = AScev;
|
|
const SCEV *Sink = BScev;
|
|
|
|
// If the induction step is negative we have to invert source and sink of the
|
|
// dependence.
|
|
if (StrideAPtr < 0) {
|
|
//Src = BScev;
|
|
//Sink = AScev;
|
|
std::swap(APtr, BPtr);
|
|
std::swap(Src, Sink);
|
|
std::swap(AIsWrite, BIsWrite);
|
|
std::swap(AIdx, BIdx);
|
|
std::swap(StrideAPtr, StrideBPtr);
|
|
}
|
|
|
|
const SCEV *Dist = SE->getMinusSCEV(Sink, Src);
|
|
|
|
DEBUG(dbgs() << "LV: Src Scev: " << *Src << "Sink Scev: " << *Sink
|
|
<< "(Induction step: " << StrideAPtr << ")\n");
|
|
DEBUG(dbgs() << "LV: Distance for " << *InstMap[AIdx] << " to "
|
|
<< *InstMap[BIdx] << ": " << *Dist << "\n");
|
|
|
|
// Need consecutive accesses. We don't want to vectorize
|
|
// "A[B[i]] += ..." and similar code or pointer arithmetic that could wrap in
|
|
// the address space.
|
|
if (!StrideAPtr || !StrideBPtr || StrideAPtr != StrideBPtr){
|
|
DEBUG(dbgs() << "Non-consecutive pointer access\n");
|
|
return true;
|
|
}
|
|
|
|
const SCEVConstant *C = dyn_cast<SCEVConstant>(Dist);
|
|
if (!C) {
|
|
DEBUG(dbgs() << "LV: Dependence because of non constant distance\n");
|
|
return true;
|
|
}
|
|
|
|
Type *ATy = APtr->getType()->getPointerElementType();
|
|
Type *BTy = BPtr->getType()->getPointerElementType();
|
|
unsigned TypeByteSize = DL->getTypeAllocSize(ATy);
|
|
|
|
// Negative distances are not plausible dependencies.
|
|
const APInt &Val = C->getValue()->getValue();
|
|
if (Val.isNegative()) {
|
|
bool IsTrueDataDependence = (AIsWrite && !BIsWrite);
|
|
if (IsTrueDataDependence &&
|
|
(couldPreventStoreLoadForward(Val.abs().getZExtValue(), TypeByteSize) ||
|
|
ATy != BTy))
|
|
return true;
|
|
|
|
DEBUG(dbgs() << "LV: Dependence is negative: NoDep\n");
|
|
return false;
|
|
}
|
|
|
|
// Write to the same location with the same size.
|
|
// Could be improved to assert type sizes are the same (i32 == float, etc).
|
|
if (Val == 0) {
|
|
if (ATy == BTy)
|
|
return false;
|
|
DEBUG(dbgs() << "LV: Zero dependence difference but different types");
|
|
return true;
|
|
}
|
|
|
|
assert(Val.isStrictlyPositive() && "Expect a positive value");
|
|
|
|
// Positive distance bigger than max vectorization factor.
|
|
if (ATy != BTy) {
|
|
DEBUG(dbgs() <<
|
|
"LV: ReadWrite-Write positive dependency with different types");
|
|
return false;
|
|
}
|
|
|
|
unsigned Distance = (unsigned) Val.getZExtValue();
|
|
|
|
// Bail out early if passed-in parameters make vectorization not feasible.
|
|
unsigned ForcedFactor = VectorizationFactor ? VectorizationFactor : 1;
|
|
unsigned ForcedUnroll = VectorizationUnroll ? VectorizationUnroll : 1;
|
|
|
|
// The distance must be bigger than the size needed for a vectorized version
|
|
// of the operation and the size of the vectorized operation must not be
|
|
// bigger than the currrent maximum size.
|
|
if (Distance < 2*TypeByteSize ||
|
|
2*TypeByteSize > MaxSafeDepDistBytes ||
|
|
Distance < TypeByteSize * ForcedUnroll * ForcedFactor) {
|
|
DEBUG(dbgs() << "LV: Failure because of Positive distance "
|
|
<< Val.getSExtValue() << "\n");
|
|
return true;
|
|
}
|
|
|
|
MaxSafeDepDistBytes = Distance < MaxSafeDepDistBytes ?
|
|
Distance : MaxSafeDepDistBytes;
|
|
|
|
bool IsTrueDataDependence = (!AIsWrite && BIsWrite);
|
|
if (IsTrueDataDependence &&
|
|
couldPreventStoreLoadForward(Distance, TypeByteSize))
|
|
return true;
|
|
|
|
DEBUG(dbgs() << "LV: Positive distance " << Val.getSExtValue() <<
|
|
" with max VF=" << MaxSafeDepDistBytes/TypeByteSize << "\n");
|
|
|
|
return false;
|
|
}
|
|
|
|
bool
|
|
MemoryDepChecker::areDepsSafe(AccessAnalysis::DepCandidates &AccessSets,
|
|
MemAccessInfoSet &CheckDeps) {
|
|
|
|
MaxSafeDepDistBytes = -1U;
|
|
while (!CheckDeps.empty()) {
|
|
MemAccessInfo CurAccess = *CheckDeps.begin();
|
|
|
|
// Get the relevant memory access set.
|
|
EquivalenceClasses<MemAccessInfo>::iterator I =
|
|
AccessSets.findValue(AccessSets.getLeaderValue(CurAccess));
|
|
|
|
// Check accesses within this set.
|
|
EquivalenceClasses<MemAccessInfo>::member_iterator AI, AE;
|
|
AI = AccessSets.member_begin(I), AE = AccessSets.member_end();
|
|
|
|
// Check every access pair.
|
|
while (AI != AE) {
|
|
CheckDeps.erase(*AI);
|
|
EquivalenceClasses<MemAccessInfo>::member_iterator OI = llvm::next(AI);
|
|
while (OI != AE) {
|
|
// Check every accessing instruction pair in program order.
|
|
for (std::vector<unsigned>::iterator I1 = Accesses[*AI].begin(),
|
|
I1E = Accesses[*AI].end(); I1 != I1E; ++I1)
|
|
for (std::vector<unsigned>::iterator I2 = Accesses[*OI].begin(),
|
|
I2E = Accesses[*OI].end(); I2 != I2E; ++I2) {
|
|
if (*I1 < *I2 && isDependent(*AI, *I1, *OI, *I2))
|
|
return false;
|
|
if (*I2 < *I1 && isDependent(*OI, *I2, *AI, *I1))
|
|
return false;
|
|
}
|
|
++OI;
|
|
}
|
|
AI++;
|
|
}
|
|
}
|
|
return true;
|
|
}
|
|
|
|
bool LoopVectorizationLegality::canVectorizeMemory() {
|
|
|
|
typedef SmallVector<Value*, 16> ValueVector;
|
|
typedef SmallPtrSet<Value*, 16> ValueSet;
|
|
|
|
// Holds the Load and Store *instructions*.
|
|
ValueVector Loads;
|
|
ValueVector Stores;
|
|
|
|
// Holds all the different accesses in the loop.
|
|
unsigned NumReads = 0;
|
|
unsigned NumReadWrites = 0;
|
|
|
|
PtrRtCheck.Pointers.clear();
|
|
PtrRtCheck.Need = false;
|
|
|
|
const bool IsAnnotatedParallel = TheLoop->isAnnotatedParallel();
|
|
MemoryDepChecker DepChecker(SE, DL, TheLoop);
|
|
|
|
// For each block.
|
|
for (Loop::block_iterator bb = TheLoop->block_begin(),
|
|
be = TheLoop->block_end(); bb != be; ++bb) {
|
|
|
|
// Scan the BB and collect legal loads and stores.
|
|
for (BasicBlock::iterator it = (*bb)->begin(), e = (*bb)->end(); it != e;
|
|
++it) {
|
|
|
|
// If this is a load, save it. If this instruction can read from memory
|
|
// but is not a load, then we quit. Notice that we don't handle function
|
|
// calls that read or write.
|
|
if (it->mayReadFromMemory()) {
|
|
LoadInst *Ld = dyn_cast<LoadInst>(it);
|
|
if (!Ld) return false;
|
|
if (!Ld->isSimple() && !IsAnnotatedParallel) {
|
|
DEBUG(dbgs() << "LV: Found a non-simple load.\n");
|
|
return false;
|
|
}
|
|
Loads.push_back(Ld);
|
|
DepChecker.addAccess(Ld);
|
|
continue;
|
|
}
|
|
|
|
// Save 'store' instructions. Abort if other instructions write to memory.
|
|
if (it->mayWriteToMemory()) {
|
|
StoreInst *St = dyn_cast<StoreInst>(it);
|
|
if (!St) return false;
|
|
if (!St->isSimple() && !IsAnnotatedParallel) {
|
|
DEBUG(dbgs() << "LV: Found a non-simple store.\n");
|
|
return false;
|
|
}
|
|
Stores.push_back(St);
|
|
DepChecker.addAccess(St);
|
|
}
|
|
} // next instr.
|
|
} // next block.
|
|
|
|
// Now we have two lists that hold the loads and the stores.
|
|
// Next, we find the pointers that they use.
|
|
|
|
// Check if we see any stores. If there are no stores, then we don't
|
|
// care if the pointers are *restrict*.
|
|
if (!Stores.size()) {
|
|
DEBUG(dbgs() << "LV: Found a read-only loop!\n");
|
|
return true;
|
|
}
|
|
|
|
AccessAnalysis::DepCandidates DependentAccesses;
|
|
AccessAnalysis Accesses(DL, DependentAccesses);
|
|
|
|
// Holds the analyzed pointers. We don't want to call GetUnderlyingObjects
|
|
// multiple times on the same object. If the ptr is accessed twice, once
|
|
// for read and once for write, it will only appear once (on the write
|
|
// list). This is okay, since we are going to check for conflicts between
|
|
// writes and between reads and writes, but not between reads and reads.
|
|
ValueSet Seen;
|
|
|
|
ValueVector::iterator I, IE;
|
|
for (I = Stores.begin(), IE = Stores.end(); I != IE; ++I) {
|
|
StoreInst *ST = cast<StoreInst>(*I);
|
|
Value* Ptr = ST->getPointerOperand();
|
|
|
|
if (isUniform(Ptr)) {
|
|
DEBUG(dbgs() << "LV: We don't allow storing to uniform addresses\n");
|
|
return false;
|
|
}
|
|
|
|
// If we did *not* see this pointer before, insert it to the read-write
|
|
// list. At this phase it is only a 'write' list.
|
|
if (Seen.insert(Ptr)) {
|
|
++NumReadWrites;
|
|
Accesses.addStore(Ptr);
|
|
}
|
|
}
|
|
|
|
if (IsAnnotatedParallel) {
|
|
DEBUG(dbgs()
|
|
<< "LV: A loop annotated parallel, ignore memory dependency "
|
|
<< "checks.\n");
|
|
return true;
|
|
}
|
|
|
|
SmallPtrSet<Value *, 16> ReadOnlyPtr;
|
|
for (I = Loads.begin(), IE = Loads.end(); I != IE; ++I) {
|
|
LoadInst *LD = cast<LoadInst>(*I);
|
|
Value* Ptr = LD->getPointerOperand();
|
|
// If we did *not* see this pointer before, insert it to the
|
|
// read list. If we *did* see it before, then it is already in
|
|
// the read-write list. This allows us to vectorize expressions
|
|
// such as A[i] += x; Because the address of A[i] is a read-write
|
|
// pointer. This only works if the index of A[i] is consecutive.
|
|
// If the address of i is unknown (for example A[B[i]]) then we may
|
|
// read a few words, modify, and write a few words, and some of the
|
|
// words may be written to the same address.
|
|
bool IsReadOnlyPtr = false;
|
|
if (Seen.insert(Ptr) || !isStridedPtr(SE, DL, Ptr, TheLoop)) {
|
|
++NumReads;
|
|
IsReadOnlyPtr = true;
|
|
}
|
|
Accesses.addLoad(Ptr, IsReadOnlyPtr);
|
|
}
|
|
|
|
// If we write (or read-write) to a single destination and there are no
|
|
// other reads in this loop then is it safe to vectorize.
|
|
if (NumReadWrites == 1 && NumReads == 0) {
|
|
DEBUG(dbgs() << "LV: Found a write-only loop!\n");
|
|
return true;
|
|
}
|
|
|
|
// Build dependence sets and check whether we need a runtime pointer bounds
|
|
// check.
|
|
Accesses.buildDependenceSets();
|
|
bool NeedRTCheck = Accesses.isRTCheckNeeded();
|
|
|
|
// Find pointers with computable bounds. We are going to use this information
|
|
// to place a runtime bound check.
|
|
unsigned NumComparisons = 0;
|
|
bool CanDoRT = false;
|
|
if (NeedRTCheck)
|
|
CanDoRT = Accesses.canCheckPtrAtRT(PtrRtCheck, NumComparisons, SE, TheLoop);
|
|
|
|
|
|
DEBUG(dbgs() << "LV: We need to do " << NumComparisons <<
|
|
" pointer comparisons.\n");
|
|
|
|
// If we only have one set of dependences to check pointers among we don't
|
|
// need a runtime check.
|
|
if (NumComparisons == 0 && NeedRTCheck)
|
|
NeedRTCheck = false;
|
|
|
|
// Check that we did not collect too many pointers or found a unsizeable
|
|
// pointer.
|
|
if (!CanDoRT || NumComparisons > RuntimeMemoryCheckThreshold) {
|
|
PtrRtCheck.reset();
|
|
CanDoRT = false;
|
|
}
|
|
|
|
if (CanDoRT) {
|
|
DEBUG(dbgs() << "LV: We can perform a memory runtime check if needed.\n");
|
|
}
|
|
|
|
if (NeedRTCheck && !CanDoRT) {
|
|
DEBUG(dbgs() << "LV: We can't vectorize because we can't find " <<
|
|
"the array bounds.\n");
|
|
PtrRtCheck.reset();
|
|
return false;
|
|
}
|
|
|
|
PtrRtCheck.Need = NeedRTCheck;
|
|
|
|
bool CanVecMem = true;
|
|
if (Accesses.isDependencyCheckNeeded()) {
|
|
DEBUG(dbgs() << "LV: Checking memory dependencies\n");
|
|
CanVecMem = DepChecker.areDepsSafe(DependentAccesses,
|
|
Accesses.getDependenciesToCheck());
|
|
MaxSafeDepDistBytes = DepChecker.getMaxSafeDepDistBytes();
|
|
}
|
|
|
|
DEBUG(dbgs() << "LV: We "<< (NeedRTCheck ? "" : "don't") <<
|
|
" need a runtime memory check.\n");
|
|
|
|
return CanVecMem;
|
|
}
|
|
|
|
static bool hasMultipleUsesOf(Instruction *I,
|
|
SmallPtrSet<Instruction *, 8> &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, SmallPtrSet<Instruction *, 8> &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 = 0;
|
|
// 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, 0);
|
|
|
|
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 (Value::use_iterator UI = Cur->use_begin(), E = Cur->use_end(); UI != E;
|
|
++UI) {
|
|
Instruction *Usr = cast<Instruction>(*UI);
|
|
|
|
// Check if we found the exit user.
|
|
BasicBlock *Parent = Usr->getParent();
|
|
if (!TheLoop->contains(Parent)) {
|
|
// Exit if you find multiple outside users.
|
|
if (ExitInstruction != 0)
|
|
return false;
|
|
ExitInstruction = Cur;
|
|
continue;
|
|
}
|
|
|
|
// Process instructions only once (termination).
|
|
if (VisitedInsts.insert(Usr)) {
|
|
if (isa<PHINode>(Usr))
|
|
PHIs.push_back(Usr);
|
|
else
|
|
NonPHIs.push_back(Usr);
|
|
}
|
|
// Remember that we completed the cycle.
|
|
if (Usr == 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 = 0;
|
|
SelectInst *Select = 0;
|
|
|
|
// 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->use_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->isCommutative() && I->isAssociative());
|
|
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::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) {
|
|
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);
|
|
|
|
// Integer inductions need to have a stride of one.
|
|
if (PhiTy->isIntegerTy()) {
|
|
if (Step->isOne())
|
|
return IK_IntInduction;
|
|
if (Step->isAllOnesValue())
|
|
return IK_ReverseIntInduction;
|
|
return IK_NoInduction;
|
|
}
|
|
|
|
// Calculate the pointer stride and check if it is consecutive.
|
|
const SCEVConstant *C = dyn_cast<SCEVConstant>(Step);
|
|
if (!C)
|
|
return IK_NoInduction;
|
|
|
|
assert(PhiTy->isPointerTy() && "The PHI must be a pointer");
|
|
uint64_t Size = DL->getTypeAllocSize(PhiTy->getPointerElementType());
|
|
if (C->getValue()->equalsInt(Size))
|
|
return IK_PtrInduction;
|
|
else if (C->getValue()->equalsInt(0 - Size))
|
|
return IK_ReversePtrInduction;
|
|
|
|
return IK_NoInduction;
|
|
}
|
|
|
|
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) {
|
|
assert(TheLoop->contains(BB) && "Unknown block used");
|
|
|
|
// Blocks that do not dominate the latch need predication.
|
|
BasicBlock* Latch = TheLoop->getLoopLatch();
|
|
return !DT->dominates(BB, Latch);
|
|
}
|
|
|
|
bool LoopVectorizationLegality::blockCanBePredicated(BasicBlock *BB,
|
|
SmallPtrSet<Value *, 8>& SafePtrs) {
|
|
for (BasicBlock::iterator it = BB->begin(), e = BB->end(); it != e; ++it) {
|
|
// We might be able to hoist the load.
|
|
if (it->mayReadFromMemory()) {
|
|
LoadInst *LI = dyn_cast<LoadInst>(it);
|
|
if (!LI || !SafePtrs.count(LI->getPointerOperand()))
|
|
return false;
|
|
}
|
|
|
|
// We don't predicate stores at the moment.
|
|
if (it->mayWriteToMemory() || 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,
|
|
unsigned UserVF) {
|
|
// Width 1 means no vectorize
|
|
VectorizationFactor Factor = { 1U, 0U };
|
|
if (OptForSize && Legal->getRuntimePointerCheck()->Need) {
|
|
DEBUG(dbgs() << "LV: Aborting. Runtime ptr check is required in Os.\n");
|
|
return Factor;
|
|
}
|
|
|
|
// Find the trip count.
|
|
unsigned TC = SE->getSmallConstantTripCount(TheLoop, TheLoop->getLoopLatch());
|
|
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 <= 32 && "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) {
|
|
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) {
|
|
DEBUG(dbgs() << "LV: Aborting. A tail loop is required in Os.\n");
|
|
return Factor;
|
|
}
|
|
}
|
|
|
|
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);
|
|
unsigned Width = 1;
|
|
DEBUG(dbgs() << "LV: Scalar loop costs: "<< (int)Cost << ".\n");
|
|
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(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();
|
|
|
|
// 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 UserUF,
|
|
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 the 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.
|
|
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,
|
|
TheLoop->getLoopLatch());
|
|
if (TC > 1 && TC < TinyTripCountUnrollThreshold)
|
|
return 1;
|
|
|
|
unsigned TargetVectorRegisters = TTI.getNumberOfRegisters(true);
|
|
DEBUG(dbgs() << "LV: The target has " << TargetVectorRegisters <<
|
|
" vector registers\n");
|
|
|
|
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.
|
|
unsigned UF = (TargetVectorRegisters - R.LoopInvariantRegs) / R.MaxLocalUsers;
|
|
|
|
// Clamp the unroll factor ranges to reasonable factors.
|
|
unsigned MaxUnrollSize = TTI.getMaximumUnrollFactor();
|
|
|
|
// 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 > MaxUnrollSize)
|
|
UF = MaxUnrollSize;
|
|
else if (UF < 1)
|
|
UF = 1;
|
|
|
|
if (Legal->getReductionVars()->size()) {
|
|
DEBUG(dbgs() << "LV: Unrolling because of reductions. \n");
|
|
return UF;
|
|
}
|
|
|
|
// We want to unroll tiny loops in order to reduce the loop overhead.
|
|
// 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.
|
|
DEBUG(dbgs() << "LV: Loop cost is "<< LoopCost <<" \n");
|
|
if (LoopCost < 20) {
|
|
DEBUG(dbgs() << "LV: Unrolling to reduce branch cost. \n");
|
|
unsigned NewUF = 20/LoopCost + 1;
|
|
return std::min(NewUF, UF);
|
|
}
|
|
|
|
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;
|
|
|
|
// 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;
|
|
|
|
unsigned C = getInstructionCost(it, VF);
|
|
Cost += 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 (Legal->blockNeedsPredication(*bb) && VF == 1)
|
|
BlockCost /= 2;
|
|
|
|
Cost += BlockCost;
|
|
}
|
|
|
|
return Cost;
|
|
}
|
|
|
|
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: {
|
|
// 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;
|
|
|
|
if (isa<ConstantInt>(I->getOperand(1)))
|
|
Op2VK = TargetTransformInfo::OK_UniformConstantValue;
|
|
|
|
return TTI.getArithmeticInstrCost(I->getOpcode(), VectorTy, Op1VK, Op2VK);
|
|
}
|
|
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) {
|
|
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(ValTy->getScalarType());
|
|
Cost += VF * TTI.getMemoryOpCost(I->getOpcode(), ValTy->getScalarType(),
|
|
Alignment, AS);
|
|
return Cost;
|
|
}
|
|
|
|
// Wide load/stores.
|
|
unsigned Cost = TTI.getAddressComputationCost(VectorTy);
|
|
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_AG_DEPENDENCY(TargetTransformInfo)
|
|
INITIALIZE_PASS_DEPENDENCY(ScalarEvolution)
|
|
INITIALIZE_PASS_DEPENDENCY(LoopSimplify)
|
|
INITIALIZE_PASS_END(LoopVectorize, LV_NAME, lv_name, false, false)
|
|
|
|
namespace llvm {
|
|
Pass *createLoopVectorizePass() {
|
|
return new LoopVectorize();
|
|
}
|
|
}
|
|
|
|
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;
|
|
}
|