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If the arrays are found to be disjoint then we run the vectorized version of the loop. If they are not, we run the scalar code. git-svn-id: https://llvm.org/svn/llvm-project/llvm/trunk@167608 91177308-0d34-0410-b5e6-96231b3b80d8
1941 lines
71 KiB
C++
1941 lines
71 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. Legalization of the IR is done
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// in the codegen. However, the vectorizes uses (will use) the codegen
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// interfaces to generate IR that is likely to result in an optimal binary.
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//
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// The loop vectorizer combines consecutive loop iteration 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. SingleBlockLoopVectorizer - 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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// 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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//===----------------------------------------------------------------------===//
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#define LV_NAME "loop-vectorize"
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#define DEBUG_TYPE LV_NAME
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#include "llvm/Constants.h"
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#include "llvm/DerivedTypes.h"
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#include "llvm/Instructions.h"
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#include "llvm/LLVMContext.h"
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#include "llvm/Pass.h"
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#include "llvm/Analysis/LoopPass.h"
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#include "llvm/Value.h"
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#include "llvm/Function.h"
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#include "llvm/Analysis/Verifier.h"
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#include "llvm/Module.h"
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#include "llvm/Type.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/AliasSetTracker.h"
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#include "llvm/Analysis/ScalarEvolution.h"
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#include "llvm/Analysis/Dominators.h"
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#include "llvm/Analysis/ScalarEvolutionExpressions.h"
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#include "llvm/Analysis/ScalarEvolutionExpander.h"
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#include "llvm/Analysis/LoopInfo.h"
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#include "llvm/Analysis/ValueTracking.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/TargetTransformInfo.h"
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#include "llvm/Support/CommandLine.h"
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#include "llvm/Support/Debug.h"
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#include "llvm/Support/raw_ostream.h"
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#include "llvm/DataLayout.h"
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#include "llvm/Transforms/Utils/Local.h"
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#include <algorithm>
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using namespace llvm;
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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("Set the default vectorization width. Zero is autoselect."));
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/// We don't vectorize loops with a known constant trip count below this number.
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const unsigned TinyTripCountThreshold = 16;
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/// When performing a runtime memory check, do not check more than this
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/// numner of pointers. Notice that the check is quadratic!
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const unsigned RuntimeMemoryCheckThreshold = 2;
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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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/// SingleBlockLoopVectorizer 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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/// SingleBlockLoopVectorizer 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 SingleBlockLoopVectorizer 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 SingleBlockLoopVectorizer {
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public:
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/// Ctor.
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SingleBlockLoopVectorizer(Loop *Orig, ScalarEvolution *Se, LoopInfo *Li,
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DominatorTree *dt, LPPassManager *Lpm,
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unsigned VecWidth):
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OrigLoop(Orig), SE(Se), LI(Li), DT(dt), LPM(Lpm), VF(VecWidth),
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Builder(Se->getContext()), Induction(0), OldInduction(0) { }
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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.
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updateAnalysis();
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}
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private:
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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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/// Insert the new loop to the loop hierarchy and pass manager.
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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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/// 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 is a helper function used by getBroadcastInstrs. It adds 0, 1, 2 ..
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/// for each element in the vector. Starting from zero.
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Value *getConsecutiveVector(Value* Val);
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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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Value *getVectorValue(Value *V);
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/// Get a uniform vector of constant integers. We use this to get
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/// vectors of ones and zeros for the reduction code.
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Constant* getUniformVector(unsigned Val, Type* ScalarTy);
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typedef DenseMap<Value*, Value*> ValueMap;
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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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// Loop Pass Manager;
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LPPassManager *LPM;
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// The vectorization factor to use.
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unsigned VF;
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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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///The first bypass block.
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BasicBlock *LoopBypassBlock;
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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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// Maps scalars to widened vectors.
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ValueMap WidenMap;
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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 canVectorizeBlock checks for a number
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/// of different conditions, such as the availability of a single induction
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/// variable, that all types are supported and vectorize-able, etc.
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/// This code reflects the capabilities of SingleBlockLoopVectorizer.
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/// This class is also used by SingleBlockLoopVectorizer 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 *Lp, ScalarEvolution *Se, DataLayout *Dl):
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TheLoop(Lp), SE(Se), DL(Dl), Induction(0) { }
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/// This represents the kinds of reductions that we support.
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enum ReductionKind {
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NoReduction, /// Not a reduction.
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IntegerAdd, /// Sum of numbers.
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IntegerMult, /// Product of numbers.
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IntegerOr, /// Bitwise or logical OR of numbers.
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IntegerAnd, /// Bitwise or logical AND of numbers.
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IntegerXor /// Bitwise or logical XOR of numbers.
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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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// Default C'tor
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ReductionDescriptor():
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StartValue(0), LoopExitInstr(0), Kind(NoReduction) {}
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// C'tor.
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ReductionDescriptor(Value *Start, Instruction *Exit, ReductionKind K):
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StartValue(Start), LoopExitInstr(Exit), Kind(K) {}
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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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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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};
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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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/// 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<Value*, 2> Pointers;
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};
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/// ReductionList contains the reduction descriptors for all
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/// of the reductions that were found in the loop.
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typedef DenseMap<PHINode*, ReductionDescriptor> ReductionList;
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/// Returns true if it is legal to vectorize this loop.
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/// This does not mean that it is profitable to vectorize this
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/// loop, only that it is legal to do so.
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bool canVectorize();
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/// Returns the Induction variable.
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PHINode *getInduction() {return Induction;}
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/// Returns the reduction variables found in the loop.
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ReductionList *getReductionVars() { return &Reductions; }
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/// Check if the pointer returned by this GEP is consecutive
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/// when the index is vectorized. This happens when the last
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/// index of the GEP is consecutive, like the induction variable.
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/// This check allows us to vectorize A[idx] into a wide load/store.
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bool isConsecutiveGep(Value *Ptr);
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/// Returns true if the value V is uniform within the loop.
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bool isUniform(Value *V);
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/// Returns true if this instruction will remain scalar after vectorization.
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bool isUniformAfterVectorization(Instruction* I) {return Uniforms.count(I);}
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/// Returns the information that we collected about runtime memory check.
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RuntimePointerCheck *getRuntimePointerCheck() {return &PtrRtCheck; }
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private:
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/// Check if a single basic block loop is vectorizable.
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/// At this point we know that this is a loop with a constant trip count
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/// and we only need to check individual instructions.
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bool canVectorizeBlock(BasicBlock &BB);
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/// When we vectorize loops we may change the order in which
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/// we read and write from memory. This method checks if it is
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/// legal to vectorize the code, considering only memory constrains.
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/// Returns true if BB is vectorizable
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bool canVectorizeMemory(BasicBlock &BB);
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/// Returns True, if 'Phi' is the kind of reduction variable for type
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/// 'Kind'. If this is a reduction variable, it adds it to ReductionList.
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bool AddReductionVar(PHINode *Phi, ReductionKind Kind);
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/// Returns true if the instruction I can be a reduction variable of type
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/// 'Kind'.
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bool isReductionInstr(Instruction *I, ReductionKind Kind);
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/// Returns True, if 'Phi' is an induction variable.
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bool isInductionVariable(PHINode *Phi);
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/// Return true if we
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bool hasComputableBounds(Value *Ptr);
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/// The loop that we evaluate.
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Loop *TheLoop;
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/// Scev analysis.
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ScalarEvolution *SE;
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/// DataLayout analysis.
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DataLayout *DL;
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// --- vectorization state --- //
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/// Holds the induction variable.
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PHINode *Induction;
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/// Holds the reduction variables.
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ReductionList Reductions;
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/// Allowed outside users. This holds the reduction
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/// vars which can be accessed from outside the loop.
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SmallPtrSet<Value*, 4> AllowedExit;
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/// This set holds the variables which are known to be uniform after
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/// vectorization.
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SmallPtrSet<Instruction*, 4> Uniforms;
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/// We need to check that all of the pointers in this list are disjoint
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/// at runtime.
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RuntimePointerCheck PtrRtCheck;
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};
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/// LoopVectorizationCostModel - estimates the expected speedups due to
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/// vectorization.
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/// In many cases vectorization is not profitable. This can happen because
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/// of a number of reasons. In this class we mainly attempt to predict
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/// the expected speedup/slowdowns due to the supported instruction set.
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/// We use the VectorTargetTransformInfo to query the different backends
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/// for the cost of different operations.
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class LoopVectorizationCostModel {
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public:
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/// C'tor.
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LoopVectorizationCostModel(Loop *Lp, ScalarEvolution *Se,
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LoopVectorizationLegality *Leg,
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const VectorTargetTransformInfo *Vtti):
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TheLoop(Lp), SE(Se), Legal(Leg), VTTI(Vtti) { }
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/// Returns the most profitable vectorization factor for the loop that is
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/// smaller or equal to the VF argument. This method checks every power
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/// of two up to VF.
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unsigned findBestVectorizationFactor(unsigned VF = 8);
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private:
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/// Returns the expected execution cost. The unit of the cost does
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/// not matter because we use the 'cost' units to compare different
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/// vector widths. The cost that is returned is *not* normalized by
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/// the factor width.
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unsigned expectedCost(unsigned VF);
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/// Returns the execution time cost of an instruction for a given vector
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/// width. Vector width of one means scalar.
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unsigned getInstructionCost(Instruction *I, unsigned VF);
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/// A helper function for converting Scalar types to vector types.
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/// If the incoming type is void, we return void. If the VF is 1, we return
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/// the scalar type.
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static Type* ToVectorTy(Type *Scalar, unsigned VF);
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/// The loop that we evaluate.
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Loop *TheLoop;
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/// Scev analysis.
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ScalarEvolution *SE;
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/// Vectorization legality.
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LoopVectorizationLegality *Legal;
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/// Vector target information.
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const VectorTargetTransformInfo *VTTI;
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};
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struct LoopVectorize : public LoopPass {
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static char ID; // Pass identification, replacement for typeid
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LoopVectorize() : LoopPass(ID) {
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initializeLoopVectorizePass(*PassRegistry::getPassRegistry());
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}
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ScalarEvolution *SE;
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DataLayout *DL;
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LoopInfo *LI;
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TargetTransformInfo *TTI;
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DominatorTree *DT;
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virtual bool runOnLoop(Loop *L, LPPassManager &LPM) {
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// We only vectorize innermost loops.
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if (!L->empty())
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return false;
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SE = &getAnalysis<ScalarEvolution>();
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DL = getAnalysisIfAvailable<DataLayout>();
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LI = &getAnalysis<LoopInfo>();
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TTI = getAnalysisIfAvailable<TargetTransformInfo>();
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DT = &getAnalysis<DominatorTree>();
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DEBUG(dbgs() << "LV: Checking a loop in \"" <<
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L->getHeader()->getParent()->getName() << "\"\n");
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// Check if it is legal to vectorize the loop.
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LoopVectorizationLegality LVL(L, SE, DL);
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if (!LVL.canVectorize()) {
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DEBUG(dbgs() << "LV: Not vectorizing.\n");
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return false;
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}
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// Select the preffered vectorization factor.
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unsigned VF = 1;
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if (VectorizationFactor == 0) {
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const VectorTargetTransformInfo *VTTI = 0;
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if (TTI)
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VTTI = TTI->getVectorTargetTransformInfo();
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// Use the cost model.
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LoopVectorizationCostModel CM(L, SE, &LVL, VTTI);
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VF = CM.findBestVectorizationFactor();
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if (VF == 1) {
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DEBUG(dbgs() << "LV: Vectorization is possible but not beneficial.\n");
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return false;
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}
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} else {
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// Use the user command flag.
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VF = VectorizationFactor;
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}
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DEBUG(dbgs() << "LV: Found a vectorizable loop ("<< VF << ") in "<<
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L->getHeader()->getParent()->getParent()->getModuleIdentifier()<<
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"\n");
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// If we decided that it is *legal* to vectorizer the loop then do it.
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SingleBlockLoopVectorizer LB(L, SE, LI, DT, &LPM, VF);
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LB.vectorize(&LVL);
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DEBUG(verifyFunction(*L->getHeader()->getParent()));
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return true;
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}
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virtual void getAnalysisUsage(AnalysisUsage &AU) const {
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LoopPass::getAnalysisUsage(AU);
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AU.addRequiredID(LoopSimplifyID);
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AU.addRequiredID(LCSSAID);
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AU.addRequired<LoopInfo>();
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AU.addRequired<ScalarEvolution>();
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AU.addRequired<DominatorTree>();
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AU.addPreserved<LoopInfo>();
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AU.addPreserved<DominatorTree>();
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}
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};
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Value *SingleBlockLoopVectorizer::getBroadcastInstrs(Value *V) {
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// Instructions that access the old induction variable
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// actually want to get the new one.
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if (V == OldInduction)
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V = Induction;
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// Create the types.
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LLVMContext &C = V->getContext();
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Type *VTy = VectorType::get(V->getType(), VF);
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Type *I32 = IntegerType::getInt32Ty(C);
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Constant *Zero = ConstantInt::get(I32, 0);
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Value *Zeros = ConstantAggregateZero::get(VectorType::get(I32, VF));
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Value *UndefVal = UndefValue::get(VTy);
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// Insert the value into a new vector.
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Value *SingleElem = Builder.CreateInsertElement(UndefVal, V, Zero);
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// Broadcast the scalar into all locations in the vector.
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Value *Shuf = Builder.CreateShuffleVector(SingleElem, UndefVal, Zeros,
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"broadcast");
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// We are accessing the induction variable. Make sure to promote the
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// index for each consecutive SIMD lane. This adds 0,1,2 ... to all lanes.
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if (V == Induction)
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return getConsecutiveVector(Shuf);
|
|
return Shuf;
|
|
}
|
|
|
|
Value *SingleBlockLoopVectorizer::getConsecutiveVector(Value* Val) {
|
|
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());
|
|
unsigned VLen = Ty->getNumElements();
|
|
SmallVector<Constant*, 8> Indices;
|
|
|
|
// Create a vector of consecutive numbers from zero to VF.
|
|
for (unsigned i = 0; i < VLen; ++i)
|
|
Indices.push_back(ConstantInt::get(ITy, i));
|
|
|
|
// 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");
|
|
}
|
|
|
|
bool LoopVectorizationLegality::isConsecutiveGep(Value *Ptr) {
|
|
GetElementPtrInst *Gep = dyn_cast_or_null<GetElementPtrInst>(Ptr);
|
|
if (!Gep)
|
|
return false;
|
|
|
|
unsigned NumOperands = Gep->getNumOperands();
|
|
Value *LastIndex = Gep->getOperand(NumOperands - 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 false;
|
|
|
|
// We can emit wide load/stores only of 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 true;
|
|
}
|
|
|
|
return false;
|
|
}
|
|
|
|
bool LoopVectorizationLegality::isUniform(Value *V) {
|
|
return (SE->isLoopInvariant(SE->getSCEV(V), TheLoop));
|
|
}
|
|
|
|
Value *SingleBlockLoopVectorizer::getVectorValue(Value *V) {
|
|
assert(!V->getType()->isVectorTy() && "Can't widen a vector");
|
|
// If we saved a vectorized copy of V, use it.
|
|
Value *&MapEntry = WidenMap[V];
|
|
if (MapEntry)
|
|
return MapEntry;
|
|
|
|
// Broadcast V and save the value for future uses.
|
|
Value *B = getBroadcastInstrs(V);
|
|
MapEntry = B;
|
|
return B;
|
|
}
|
|
|
|
Constant*
|
|
SingleBlockLoopVectorizer::getUniformVector(unsigned Val, Type* ScalarTy) {
|
|
SmallVector<Constant*, 8> Indices;
|
|
// Create a vector of consecutive numbers from zero to VF.
|
|
for (unsigned i = 0; i < VF; ++i)
|
|
Indices.push_back(ConstantInt::get(ScalarTy, Val, true));
|
|
|
|
// Add the consecutive indices to the vector value.
|
|
return ConstantVector::get(Indices);
|
|
}
|
|
|
|
void SingleBlockLoopVectorizer::scalarizeInstruction(Instruction *Instr) {
|
|
assert(!Instr->getType()->isAggregateType() && "Can't handle vectors");
|
|
// Holds vector parameters or scalars, in case of uniform vals.
|
|
SmallVector<Value*, 8> Params;
|
|
|
|
// 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(getBroadcastInstrs(Induction));
|
|
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 && SrcInst->getParent() == Instr->getParent()) {
|
|
assert(WidenMap.count(SrcInst) && "Source operand is unavailable");
|
|
// The parameter is a vector value from earlier.
|
|
Params.push_back(WidenMap[SrcInst]);
|
|
} else {
|
|
// The parameter is a scalar from outside the loop. Maybe even a constant.
|
|
Params.push_back(SrcOp);
|
|
}
|
|
}
|
|
|
|
assert(Params.size() == Instr->getNumOperands() &&
|
|
"Invalid number of operands");
|
|
|
|
// Does this instruction return a value ?
|
|
bool IsVoidRetTy = Instr->getType()->isVoidTy();
|
|
Value *VecResults = 0;
|
|
|
|
// If we have a return value, create an empty vector. We place the scalarized
|
|
// instructions in this vector.
|
|
if (!IsVoidRetTy)
|
|
VecResults = UndefValue::get(VectorType::get(Instr->getType(), VF));
|
|
|
|
// For each scalar that we create:
|
|
for (unsigned i = 0; i < VF; ++i) {
|
|
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];
|
|
// Param is a vector. Need to extract the right lane.
|
|
if (Op->getType()->isVectorTy())
|
|
Op = Builder.CreateExtractElement(Op, Builder.getInt32(i));
|
|
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 = Builder.CreateInsertElement(VecResults, Cloned,
|
|
Builder.getInt32(i));
|
|
}
|
|
|
|
if (!IsVoidRetTy)
|
|
WidenMap[Instr] = VecResults;
|
|
}
|
|
|
|
void
|
|
SingleBlockLoopVectorizer::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.
|
|
/ |
|
|
/ v
|
|
| [ ] <-- vector pre header.
|
|
| |
|
|
| v
|
|
| [ ] \
|
|
| [ ]_| <-- vector loop.
|
|
| |
|
|
\ v
|
|
>[ ] <--- middle-block.
|
|
/ |
|
|
/ v
|
|
| [ ] <--- new preheader.
|
|
| |
|
|
| v
|
|
| [ ] \
|
|
| [ ]_| <-- old scalar loop to handle remainder.
|
|
\ |
|
|
\ v
|
|
>[ ] <-- exit block.
|
|
...
|
|
*/
|
|
|
|
OldInduction = Legal->getInduction();
|
|
assert(OldInduction && "We must have a single phi node.");
|
|
Type *IdxTy = OldInduction->getType();
|
|
|
|
// Find the loop boundaries.
|
|
const SCEV *ExitCount = SE->getExitCount(OrigLoop, OrigLoop->getHeader());
|
|
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));
|
|
// 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.
|
|
// We are using Zext because it should be less expensive.
|
|
if (ExitCount->getType() != IdxTy)
|
|
ExitCount = SE->getZeroExtendExpr(ExitCount, IdxTy);
|
|
|
|
// This is the original scalar-loop preheader.
|
|
BasicBlock *BypassBlock = OrigLoop->getLoopPreheader();
|
|
BasicBlock *ExitBlock = OrigLoop->getExitBlock();
|
|
assert(ExitBlock && "Must have an exit block");
|
|
|
|
// The loop index does not have to start at Zero. It starts with this value.
|
|
Value *StartIdx = OldInduction->getIncomingValueForBlock(BypassBlock);
|
|
|
|
assert(OrigLoop->getNumBlocks() == 1 && "Invalid loop");
|
|
assert(BypassBlock && "Invalid loop structure");
|
|
|
|
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.preheader");
|
|
// Find the induction variable.
|
|
BasicBlock *OldBasicBlock = OrigLoop->getHeader();
|
|
|
|
// Use this IR builder to create the loop instructions (Phi, Br, Cmp)
|
|
// inside the loop.
|
|
Builder.SetInsertPoint(VecBody->getFirstInsertionPt());
|
|
|
|
// Generate the induction variable.
|
|
Induction = Builder.CreatePHI(IdxTy, 2, "index");
|
|
Constant *Step = ConstantInt::get(IdxTy, VF);
|
|
|
|
// 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");
|
|
Instruction *Loc = BypassBlock->getTerminator();
|
|
|
|
// Count holds the overall loop count (N).
|
|
Value *Count = Exp.expandCodeFor(ExitCount, Induction->getType(), Loc);
|
|
|
|
// Add the start index to the loop count to get the new end index.
|
|
Value *IdxEnd = BinaryOperator::CreateAdd(Count, StartIdx, "end.idx", Loc);
|
|
|
|
// Now we need to generate the expression for N - (N % VF), which is
|
|
// the part that the vectorized body will execute.
|
|
Constant *CIVF = ConstantInt::get(IdxTy, VF);
|
|
Value *R = BinaryOperator::CreateURem(Count, CIVF, "n.mod.vf", Loc);
|
|
Value *CountRoundDown = BinaryOperator::CreateSub(Count, R, "n.vec", Loc);
|
|
Value *IdxEndRoundDown = BinaryOperator::CreateAdd(CountRoundDown, StartIdx,
|
|
"end.idx.rnd.down", Loc);
|
|
|
|
// Now, compare the new count to zero. If it is zero, jump to the scalar part.
|
|
Value *Cmp = CmpInst::Create(Instruction::ICmp, CmpInst::ICMP_EQ,
|
|
IdxEndRoundDown,
|
|
StartIdx,
|
|
"cmp.zero", Loc);
|
|
|
|
LoopVectorizationLegality::RuntimePointerCheck *PtrRtCheck =
|
|
Legal->getRuntimePointerCheck();
|
|
Value *MemoryRuntimeCheck = 0;
|
|
if (PtrRtCheck->Need) {
|
|
unsigned NumPointers = PtrRtCheck->Pointers.size();
|
|
SmallVector<Value* , 2> Starts;
|
|
SmallVector<Value* , 2> Ends;
|
|
|
|
// Use this type for pointer arithmetic.
|
|
Type* PtrArithTy = PtrRtCheck->Pointers[0]->getType();
|
|
|
|
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() << "LV1: 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");
|
|
const SCEVAddRecExpr *AR = dyn_cast<SCEVAddRecExpr>(Sc);
|
|
Value *Start = Exp.expandCodeFor(AR->getStart(), PtrArithTy, Loc);
|
|
const SCEV *Ex = SE->getExitCount(OrigLoop, OrigLoop->getHeader());
|
|
const SCEV *ScEnd = AR->evaluateAtIteration(Ex, *SE);
|
|
assert(!isa<SCEVCouldNotCompute>(ScEnd) && "Invalid scev range.");
|
|
Value *End = Exp.expandCodeFor(ScEnd, PtrArithTy, Loc);
|
|
Starts.push_back(Start);
|
|
Ends.push_back(End);
|
|
}
|
|
}
|
|
|
|
for (unsigned i=0; i < NumPointers; ++i) {
|
|
for (unsigned j=i+1; j < NumPointers; ++j) {
|
|
Value *Cmp0 = CmpInst::Create(Instruction::ICmp, CmpInst::ICMP_ULE,
|
|
Starts[0], Ends[1], "bound0", Loc);
|
|
Value *Cmp1 = CmpInst::Create(Instruction::ICmp, CmpInst::ICMP_ULE,
|
|
Starts[1], Ends[0], "bound1", Loc);
|
|
Value *IsConflict = BinaryOperator::Create(Instruction::And, Cmp0, Cmp1,
|
|
"found.conflict", Loc);
|
|
if (MemoryRuntimeCheck) {
|
|
MemoryRuntimeCheck = BinaryOperator::Create(Instruction::Or,
|
|
MemoryRuntimeCheck,
|
|
IsConflict,
|
|
"conflict.rdx", Loc);
|
|
} else {
|
|
MemoryRuntimeCheck = IsConflict;
|
|
}
|
|
}
|
|
}
|
|
}// end of need-runtime-check code.
|
|
|
|
// If we are using memory runtime checks, include them in.
|
|
if (MemoryRuntimeCheck) {
|
|
Cmp = BinaryOperator::Create(Instruction::Or, Cmp, MemoryRuntimeCheck,
|
|
"CntOrMem", Loc);
|
|
}
|
|
|
|
BranchInst::Create(MiddleBlock, VectorPH, Cmp, Loc);
|
|
// Remove the old terminator.
|
|
Loc->eraseFromParent();
|
|
|
|
// We are going to resume the execution of the scalar loop.
|
|
// This PHI decides on what number to start. If we come from the
|
|
// vector loop then we need to start with the end index minus the
|
|
// index modulo VF. If we come from a bypass edge then we need to start
|
|
// from the real start.
|
|
PHINode* ResumeIndex = PHINode::Create(IdxTy, 2, "resume.idx",
|
|
MiddleBlock->getTerminator());
|
|
ResumeIndex->addIncoming(StartIdx, BypassBlock);
|
|
ResumeIndex->addIncoming(IdxEndRoundDown, VecBody);
|
|
|
|
// 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();
|
|
|
|
// Fix the scalar body iteration count.
|
|
unsigned BlockIdx = OldInduction->getBasicBlockIndex(ScalarPH);
|
|
OldInduction->setIncomingValue(BlockIdx, ResumeIndex);
|
|
|
|
// Get ready to start creating new instructions into the vectorized body.
|
|
Builder.SetInsertPoint(VecBody->getFirstInsertionPt());
|
|
|
|
// Register the new loop.
|
|
Loop* Lp = new Loop();
|
|
LPM->insertLoop(Lp, OrigLoop->getParentLoop());
|
|
|
|
Lp->addBasicBlockToLoop(VecBody, LI->getBase());
|
|
|
|
Loop *ParentLoop = OrigLoop->getParentLoop();
|
|
if (ParentLoop) {
|
|
ParentLoop->addBasicBlockToLoop(ScalarPH, LI->getBase());
|
|
ParentLoop->addBasicBlockToLoop(VectorPH, LI->getBase());
|
|
ParentLoop->addBasicBlockToLoop(MiddleBlock, LI->getBase());
|
|
}
|
|
|
|
// Save the state.
|
|
LoopVectorPreHeader = VectorPH;
|
|
LoopScalarPreHeader = ScalarPH;
|
|
LoopMiddleBlock = MiddleBlock;
|
|
LoopExitBlock = ExitBlock;
|
|
LoopVectorBody = VecBody;
|
|
LoopScalarBody = OldBasicBlock;
|
|
LoopBypassBlock = BypassBlock;
|
|
}
|
|
|
|
/// This function returns the identity element (or neutral element) for
|
|
/// the operation K.
|
|
static unsigned
|
|
getReductionIdentity(LoopVectorizationLegality::ReductionKind K) {
|
|
switch (K) {
|
|
case LoopVectorizationLegality::IntegerXor:
|
|
case LoopVectorizationLegality::IntegerAdd:
|
|
case LoopVectorizationLegality::IntegerOr:
|
|
// Adding, Xoring, Oring zero to a number does not change it.
|
|
return 0;
|
|
case LoopVectorizationLegality::IntegerMult:
|
|
// Multiplying a number by 1 does not change it.
|
|
return 1;
|
|
case LoopVectorizationLegality::IntegerAnd:
|
|
// AND-ing a number with an all-1 value does not change it.
|
|
return -1;
|
|
default:
|
|
llvm_unreachable("Unknown reduction kind");
|
|
}
|
|
}
|
|
|
|
void
|
|
SingleBlockLoopVectorizer::vectorizeLoop(LoopVectorizationLegality *Legal) {
|
|
//===------------------------------------------------===//
|
|
//
|
|
// Notice: any optimization or new instruction that go
|
|
// into the code below should be also be implemented in
|
|
// the cost-model.
|
|
//
|
|
//===------------------------------------------------===//
|
|
typedef SmallVector<PHINode*, 4> PhiVector;
|
|
BasicBlock &BB = *OrigLoop->getHeader();
|
|
Constant *Zero = ConstantInt::get(
|
|
IntegerType::getInt32Ty(BB.getContext()), 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
|
|
// steages. 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 PHIsToFix;
|
|
|
|
// For each instruction in the old loop.
|
|
for (BasicBlock::iterator it = BB.begin(), e = BB.end(); it != e; ++it) {
|
|
Instruction *Inst = it;
|
|
|
|
switch (Inst->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>(Inst);
|
|
// Special handling for the induction var.
|
|
if (OldInduction == Inst)
|
|
continue;
|
|
// This is phase one of vectorizing PHIs.
|
|
// This has to be a reduction variable.
|
|
assert(Legal->getReductionVars()->count(P) && "Not a Reduction");
|
|
Type *VecTy = VectorType::get(Inst->getType(), VF);
|
|
WidenMap[Inst] = Builder.CreatePHI(VecTy, 2, "vec.phi");
|
|
PHIsToFix.push_back(P);
|
|
continue;
|
|
}
|
|
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>(Inst);
|
|
Value *A = getVectorValue(Inst->getOperand(0));
|
|
Value *B = getVectorValue(Inst->getOperand(1));
|
|
|
|
// Use this vector value for all users of the original instruction.
|
|
Value *V = Builder.CreateBinOp(BinOp->getOpcode(), A, B);
|
|
WidenMap[Inst] = V;
|
|
|
|
// Update the NSW, NUW and Exact flags.
|
|
BinaryOperator *VecOp = cast<BinaryOperator>(V);
|
|
if (isa<OverflowingBinaryOperator>(BinOp)) {
|
|
VecOp->setHasNoSignedWrap(BinOp->hasNoSignedWrap());
|
|
VecOp->setHasNoUnsignedWrap(BinOp->hasNoUnsignedWrap());
|
|
}
|
|
if (isa<PossiblyExactOperator>(VecOp))
|
|
VecOp->setIsExact(BinOp->isExact());
|
|
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.
|
|
Value *Cond = Inst->getOperand(0);
|
|
bool InvariantCond = SE->isLoopInvariant(SE->getSCEV(Cond), OrigLoop);
|
|
|
|
// 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.
|
|
Cond = getVectorValue(Cond);
|
|
if (InvariantCond)
|
|
Cond = Builder.CreateExtractElement(Cond, Builder.getInt32(0));
|
|
|
|
Value *Op0 = getVectorValue(Inst->getOperand(1));
|
|
Value *Op1 = getVectorValue(Inst->getOperand(2));
|
|
WidenMap[Inst] = Builder.CreateSelect(Cond, Op0, Op1);
|
|
break;
|
|
}
|
|
|
|
case Instruction::ICmp:
|
|
case Instruction::FCmp: {
|
|
// Widen compares. Generate vector compares.
|
|
bool FCmp = (Inst->getOpcode() == Instruction::FCmp);
|
|
CmpInst *Cmp = dyn_cast<CmpInst>(Inst);
|
|
Value *A = getVectorValue(Inst->getOperand(0));
|
|
Value *B = getVectorValue(Inst->getOperand(1));
|
|
if (FCmp)
|
|
WidenMap[Inst] = Builder.CreateFCmp(Cmp->getPredicate(), A, B);
|
|
else
|
|
WidenMap[Inst] = Builder.CreateICmp(Cmp->getPredicate(), A, B);
|
|
break;
|
|
}
|
|
|
|
case Instruction::Store: {
|
|
// Attempt to issue a wide store.
|
|
StoreInst *SI = dyn_cast<StoreInst>(Inst);
|
|
Type *StTy = VectorType::get(SI->getValueOperand()->getType(), VF);
|
|
Value *Ptr = SI->getPointerOperand();
|
|
unsigned Alignment = SI->getAlignment();
|
|
|
|
assert(!Legal->isUniform(Ptr) &&
|
|
"We do not allow storing to uniform addresses");
|
|
|
|
GetElementPtrInst *Gep = dyn_cast<GetElementPtrInst>(Ptr);
|
|
|
|
// This store does not use GEPs.
|
|
if (!Legal->isConsecutiveGep(Gep)) {
|
|
scalarizeInstruction(Inst);
|
|
break;
|
|
}
|
|
|
|
// 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();
|
|
Value *LastIndex = getVectorValue(Gep->getOperand(NumOperands - 1));
|
|
LastIndex = Builder.CreateExtractElement(LastIndex, Zero);
|
|
|
|
// Create the new GEP with the new induction variable.
|
|
GetElementPtrInst *Gep2 = cast<GetElementPtrInst>(Gep->clone());
|
|
Gep2->setOperand(NumOperands - 1, LastIndex);
|
|
Ptr = Builder.Insert(Gep2);
|
|
Ptr = Builder.CreateBitCast(Ptr, StTy->getPointerTo());
|
|
Value *Val = getVectorValue(SI->getValueOperand());
|
|
Builder.CreateStore(Val, Ptr)->setAlignment(Alignment);
|
|
break;
|
|
}
|
|
case Instruction::Load: {
|
|
// Attempt to issue a wide load.
|
|
LoadInst *LI = dyn_cast<LoadInst>(Inst);
|
|
Type *RetTy = VectorType::get(LI->getType(), VF);
|
|
Value *Ptr = LI->getPointerOperand();
|
|
unsigned Alignment = LI->getAlignment();
|
|
GetElementPtrInst *Gep = dyn_cast<GetElementPtrInst>(Ptr);
|
|
|
|
// If we don't have a gep, or that the pointer is loop invariant,
|
|
// scalarize the load.
|
|
if (!Gep || Legal->isUniform(Gep) || !Legal->isConsecutiveGep(Gep)) {
|
|
scalarizeInstruction(Inst);
|
|
break;
|
|
}
|
|
|
|
// 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();
|
|
Value *LastIndex = getVectorValue(Gep->getOperand(NumOperands -1));
|
|
LastIndex = Builder.CreateExtractElement(LastIndex, Zero);
|
|
|
|
// Create the new GEP with the new induction variable.
|
|
GetElementPtrInst *Gep2 = cast<GetElementPtrInst>(Gep->clone());
|
|
Gep2->setOperand(NumOperands - 1, LastIndex);
|
|
Ptr = Builder.Insert(Gep2);
|
|
Ptr = Builder.CreateBitCast(Ptr, RetTy->getPointerTo());
|
|
LI = Builder.CreateLoad(Ptr);
|
|
LI->setAlignment(Alignment);
|
|
// Use this vector value for all users of the load.
|
|
WidenMap[Inst] = LI;
|
|
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: {
|
|
/// Vectorize bitcasts.
|
|
CastInst *CI = dyn_cast<CastInst>(Inst);
|
|
Value *A = getVectorValue(Inst->getOperand(0));
|
|
Type *DestTy = VectorType::get(CI->getType()->getScalarType(), VF);
|
|
WidenMap[Inst] = Builder.CreateCast(CI->getOpcode(), A, DestTy);
|
|
break;
|
|
}
|
|
|
|
default:
|
|
/// All other instructions are unsupported. Scalarize them.
|
|
scalarizeInstruction(Inst);
|
|
break;
|
|
}// end of switch.
|
|
}// end of for_each instr.
|
|
|
|
// At this point every instruction in the original loop is widended 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 = PHIsToFix.begin(), e = PHIsToFix.end();
|
|
it != e; ++it) {
|
|
PHINode *RdxPhi = *it;
|
|
PHINode *VecRdxPhi = dyn_cast<PHINode>(WidenMap[RdxPhi]);
|
|
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];
|
|
|
|
// 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(LoopBypassBlock->getTerminator());
|
|
|
|
// This is the vector-clone of the value that leaves the loop.
|
|
Value *VectorExit = getVectorValue(RdxDesc.LoopExitInstr);
|
|
Type *VecTy = VectorExit->getType();
|
|
|
|
// Find the reduction identity variable. Zero for addition, or, xor,
|
|
// one for multiplication, -1 for And.
|
|
Constant *Identity = getUniformVector(getReductionIdentity(RdxDesc.Kind),
|
|
VecTy->getScalarType());
|
|
|
|
// This vector is the Identity vector where the first element is the
|
|
// incoming scalar reduction.
|
|
Value *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.
|
|
VecRdxPhi->addIncoming(VectorStart, VecPreheader);
|
|
unsigned SelfEdgeIdx = (RdxPhi)->getBasicBlockIndex(LoopScalarBody);
|
|
Value *Val = getVectorValue(RdxPhi->getIncomingValue(SelfEdgeIdx));
|
|
VecRdxPhi->addIncoming(Val, 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());
|
|
|
|
// This PHINode contains the vectorized reduction variable, or
|
|
// the initial value vector, if we bypass the vector loop.
|
|
PHINode *NewPhi = Builder.CreatePHI(VecTy, 2, "rdx.vec.exit.phi");
|
|
NewPhi->addIncoming(VectorStart, LoopBypassBlock);
|
|
NewPhi->addIncoming(getVectorValue(RdxDesc.LoopExitInstr), LoopVectorBody);
|
|
|
|
// Extract the first scalar.
|
|
Value *Scalar0 =
|
|
Builder.CreateExtractElement(NewPhi, Builder.getInt32(0));
|
|
// Extract and reduce the remaining vector elements.
|
|
for (unsigned i=1; i < VF; ++i) {
|
|
Value *Scalar1 =
|
|
Builder.CreateExtractElement(NewPhi, Builder.getInt32(i));
|
|
switch (RdxDesc.Kind) {
|
|
case LoopVectorizationLegality::IntegerAdd:
|
|
Scalar0 = Builder.CreateAdd(Scalar0, Scalar1);
|
|
break;
|
|
case LoopVectorizationLegality::IntegerMult:
|
|
Scalar0 = Builder.CreateMul(Scalar0, Scalar1);
|
|
break;
|
|
case LoopVectorizationLegality::IntegerOr:
|
|
Scalar0 = Builder.CreateOr(Scalar0, Scalar1);
|
|
break;
|
|
case LoopVectorizationLegality::IntegerAnd:
|
|
Scalar0 = Builder.CreateAnd(Scalar0, Scalar1);
|
|
break;
|
|
case LoopVectorizationLegality::IntegerXor:
|
|
Scalar0 = Builder.CreateXor(Scalar0, Scalar1);
|
|
break;
|
|
default:
|
|
llvm_unreachable("Unknown reduction operation");
|
|
}
|
|
}
|
|
|
|
// 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(LoopScalarBody);
|
|
int SelfEdgeBlockIdx = (IncomingEdgeBlockIdx ? 0 : 1); // The other block.
|
|
(RdxPhi)->setIncomingValue(SelfEdgeBlockIdx, Scalar0);
|
|
(RdxPhi)->setIncomingValue(IncomingEdgeBlockIdx, RdxDesc.LoopExitInstr);
|
|
}// end of for each redux variable.
|
|
}
|
|
|
|
void SingleBlockLoopVectorizer::updateAnalysis() {
|
|
// The original basic block.
|
|
SE->forgetLoop(OrigLoop);
|
|
|
|
// Update the dominator tree information.
|
|
assert(DT->properlyDominates(LoopBypassBlock, LoopExitBlock) &&
|
|
"Entry does not dominate exit.");
|
|
|
|
DT->addNewBlock(LoopVectorPreHeader, LoopBypassBlock);
|
|
DT->addNewBlock(LoopVectorBody, LoopVectorPreHeader);
|
|
DT->addNewBlock(LoopMiddleBlock, LoopBypassBlock);
|
|
DT->addNewBlock(LoopScalarPreHeader, LoopMiddleBlock);
|
|
DT->changeImmediateDominator(LoopScalarBody, LoopScalarPreHeader);
|
|
DT->changeImmediateDominator(LoopExitBlock, LoopMiddleBlock);
|
|
|
|
DEBUG(DT->verifyAnalysis());
|
|
}
|
|
|
|
bool LoopVectorizationLegality::canVectorize() {
|
|
if (!TheLoop->getLoopPreheader()) {
|
|
assert(false && "No preheader!!");
|
|
DEBUG(dbgs() << "LV: Loop not normalized." << "\n");
|
|
return false;
|
|
}
|
|
|
|
// We can only vectorize single basic block loops.
|
|
unsigned NumBlocks = TheLoop->getNumBlocks();
|
|
if (NumBlocks != 1) {
|
|
DEBUG(dbgs() << "LV: Too many blocks:" << NumBlocks << "\n");
|
|
return false;
|
|
}
|
|
|
|
// We need to have a loop header.
|
|
BasicBlock *BB = TheLoop->getHeader();
|
|
DEBUG(dbgs() << "LV: Found a loop: " << BB->getName() << "\n");
|
|
|
|
// ScalarEvolution needs to be able to find the exit count.
|
|
const SCEV *ExitCount = SE->getExitCount(TheLoop, BB);
|
|
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, BB);
|
|
if (TC > 0u && TC < TinyTripCountThreshold) {
|
|
DEBUG(dbgs() << "LV: Found a loop with a very small trip count. " <<
|
|
"This loop is not worth vectorizing.\n");
|
|
return false;
|
|
}
|
|
|
|
// Go over each instruction and look at memory deps.
|
|
if (!canVectorizeBlock(*BB)) {
|
|
DEBUG(dbgs() << "LV: Can't vectorize this loop header\n");
|
|
return false;
|
|
}
|
|
|
|
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;
|
|
}
|
|
|
|
bool LoopVectorizationLegality::canVectorizeBlock(BasicBlock &BB) {
|
|
// Scan the instructions in the block and look for hazards.
|
|
for (BasicBlock::iterator it = BB.begin(), e = BB.end(); it != e; ++it) {
|
|
Instruction *I = it;
|
|
|
|
PHINode *Phi = dyn_cast<PHINode>(I);
|
|
if (Phi) {
|
|
// This should not happen because the loop should be normalized.
|
|
if (Phi->getNumIncomingValues() != 2) {
|
|
DEBUG(dbgs() << "LV: Found an invalid PHI.\n");
|
|
return false;
|
|
}
|
|
// We only look at integer phi nodes.
|
|
if (!Phi->getType()->isIntegerTy()) {
|
|
DEBUG(dbgs() << "LV: Found an non-int PHI.\n");
|
|
return false;
|
|
}
|
|
|
|
if (isInductionVariable(Phi)) {
|
|
if (Induction) {
|
|
DEBUG(dbgs() << "LV: Found too many inductions."<< *Phi <<"\n");
|
|
return false;
|
|
}
|
|
DEBUG(dbgs() << "LV: Found the induction PHI."<< *Phi <<"\n");
|
|
Induction = Phi;
|
|
continue;
|
|
}
|
|
if (AddReductionVar(Phi, IntegerAdd)) {
|
|
DEBUG(dbgs() << "LV: Found an ADD reduction PHI."<< *Phi <<"\n");
|
|
continue;
|
|
}
|
|
if (AddReductionVar(Phi, IntegerMult)) {
|
|
DEBUG(dbgs() << "LV: Found a MUL reduction PHI."<< *Phi <<"\n");
|
|
continue;
|
|
}
|
|
if (AddReductionVar(Phi, IntegerOr)) {
|
|
DEBUG(dbgs() << "LV: Found an OR reduction PHI."<< *Phi <<"\n");
|
|
continue;
|
|
}
|
|
if (AddReductionVar(Phi, IntegerAnd)) {
|
|
DEBUG(dbgs() << "LV: Found an AND reduction PHI."<< *Phi <<"\n");
|
|
continue;
|
|
}
|
|
if (AddReductionVar(Phi, IntegerXor)) {
|
|
DEBUG(dbgs() << "LV: Found a XOR 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.
|
|
CallInst *CI = dyn_cast<CallInst>(I);
|
|
if (CI) {
|
|
DEBUG(dbgs() << "LV: Found a call site.\n");
|
|
return false;
|
|
}
|
|
|
|
// We do not re-vectorize vectors.
|
|
if (!VectorType::isValidElementType(I->getType()) &&
|
|
!I->getType()->isVoidTy()) {
|
|
DEBUG(dbgs() << "LV: Found unvectorizable type." << "\n");
|
|
return false;
|
|
}
|
|
|
|
// Reduction instructions are allowed to have exit users.
|
|
// All other instructions must not have external users.
|
|
if (!AllowedExit.count(I))
|
|
//Check that all of the users of the loop are inside the BB.
|
|
for (Value::use_iterator it = I->use_begin(), e = I->use_end();
|
|
it != e; ++it) {
|
|
Instruction *U = cast<Instruction>(*it);
|
|
// This user may be a reduction exit value.
|
|
BasicBlock *Parent = U->getParent();
|
|
if (Parent != &BB) {
|
|
DEBUG(dbgs() << "LV: Found an outside user for : "<< *U << "\n");
|
|
return false;
|
|
}
|
|
}
|
|
} // next instr.
|
|
|
|
if (!Induction) {
|
|
DEBUG(dbgs() << "LV: Did not find an induction var.\n");
|
|
return false;
|
|
}
|
|
|
|
// Don't vectorize if the memory dependencies do not allow vectorization.
|
|
if (!canVectorizeMemory(BB))
|
|
return false;
|
|
|
|
// We now know that the loop is vectorizable!
|
|
// Collect variables that will remain uniform after vectorization.
|
|
std::vector<Value*> Worklist;
|
|
|
|
// Start with the conditional branch and walk up the block.
|
|
Worklist.push_back(BB.getTerminator()->getOperand(0));
|
|
|
|
while (Worklist.size()) {
|
|
Instruction *I = dyn_cast<Instruction>(Worklist.back());
|
|
Worklist.pop_back();
|
|
// Look at instructions inside this block.
|
|
if (!I) continue;
|
|
if (I->getParent() != &BB) continue;
|
|
|
|
// Stop when reaching PHI nodes.
|
|
if (isa<PHINode>(I)) {
|
|
assert(I == Induction && "Found a uniform PHI that is not the induction");
|
|
break;
|
|
}
|
|
|
|
// This is a known uniform.
|
|
Uniforms.insert(I);
|
|
|
|
// Insert all operands.
|
|
for (int i=0, Op = I->getNumOperands(); i < Op; ++i) {
|
|
Worklist.push_back(I->getOperand(i));
|
|
}
|
|
}
|
|
|
|
return true;
|
|
}
|
|
|
|
bool LoopVectorizationLegality::canVectorizeMemory(BasicBlock &BB) {
|
|
typedef SmallVector<Value*, 16> ValueVector;
|
|
typedef SmallPtrSet<Value*, 16> ValueSet;
|
|
// Holds the Load and Store *instructions*.
|
|
ValueVector Loads;
|
|
ValueVector Stores;
|
|
PtrRtCheck.Pointers.clear();
|
|
PtrRtCheck.Need = false;
|
|
|
|
// Scan the BB and collect legal loads and stores.
|
|
for (BasicBlock::iterator it = BB.begin(), e = BB.end(); it != e; ++it) {
|
|
Instruction *I = 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 (I->mayReadFromMemory()) {
|
|
LoadInst *Ld = dyn_cast<LoadInst>(I);
|
|
if (!Ld) return false;
|
|
if (!Ld->isSimple()) {
|
|
DEBUG(dbgs() << "LV: Found a non-simple load.\n");
|
|
return false;
|
|
}
|
|
Loads.push_back(Ld);
|
|
continue;
|
|
}
|
|
|
|
// Save store instructions. Abort if other instructions write to memory.
|
|
if (I->mayWriteToMemory()) {
|
|
StoreInst *St = dyn_cast<StoreInst>(I);
|
|
if (!St) return false;
|
|
if (!St->isSimple()) {
|
|
DEBUG(dbgs() << "LV: Found a non-simple store.\n");
|
|
return false;
|
|
}
|
|
Stores.push_back(St);
|
|
}
|
|
} // next instr.
|
|
|
|
// 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;
|
|
}
|
|
|
|
// Holds the read and read-write *pointers* that we find.
|
|
ValueVector Reads;
|
|
ValueVector ReadWrites;
|
|
|
|
// 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 = dyn_cast<StoreInst>(*I);
|
|
assert(ST && "Bad StoreInst");
|
|
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))
|
|
ReadWrites.push_back(Ptr);
|
|
}
|
|
|
|
for (I = Loads.begin(), IE = Loads.end(); I != IE; ++I) {
|
|
LoadInst *LD = dyn_cast<LoadInst>(*I);
|
|
assert(LD && "Bad LoadInst");
|
|
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.
|
|
if (Seen.insert(Ptr) || !isConsecutiveGep(Ptr))
|
|
Reads.push_back(Ptr);
|
|
}
|
|
|
|
// 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 (ReadWrites.size() == 1 && Reads.size() == 0) {
|
|
DEBUG(dbgs() << "LV: Found a write-only loop!\n");
|
|
return true;
|
|
}
|
|
|
|
// Find pointers with computable bounds. We are going to use this information
|
|
// to place a runtime bound check.
|
|
bool RT = true;
|
|
for (I = ReadWrites.begin(), IE = ReadWrites.end(); I != IE; ++I)
|
|
if (hasComputableBounds(*I)) {
|
|
PtrRtCheck.Pointers.push_back(*I);
|
|
DEBUG(dbgs() << "LV: Found a runtime check ptr:" << **I <<"\n");
|
|
} else {
|
|
RT = false;
|
|
break;
|
|
}
|
|
for (I = Reads.begin(), IE = Reads.end(); I != IE; ++I)
|
|
if (hasComputableBounds(*I)) {
|
|
PtrRtCheck.Pointers.push_back(*I);
|
|
DEBUG(dbgs() << "LV: Found a runtime check ptr:" << **I <<"\n");
|
|
} else {
|
|
RT = false;
|
|
break;
|
|
}
|
|
|
|
// Check that we did not collect too many pointers or found a
|
|
// unsizeable pointer.
|
|
if (!RT || PtrRtCheck.Pointers.size() > RuntimeMemoryCheckThreshold) {
|
|
PtrRtCheck.Pointers.clear();
|
|
RT = false;
|
|
}
|
|
|
|
PtrRtCheck.Need = RT;
|
|
|
|
if (RT) {
|
|
DEBUG(dbgs() << "LV: We can perform a memory runtime check if needed.\n");
|
|
}
|
|
|
|
// Now that the pointers are in two lists (Reads and ReadWrites), we
|
|
// can check that there are no conflicts between each of the writes and
|
|
// between the writes to the reads.
|
|
ValueSet WriteObjects;
|
|
ValueVector TempObjects;
|
|
|
|
// Check that the read-writes do not conflict with other read-write
|
|
// pointers.
|
|
for (I = ReadWrites.begin(), IE = ReadWrites.end(); I != IE; ++I) {
|
|
GetUnderlyingObjects(*I, TempObjects, DL);
|
|
for (ValueVector::iterator it=TempObjects.begin(), e=TempObjects.end();
|
|
it != e; ++it) {
|
|
if (!isIdentifiedObject(*it)) {
|
|
DEBUG(dbgs() << "LV: Found an unidentified write ptr:"<< **it <<"\n");
|
|
return RT;
|
|
}
|
|
if (!WriteObjects.insert(*it)) {
|
|
DEBUG(dbgs() << "LV: Found a possible write-write reorder:"
|
|
<< **it <<"\n");
|
|
return RT;
|
|
}
|
|
}
|
|
TempObjects.clear();
|
|
}
|
|
|
|
/// Check that the reads don't conflict with the read-writes.
|
|
for (I = Reads.begin(), IE = Reads.end(); I != IE; ++I) {
|
|
GetUnderlyingObjects(*I, TempObjects, DL);
|
|
for (ValueVector::iterator it=TempObjects.begin(), e=TempObjects.end();
|
|
it != e; ++it) {
|
|
if (!isIdentifiedObject(*it)) {
|
|
DEBUG(dbgs() << "LV: Found an unidentified read ptr:"<< **it <<"\n");
|
|
return RT;
|
|
}
|
|
if (WriteObjects.count(*it)) {
|
|
DEBUG(dbgs() << "LV: Found a possible read/write reorder:"
|
|
<< **it <<"\n");
|
|
return RT;
|
|
}
|
|
}
|
|
TempObjects.clear();
|
|
}
|
|
|
|
// It is safe to vectorize and we don't need any runtime checks.
|
|
DEBUG(dbgs() << "LV: We don't need a runtime memory check.\n");
|
|
PtrRtCheck.Pointers.clear();
|
|
PtrRtCheck.Need = false;
|
|
return true;
|
|
}
|
|
|
|
bool LoopVectorizationLegality::AddReductionVar(PHINode *Phi,
|
|
ReductionKind Kind) {
|
|
if (Phi->getNumIncomingValues() != 2)
|
|
return false;
|
|
|
|
// Find the possible incoming reduction variable.
|
|
BasicBlock *BB = Phi->getParent();
|
|
int SelfEdgeIdx = Phi->getBasicBlockIndex(BB);
|
|
int InEdgeBlockIdx = (SelfEdgeIdx ? 0 : 1); // The other entry.
|
|
Value *RdxStart = Phi->getIncomingValue(InEdgeBlockIdx);
|
|
|
|
// 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;
|
|
|
|
// Iter is our iterator. We start with the PHI node and scan for all of the
|
|
// users of this instruction. All users must be instructions which can be
|
|
// used as reduction variables (such as ADD). We may have a single
|
|
// out-of-block user. They cycle must end with the original PHI.
|
|
// Also, we can't have multiple block-local users.
|
|
Instruction *Iter = Phi;
|
|
while (true) {
|
|
// Any reduction instr must be of one of the allowed kinds.
|
|
if (!isReductionInstr(Iter, Kind))
|
|
return false;
|
|
|
|
// Did we found a user inside this block ?
|
|
bool FoundInBlockUser = false;
|
|
// Did we reach the initial PHI node ?
|
|
bool FoundStartPHI = false;
|
|
|
|
// If the instruction has no users then this is a broken
|
|
// chain and can't be a reduction variable.
|
|
if (Iter->use_empty())
|
|
return false;
|
|
|
|
// For each of the *users* of iter.
|
|
for (Value::use_iterator it = Iter->use_begin(), e = Iter->use_end();
|
|
it != e; ++it) {
|
|
Instruction *U = cast<Instruction>(*it);
|
|
// We already know that the PHI is a user.
|
|
if (U == Phi) {
|
|
FoundStartPHI = true;
|
|
continue;
|
|
}
|
|
// Check if we found the exit user.
|
|
BasicBlock *Parent = U->getParent();
|
|
if (Parent != BB) {
|
|
// We must have a single exit instruction.
|
|
if (ExitInstruction != 0)
|
|
return false;
|
|
ExitInstruction = Iter;
|
|
}
|
|
// We can't have multiple inside users.
|
|
if (FoundInBlockUser)
|
|
return false;
|
|
FoundInBlockUser = true;
|
|
Iter = U;
|
|
}
|
|
|
|
// 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.
|
|
if (FoundStartPHI && ExitInstruction) {
|
|
// 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);
|
|
Reductions[Phi] = RD;
|
|
return true;
|
|
}
|
|
}
|
|
}
|
|
|
|
bool
|
|
LoopVectorizationLegality::isReductionInstr(Instruction *I,
|
|
ReductionKind Kind) {
|
|
switch (I->getOpcode()) {
|
|
default:
|
|
return false;
|
|
case Instruction::PHI:
|
|
// possibly.
|
|
return true;
|
|
case Instruction::Add:
|
|
case Instruction::Sub:
|
|
return Kind == IntegerAdd;
|
|
case Instruction::Mul:
|
|
case Instruction::UDiv:
|
|
case Instruction::SDiv:
|
|
return Kind == IntegerMult;
|
|
case Instruction::And:
|
|
return Kind == IntegerAnd;
|
|
case Instruction::Or:
|
|
return Kind == IntegerOr;
|
|
case Instruction::Xor:
|
|
return Kind == IntegerXor;
|
|
}
|
|
}
|
|
|
|
bool LoopVectorizationLegality::isInductionVariable(PHINode *Phi) {
|
|
// Check that the PHI is consecutive and starts at zero.
|
|
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 false;
|
|
}
|
|
const SCEV *Step = AR->getStepRecurrence(*SE);
|
|
|
|
if (!Step->isOne()) {
|
|
DEBUG(dbgs() << "LV: PHI stride does not equal one.\n");
|
|
return false;
|
|
}
|
|
return true;
|
|
}
|
|
|
|
bool LoopVectorizationLegality::hasComputableBounds(Value *Ptr) {
|
|
const SCEV *PhiScev = SE->getSCEV(Ptr);
|
|
const SCEVAddRecExpr *AR = dyn_cast<SCEVAddRecExpr>(PhiScev);
|
|
if (!AR)
|
|
return false;
|
|
|
|
return AR->isAffine();
|
|
}
|
|
|
|
unsigned
|
|
LoopVectorizationCostModel::findBestVectorizationFactor(unsigned VF) {
|
|
if (!VTTI) {
|
|
DEBUG(dbgs() << "LV: No vector target information. Not vectorizing. \n");
|
|
return 1;
|
|
}
|
|
|
|
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");
|
|
return Width;
|
|
}
|
|
|
|
unsigned LoopVectorizationCostModel::expectedCost(unsigned VF) {
|
|
// We can only estimate the cost of single basic block loops.
|
|
assert(1 == TheLoop->getNumBlocks() && "Too many blocks in loop");
|
|
|
|
BasicBlock *BB = TheLoop->getHeader();
|
|
unsigned Cost = 0;
|
|
|
|
// For each instruction in the old loop.
|
|
for (BasicBlock::iterator it = BB->begin(), e = BB->end(); it != e; ++it) {
|
|
Instruction *Inst = it;
|
|
unsigned C = getInstructionCost(Inst, VF);
|
|
Cost += C;
|
|
DEBUG(dbgs() << "LV: Found an estimated cost of "<< C <<" for VF "<< VF <<
|
|
" For instruction: "<< *Inst << "\n");
|
|
}
|
|
|
|
return Cost;
|
|
}
|
|
|
|
unsigned
|
|
LoopVectorizationCostModel::getInstructionCost(Instruction *I, unsigned VF) {
|
|
assert(VTTI && "Invalid vector target transformation info");
|
|
|
|
// 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 scalar GEPs are usually
|
|
// lowered to the intruction addressing mode. At the moment we don't
|
|
// generate vector geps.
|
|
return 0;
|
|
case Instruction::Br: {
|
|
return VTTI->getCFInstrCost(I->getOpcode());
|
|
}
|
|
case Instruction::PHI:
|
|
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: {
|
|
return VTTI->getArithmeticInstrCost(I->getOpcode(), VectorTy);
|
|
}
|
|
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 VTTI->getCmpSelInstrCost(I->getOpcode(), VectorTy, CondTy);
|
|
}
|
|
case Instruction::ICmp:
|
|
case Instruction::FCmp: {
|
|
Type *ValTy = I->getOperand(0)->getType();
|
|
VectorTy = ToVectorTy(ValTy, VF);
|
|
return VTTI->getCmpSelInstrCost(I->getOpcode(), VectorTy);
|
|
}
|
|
case Instruction::Store: {
|
|
StoreInst *SI = cast<StoreInst>(I);
|
|
Type *ValTy = SI->getValueOperand()->getType();
|
|
VectorTy = ToVectorTy(ValTy, VF);
|
|
|
|
if (VF == 1)
|
|
return VTTI->getMemoryOpCost(I->getOpcode(), ValTy,
|
|
SI->getAlignment(), SI->getPointerAddressSpace());
|
|
|
|
// Scalarized stores.
|
|
if (!Legal->isConsecutiveGep(SI->getPointerOperand())) {
|
|
unsigned Cost = 0;
|
|
unsigned ExtCost = VTTI->getInstrCost(Instruction::ExtractElement,
|
|
ValTy);
|
|
// The cost of extracting from the value vector.
|
|
Cost += VF * (ExtCost);
|
|
// The cost of the scalar stores.
|
|
Cost += VF * VTTI->getMemoryOpCost(I->getOpcode(),
|
|
ValTy->getScalarType(),
|
|
SI->getAlignment(),
|
|
SI->getPointerAddressSpace());
|
|
return Cost;
|
|
}
|
|
|
|
// Wide stores.
|
|
return VTTI->getMemoryOpCost(I->getOpcode(), VectorTy, SI->getAlignment(),
|
|
SI->getPointerAddressSpace());
|
|
}
|
|
case Instruction::Load: {
|
|
LoadInst *LI = cast<LoadInst>(I);
|
|
|
|
if (VF == 1)
|
|
return VTTI->getMemoryOpCost(I->getOpcode(), RetTy,
|
|
LI->getAlignment(),
|
|
LI->getPointerAddressSpace());
|
|
|
|
// Scalarized loads.
|
|
if (!Legal->isConsecutiveGep(LI->getPointerOperand())) {
|
|
unsigned Cost = 0;
|
|
unsigned InCost = VTTI->getInstrCost(Instruction::InsertElement, RetTy);
|
|
// The cost of inserting the loaded value into the result vector.
|
|
Cost += VF * (InCost);
|
|
// The cost of the scalar stores.
|
|
Cost += VF * VTTI->getMemoryOpCost(I->getOpcode(),
|
|
RetTy->getScalarType(),
|
|
LI->getAlignment(),
|
|
LI->getPointerAddressSpace());
|
|
return Cost;
|
|
}
|
|
|
|
// Wide loads.
|
|
return VTTI->getMemoryOpCost(I->getOpcode(), VectorTy, LI->getAlignment(),
|
|
LI->getPointerAddressSpace());
|
|
}
|
|
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: {
|
|
Type *SrcVecTy = ToVectorTy(I->getOperand(0)->getType(), VF);
|
|
return VTTI->getCastInstrCost(I->getOpcode(), VectorTy, SrcVecTy);
|
|
}
|
|
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;
|
|
|
|
bool IsVoid = RetTy->isVoidTy();
|
|
|
|
unsigned InsCost = (IsVoid ? 0 :
|
|
VTTI->getInstrCost(Instruction::InsertElement,
|
|
VectorTy));
|
|
|
|
unsigned ExtCost = VTTI->getInstrCost(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.
|
|
Cost += VF * VTTI->getInstrCost(I->getOpcode(), RetTy);
|
|
return Cost;
|
|
}
|
|
}// end of switch.
|
|
}
|
|
|
|
Type* LoopVectorizationCostModel::ToVectorTy(Type *Scalar, unsigned VF) {
|
|
if (Scalar->isVoidTy() || VF == 1)
|
|
return Scalar;
|
|
return VectorType::get(Scalar, VF);
|
|
}
|
|
|
|
} // namespace
|
|
|
|
char LoopVectorize::ID = 0;
|
|
static const char lv_name[] = "Loop Vectorization";
|
|
INITIALIZE_PASS_BEGIN(LoopVectorize, LV_NAME, lv_name, false, false)
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INITIALIZE_AG_DEPENDENCY(AliasAnalysis)
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INITIALIZE_PASS_DEPENDENCY(ScalarEvolution)
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INITIALIZE_PASS_DEPENDENCY(LoopSimplify)
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INITIALIZE_PASS_END(LoopVectorize, LV_NAME, lv_name, false, false)
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namespace llvm {
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Pass *createLoopVectorizePass() {
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return new LoopVectorize();
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}
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}
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