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Use the size of the widest type of the matrix multiplication operands
The size of the operands type is the one of the parameters required to determine the BLIS micro-kernel. We get the size of the widest type of the matrix multiplication operands in case there are several different types. Reviewed-by: Michael Kruse <llvm@meinersbur.de> Differential Revision: https://reviews.llvm.org/D29269 llvm-svn: 294828
This commit is contained in:
Roman Gareev
parent
3afa777f10
commit
3d4eae31ea
@ -900,6 +900,36 @@ __isl_give isl_schedule_node *ScheduleTreeOptimizer::createMacroKernel(
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return isl_schedule_node_child(isl_schedule_node_child(Node, 0), 0);
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}
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/// Get the size of the widest type of the matrix multiplication operands
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/// in bytes, including alignment padding.
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///
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/// @param MMI Parameters of the matrix multiplication operands.
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/// @return The size of the widest type of the matrix multiplication operands
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/// in bytes, including alignment padding.
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static uint64_t getMatMulAlignTypeSize(MatMulInfoTy MMI) {
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auto *S = MMI.A->getStatement()->getParent();
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auto &DL = S->getFunction().getParent()->getDataLayout();
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auto ElementSizeA = DL.getTypeAllocSize(MMI.A->getElementType());
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auto ElementSizeB = DL.getTypeAllocSize(MMI.B->getElementType());
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auto ElementSizeC = DL.getTypeAllocSize(MMI.WriteToC->getElementType());
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return std::max({ElementSizeA, ElementSizeB, ElementSizeC});
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}
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/// Get the size of the widest type of the matrix multiplication operands
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/// in bits.
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///
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/// @param MMI Parameters of the matrix multiplication operands.
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/// @return The size of the widest type of the matrix multiplication operands
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/// in bits.
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static uint64_t getMatMulTypeSize(MatMulInfoTy MMI) {
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auto *S = MMI.A->getStatement()->getParent();
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auto &DL = S->getFunction().getParent()->getDataLayout();
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auto ElementSizeA = DL.getTypeSizeInBits(MMI.A->getElementType());
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auto ElementSizeB = DL.getTypeSizeInBits(MMI.B->getElementType());
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auto ElementSizeC = DL.getTypeSizeInBits(MMI.WriteToC->getElementType());
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return std::max({ElementSizeA, ElementSizeB, ElementSizeC});
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}
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/// Get parameters of the BLIS micro kernel.
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///
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/// We choose the Mr and Nr parameters of the micro kernel to be large enough
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@ -909,10 +939,11 @@ __isl_give isl_schedule_node *ScheduleTreeOptimizer::createMacroKernel(
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/// release more registers for entries of multiplied matrices.
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///
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/// @param TTI Target Transform Info.
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/// @param MMI Parameters of the matrix multiplication operands.
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/// @return The structure of type MicroKernelParamsTy.
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/// @see MicroKernelParamsTy
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static struct MicroKernelParamsTy
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getMicroKernelParams(const llvm::TargetTransformInfo *TTI) {
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getMicroKernelParams(const llvm::TargetTransformInfo *TTI, MatMulInfoTy MMI) {
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assert(TTI && "The target transform info should be provided.");
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// Nvec - Number of double-precision floating-point numbers that can be hold
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@ -921,7 +952,10 @@ getMicroKernelParams(const llvm::TargetTransformInfo *TTI) {
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if (RegisterBitwidth == -1)
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RegisterBitwidth = TTI->getRegisterBitWidth(true);
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auto Nvec = RegisterBitwidth / 64;
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auto ElementSize = getMatMulTypeSize(MMI);
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assert(ElementSize > 0 && "The element size of the matrix multiplication "
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"operands should be greater than zero.");
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auto Nvec = RegisterBitwidth / ElementSize;
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if (Nvec == 0)
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Nvec = 2;
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int Nr =
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@ -940,11 +974,13 @@ getMicroKernelParams(const llvm::TargetTransformInfo *TTI) {
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///
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/// @param MicroKernelParams Parameters of the micro-kernel
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/// to be taken into account.
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/// @param MMI Parameters of the matrix multiplication operands.
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/// @return The structure of type MacroKernelParamsTy.
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/// @see MacroKernelParamsTy
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/// @see MicroKernelParamsTy
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static struct MacroKernelParamsTy
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getMacroKernelParams(const MicroKernelParamsTy &MicroKernelParams) {
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getMacroKernelParams(const MicroKernelParamsTy &MicroKernelParams,
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MatMulInfoTy MMI) {
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// According to www.cs.utexas.edu/users/flame/pubs/TOMS-BLIS-Analytical.pdf,
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// it requires information about the first two levels of a cache to determine
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// all the parameters of a macro-kernel. It also checks that an associativity
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@ -960,10 +996,14 @@ getMacroKernelParams(const MicroKernelParamsTy &MicroKernelParams) {
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int Car = floor(
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(FirstCacheLevelAssociativity - 1) /
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(1 + static_cast<double>(MicroKernelParams.Nr) / MicroKernelParams.Mr));
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auto ElementSize = getMatMulAlignTypeSize(MMI);
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assert(ElementSize > 0 && "The element size of the matrix multiplication "
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"operands should be greater than zero.");
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int Kc = (Car * FirstCacheLevelSize) /
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(MicroKernelParams.Mr * FirstCacheLevelAssociativity * 8);
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double Cac = static_cast<double>(Kc * 8 * SecondCacheLevelAssociativity) /
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SecondCacheLevelSize;
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(MicroKernelParams.Mr * FirstCacheLevelAssociativity * ElementSize);
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double Cac =
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static_cast<double>(Kc * ElementSize * SecondCacheLevelAssociativity) /
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SecondCacheLevelSize;
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int Mc = floor((SecondCacheLevelAssociativity - 2) / Cac);
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int Nc = PollyPatternMatchingNcQuotient * MicroKernelParams.Nr;
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return {Mc, Nc, Kc};
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@ -1198,8 +1238,8 @@ __isl_give isl_schedule_node *ScheduleTreeOptimizer::optimizeMatMulPattern(
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Node = permuteBandNodeDimensions(Node, NewJ, DimOutNum - 2);
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NewK = MMI.k == DimOutNum - 2 ? MMI.j : MMI.k;
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Node = permuteBandNodeDimensions(Node, NewK, DimOutNum - 1);
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auto MicroKernelParams = getMicroKernelParams(TTI);
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auto MacroKernelParams = getMacroKernelParams(MicroKernelParams);
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auto MicroKernelParams = getMicroKernelParams(TTI, MMI);
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auto MacroKernelParams = getMacroKernelParams(MicroKernelParams, MMI);
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Node = createMacroKernel(Node, MacroKernelParams);
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Node = createMicroKernel(Node, MicroKernelParams);
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if (MacroKernelParams.Mc == 1 || MacroKernelParams.Nc == 1 ||
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156
polly/test/ScheduleOptimizer/pattern-matching-based-opts_7.ll
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156
polly/test/ScheduleOptimizer/pattern-matching-based-opts_7.ll
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@ -0,0 +1,156 @@
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; RUN: opt %loadPolly -polly-opt-isl -polly-pattern-matching-based-opts=true \
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; RUN: -polly-target-throughput-vector-fma=1 \
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; RUN: -polly-target-latency-vector-fma=8 \
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; RUN: -analyze -polly-ast -polly-target-1st-cache-level-associativity=8 \
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; RUN: -polly-target-2nd-cache-level-associativity=8 \
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; RUN: -polly-target-1st-cache-level-size=32768 \
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; RUN: -polly-target-vector-register-bitwidth=256 \
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; RUN: -polly-target-2nd-cache-level-size=262144 < %s \
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; RUN: | FileCheck %s
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;
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; /* C := A * B + C */
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; /* Elements of the matrices A, B, C have the float type. */
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; /* The type size of elements of the matrix multiplication operands is used
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; to determine the parameters of the code produced by the optimization
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; of the matrix multiplication (e.g. bounds of the loops of the loop
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; nest, the innermost loop body). This test checks the form of
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; the generated loop nest. See getMicroKernelParams and
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; getMacroKernelParams from lib/Transform/ScheduleOptimizer.cpp
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; for details. */
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; for (i = 0; i < _PB_NI; i++)
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; for (j = 0; j < _PB_NJ; j++)
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; for (k = 0; k < _PB_NK; ++k)
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; C[i][j] += A[i][k] * B[k][j];
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;
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; CHECK: // 1st level tiling - Tiles
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; CHECK-NEXT: for (int c1 = 0; c1 <= 2; c1 += 1) {
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; CHECK-NEXT: for (int c3 = 0; c3 <= 1023; c3 += 1)
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; CHECK-NEXT: for (int c4 = 384 * c1; c4 <= min(1023, 384 * c1 + 383); c4 += 1)
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; CHECK-NEXT: CopyStmt_0(0, c3, c4);
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; CHECK-NEXT: for (int c2 = 0; c2 <= 7; c2 += 1) {
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; CHECK-NEXT: for (int c3 = 128 * c2; c3 <= 128 * c2 + 127; c3 += 1)
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; CHECK-NEXT: for (int c5 = 384 * c1; c5 <= min(1023, 384 * c1 + 383); c5 += 1)
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; CHECK-NEXT: CopyStmt_1(c3, 0, c5);
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; CHECK-NEXT: // 1st level tiling - Points
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; CHECK-NEXT: // Register tiling - Tiles
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; CHECK-NEXT: for (int c3 = 0; c3 <= 127; c3 += 1)
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; CHECK-NEXT: for (int c4 = 0; c4 <= 15; c4 += 1)
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; CHECK-NEXT: for (int c5 = 0; c5 <= min(383, -384 * c1 + 1023); c5 += 1) {
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; CHECK-NEXT: // Register tiling - Points
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; CHECK-NEXT: {
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; CHECK-NEXT: Stmt_for_body6(128 * c2 + 8 * c4, 8 * c3, 384 * c1 + c5);
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; CHECK-NEXT: Stmt_for_body6(128 * c2 + 8 * c4, 8 * c3 + 1, 384 * c1 + c5);
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; CHECK-NEXT: Stmt_for_body6(128 * c2 + 8 * c4, 8 * c3 + 2, 384 * c1 + c5);
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; CHECK-NEXT: Stmt_for_body6(128 * c2 + 8 * c4, 8 * c3 + 3, 384 * c1 + c5);
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; CHECK-NEXT: Stmt_for_body6(128 * c2 + 8 * c4, 8 * c3 + 4, 384 * c1 + c5);
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; CHECK-NEXT: Stmt_for_body6(128 * c2 + 8 * c4, 8 * c3 + 5, 384 * c1 + c5);
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; CHECK-NEXT: Stmt_for_body6(128 * c2 + 8 * c4, 8 * c3 + 6, 384 * c1 + c5);
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; CHECK-NEXT: Stmt_for_body6(128 * c2 + 8 * c4, 8 * c3 + 7, 384 * c1 + c5);
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; CHECK-NEXT: Stmt_for_body6(128 * c2 + 8 * c4 + 1, 8 * c3, 384 * c1 + c5);
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; CHECK-NEXT: Stmt_for_body6(128 * c2 + 8 * c4 + 1, 8 * c3 + 1, 384 * c1 + c5);
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; CHECK-NEXT: Stmt_for_body6(128 * c2 + 8 * c4 + 1, 8 * c3 + 2, 384 * c1 + c5);
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; CHECK-NEXT: Stmt_for_body6(128 * c2 + 8 * c4 + 1, 8 * c3 + 3, 384 * c1 + c5);
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; CHECK-NEXT: Stmt_for_body6(128 * c2 + 8 * c4 + 1, 8 * c3 + 4, 384 * c1 + c5);
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; CHECK-NEXT: Stmt_for_body6(128 * c2 + 8 * c4 + 1, 8 * c3 + 5, 384 * c1 + c5);
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; CHECK-NEXT: Stmt_for_body6(128 * c2 + 8 * c4 + 1, 8 * c3 + 6, 384 * c1 + c5);
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; CHECK-NEXT: Stmt_for_body6(128 * c2 + 8 * c4 + 1, 8 * c3 + 7, 384 * c1 + c5);
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; CHECK-NEXT: Stmt_for_body6(128 * c2 + 8 * c4 + 2, 8 * c3, 384 * c1 + c5);
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; CHECK-NEXT: Stmt_for_body6(128 * c2 + 8 * c4 + 2, 8 * c3 + 1, 384 * c1 + c5);
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; CHECK-NEXT: Stmt_for_body6(128 * c2 + 8 * c4 + 2, 8 * c3 + 2, 384 * c1 + c5);
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; CHECK-NEXT: Stmt_for_body6(128 * c2 + 8 * c4 + 2, 8 * c3 + 3, 384 * c1 + c5);
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; CHECK-NEXT: Stmt_for_body6(128 * c2 + 8 * c4 + 2, 8 * c3 + 4, 384 * c1 + c5);
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; CHECK-NEXT: Stmt_for_body6(128 * c2 + 8 * c4 + 2, 8 * c3 + 5, 384 * c1 + c5);
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; CHECK-NEXT: Stmt_for_body6(128 * c2 + 8 * c4 + 2, 8 * c3 + 6, 384 * c1 + c5);
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; CHECK-NEXT: Stmt_for_body6(128 * c2 + 8 * c4 + 2, 8 * c3 + 7, 384 * c1 + c5);
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; CHECK-NEXT: Stmt_for_body6(128 * c2 + 8 * c4 + 3, 8 * c3, 384 * c1 + c5);
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; CHECK-NEXT: Stmt_for_body6(128 * c2 + 8 * c4 + 3, 8 * c3 + 1, 384 * c1 + c5);
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; CHECK-NEXT: Stmt_for_body6(128 * c2 + 8 * c4 + 3, 8 * c3 + 2, 384 * c1 + c5);
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; CHECK-NEXT: Stmt_for_body6(128 * c2 + 8 * c4 + 3, 8 * c3 + 3, 384 * c1 + c5);
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; CHECK-NEXT: Stmt_for_body6(128 * c2 + 8 * c4 + 3, 8 * c3 + 4, 384 * c1 + c5);
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; CHECK-NEXT: Stmt_for_body6(128 * c2 + 8 * c4 + 3, 8 * c3 + 5, 384 * c1 + c5);
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; CHECK-NEXT: Stmt_for_body6(128 * c2 + 8 * c4 + 3, 8 * c3 + 6, 384 * c1 + c5);
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; CHECK-NEXT: Stmt_for_body6(128 * c2 + 8 * c4 + 3, 8 * c3 + 7, 384 * c1 + c5);
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; CHECK-NEXT: Stmt_for_body6(128 * c2 + 8 * c4 + 4, 8 * c3, 384 * c1 + c5);
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; CHECK-NEXT: Stmt_for_body6(128 * c2 + 8 * c4 + 4, 8 * c3 + 1, 384 * c1 + c5);
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; CHECK-NEXT: Stmt_for_body6(128 * c2 + 8 * c4 + 4, 8 * c3 + 2, 384 * c1 + c5);
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; CHECK-NEXT: Stmt_for_body6(128 * c2 + 8 * c4 + 4, 8 * c3 + 3, 384 * c1 + c5);
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; CHECK-NEXT: Stmt_for_body6(128 * c2 + 8 * c4 + 4, 8 * c3 + 4, 384 * c1 + c5);
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; CHECK-NEXT: Stmt_for_body6(128 * c2 + 8 * c4 + 4, 8 * c3 + 5, 384 * c1 + c5);
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; CHECK-NEXT: Stmt_for_body6(128 * c2 + 8 * c4 + 4, 8 * c3 + 6, 384 * c1 + c5);
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; CHECK-NEXT: Stmt_for_body6(128 * c2 + 8 * c4 + 4, 8 * c3 + 7, 384 * c1 + c5);
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; CHECK-NEXT: Stmt_for_body6(128 * c2 + 8 * c4 + 5, 8 * c3, 384 * c1 + c5);
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; CHECK-NEXT: Stmt_for_body6(128 * c2 + 8 * c4 + 5, 8 * c3 + 1, 384 * c1 + c5);
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; CHECK-NEXT: Stmt_for_body6(128 * c2 + 8 * c4 + 5, 8 * c3 + 2, 384 * c1 + c5);
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; CHECK-NEXT: Stmt_for_body6(128 * c2 + 8 * c4 + 5, 8 * c3 + 3, 384 * c1 + c5);
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; CHECK-NEXT: Stmt_for_body6(128 * c2 + 8 * c4 + 5, 8 * c3 + 4, 384 * c1 + c5);
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; CHECK-NEXT: Stmt_for_body6(128 * c2 + 8 * c4 + 5, 8 * c3 + 5, 384 * c1 + c5);
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; CHECK-NEXT: Stmt_for_body6(128 * c2 + 8 * c4 + 5, 8 * c3 + 6, 384 * c1 + c5);
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; CHECK-NEXT: Stmt_for_body6(128 * c2 + 8 * c4 + 5, 8 * c3 + 7, 384 * c1 + c5);
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; CHECK-NEXT: Stmt_for_body6(128 * c2 + 8 * c4 + 6, 8 * c3, 384 * c1 + c5);
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; CHECK-NEXT: Stmt_for_body6(128 * c2 + 8 * c4 + 6, 8 * c3 + 1, 384 * c1 + c5);
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; CHECK-NEXT: Stmt_for_body6(128 * c2 + 8 * c4 + 6, 8 * c3 + 2, 384 * c1 + c5);
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; CHECK-NEXT: Stmt_for_body6(128 * c2 + 8 * c4 + 6, 8 * c3 + 3, 384 * c1 + c5);
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; CHECK-NEXT: Stmt_for_body6(128 * c2 + 8 * c4 + 6, 8 * c3 + 4, 384 * c1 + c5);
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; CHECK-NEXT: Stmt_for_body6(128 * c2 + 8 * c4 + 6, 8 * c3 + 5, 384 * c1 + c5);
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; CHECK-NEXT: Stmt_for_body6(128 * c2 + 8 * c4 + 6, 8 * c3 + 6, 384 * c1 + c5);
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; CHECK-NEXT: Stmt_for_body6(128 * c2 + 8 * c4 + 6, 8 * c3 + 7, 384 * c1 + c5);
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; CHECK-NEXT: Stmt_for_body6(128 * c2 + 8 * c4 + 7, 8 * c3, 384 * c1 + c5);
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; CHECK-NEXT: Stmt_for_body6(128 * c2 + 8 * c4 + 7, 8 * c3 + 1, 384 * c1 + c5);
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; CHECK-NEXT: Stmt_for_body6(128 * c2 + 8 * c4 + 7, 8 * c3 + 2, 384 * c1 + c5);
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; CHECK-NEXT: Stmt_for_body6(128 * c2 + 8 * c4 + 7, 8 * c3 + 3, 384 * c1 + c5);
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; CHECK-NEXT: Stmt_for_body6(128 * c2 + 8 * c4 + 7, 8 * c3 + 4, 384 * c1 + c5);
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; CHECK-NEXT: Stmt_for_body6(128 * c2 + 8 * c4 + 7, 8 * c3 + 5, 384 * c1 + c5);
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; CHECK-NEXT: Stmt_for_body6(128 * c2 + 8 * c4 + 7, 8 * c3 + 6, 384 * c1 + c5);
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; CHECK-NEXT: Stmt_for_body6(128 * c2 + 8 * c4 + 7, 8 * c3 + 7, 384 * c1 + c5);
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; CHECK-NEXT: }
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; CHECK-NEXT: }
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; CHECK-NEXT: }
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; CHECK-NEXT: }
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;
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target datalayout = "e-m:e-i64:64-f80:128-n8:16:32:64-S128"
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target triple = "x86_64-unknown-unknown"
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; Function Attrs: noinline nounwind uwtable
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define internal void @kernel_gemm(i32 %ni, i32 %nj, i32 %nk, float %alpha, float %beta, [1024 x float]* %C, [1024 x float]* %A, [1024 x float]* %B) #0 {
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entry:
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br label %entry.split
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entry.split: ; preds = %entry
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br label %for.cond1.preheader
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for.cond1.preheader: ; preds = %for.inc20, %entry.split
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%indvars.iv41 = phi i64 [ 0, %entry.split ], [ %indvars.iv.next42, %for.inc20 ]
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br label %for.cond4.preheader
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for.cond4.preheader: ; preds = %for.inc17, %for.cond1.preheader
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%indvars.iv38 = phi i64 [ 0, %for.cond1.preheader ], [ %indvars.iv.next39, %for.inc17 ]
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br label %for.body6
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for.body6: ; preds = %for.body6, %for.cond4.preheader
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%indvars.iv = phi i64 [ 0, %for.cond4.preheader ], [ %indvars.iv.next, %for.body6 ]
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%arrayidx8 = getelementptr inbounds [1024 x float], [1024 x float]* %A, i64 %indvars.iv41, i64 %indvars.iv
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%tmp = load float, float* %arrayidx8, align 4
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%arrayidx12 = getelementptr inbounds [1024 x float], [1024 x float]* %B, i64 %indvars.iv, i64 %indvars.iv38
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%tmp1 = load float, float* %arrayidx12, align 4
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%mul = fmul float %tmp, %tmp1
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%arrayidx16 = getelementptr inbounds [1024 x float], [1024 x float]* %C, i64 %indvars.iv41, i64 %indvars.iv38
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%tmp2 = load float, float* %arrayidx16, align 4
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%add = fadd float %tmp2, %mul
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store float %add, float* %arrayidx16, align 4
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%indvars.iv.next = add nuw nsw i64 %indvars.iv, 1
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%exitcond = icmp ne i64 %indvars.iv.next, 1024
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br i1 %exitcond, label %for.body6, label %for.inc17
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for.inc17: ; preds = %for.body6
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%indvars.iv.next39 = add nuw nsw i64 %indvars.iv38, 1
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%exitcond40 = icmp ne i64 %indvars.iv.next39, 1024
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br i1 %exitcond40, label %for.cond4.preheader, label %for.inc20
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for.inc20: ; preds = %for.inc17
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%indvars.iv.next42 = add nuw nsw i64 %indvars.iv41, 1
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%exitcond43 = icmp ne i64 %indvars.iv.next42, 1024
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br i1 %exitcond43, label %for.cond1.preheader, label %for.end22
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for.end22: ; preds = %for.inc20
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ret void
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}
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126
polly/test/ScheduleOptimizer/pattern-matching-based-opts_8.ll
Normal file
126
polly/test/ScheduleOptimizer/pattern-matching-based-opts_8.ll
Normal file
@ -0,0 +1,126 @@
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; RUN: opt %loadPolly -polly-opt-isl -polly-pattern-matching-based-opts=true \
|
||||
; RUN: -polly-target-throughput-vector-fma=1 \
|
||||
; RUN: -polly-target-latency-vector-fma=8 \
|
||||
; RUN: -analyze -polly-ast -polly-target-1st-cache-level-associativity=8 \
|
||||
; RUN: -polly-target-2nd-cache-level-associativity=8 \
|
||||
; RUN: -polly-target-1st-cache-level-size=32768 \
|
||||
; RUN: -polly-target-vector-register-bitwidth=256 \
|
||||
; RUN: -polly-target-2nd-cache-level-size=262144 < %s \
|
||||
; RUN: | FileCheck %s
|
||||
;
|
||||
; /* C := A * B + C */
|
||||
; /* Elements of the matrices B, C have the double type. */
|
||||
; /* Elements of the matrix A have the float type. */
|
||||
; /* The type size of elements of the matrix multiplication operands is used
|
||||
; to determine the parameters of the code produced by the optimization
|
||||
; of the matrix multiplication (e.g. bounds of the loops of the loop
|
||||
; nest, the innermost loop body). This test checks the form of
|
||||
; the generated loop nest. See getMicroKernelParams and
|
||||
; getMacroKernelParams from lib/Transform/ScheduleOptimizer.cpp
|
||||
; for details. */
|
||||
; for (i = 0; i < _PB_NI; i++)
|
||||
; for (j = 0; j < _PB_NJ; j++)
|
||||
; for (k = 0; k < _PB_NK; ++k)
|
||||
; C[i][j] += A[i][k] * B[k][j];
|
||||
;
|
||||
; CHECK: // 1st level tiling - Tiles
|
||||
; CHECK-NEXT: for (int c1 = 0; c1 <= 3; c1 += 1) {
|
||||
; CHECK-NEXT: for (int c3 = 0; c3 <= 1023; c3 += 1)
|
||||
; CHECK-NEXT: for (int c4 = 256 * c1; c4 <= 256 * c1 + 255; c4 += 1)
|
||||
; CHECK-NEXT: CopyStmt_0(0, c3, c4);
|
||||
; CHECK-NEXT: for (int c2 = 0; c2 <= 10; c2 += 1) {
|
||||
; CHECK-NEXT: for (int c3 = 96 * c2; c3 <= min(1023, 96 * c2 + 95); c3 += 1)
|
||||
; CHECK-NEXT: for (int c5 = 256 * c1; c5 <= 256 * c1 + 255; c5 += 1)
|
||||
; CHECK-NEXT: CopyStmt_1(c3, 0, c5);
|
||||
; CHECK-NEXT: // 1st level tiling - Points
|
||||
; CHECK-NEXT: // Register tiling - Tiles
|
||||
; CHECK-NEXT: for (int c3 = 0; c3 <= 127; c3 += 1)
|
||||
; CHECK-NEXT: for (int c4 = 0; c4 <= min(23, -24 * c2 + 255); c4 += 1)
|
||||
; CHECK-NEXT: for (int c5 = 0; c5 <= 255; c5 += 1) {
|
||||
; CHECK-NEXT: // Register tiling - Points
|
||||
; CHECK-NEXT: {
|
||||
; CHECK-NEXT: Stmt_for_body6(96 * c2 + 4 * c4, 8 * c3, 256 * c1 + c5);
|
||||
; CHECK-NEXT: Stmt_for_body6(96 * c2 + 4 * c4, 8 * c3 + 1, 256 * c1 + c5);
|
||||
; CHECK-NEXT: Stmt_for_body6(96 * c2 + 4 * c4, 8 * c3 + 2, 256 * c1 + c5);
|
||||
; CHECK-NEXT: Stmt_for_body6(96 * c2 + 4 * c4, 8 * c3 + 3, 256 * c1 + c5);
|
||||
; CHECK-NEXT: Stmt_for_body6(96 * c2 + 4 * c4, 8 * c3 + 4, 256 * c1 + c5);
|
||||
; CHECK-NEXT: Stmt_for_body6(96 * c2 + 4 * c4, 8 * c3 + 5, 256 * c1 + c5);
|
||||
; CHECK-NEXT: Stmt_for_body6(96 * c2 + 4 * c4, 8 * c3 + 6, 256 * c1 + c5);
|
||||
; CHECK-NEXT: Stmt_for_body6(96 * c2 + 4 * c4, 8 * c3 + 7, 256 * c1 + c5);
|
||||
; CHECK-NEXT: Stmt_for_body6(96 * c2 + 4 * c4 + 1, 8 * c3, 256 * c1 + c5);
|
||||
; CHECK-NEXT: Stmt_for_body6(96 * c2 + 4 * c4 + 1, 8 * c3 + 1, 256 * c1 + c5);
|
||||
; CHECK-NEXT: Stmt_for_body6(96 * c2 + 4 * c4 + 1, 8 * c3 + 2, 256 * c1 + c5);
|
||||
; CHECK-NEXT: Stmt_for_body6(96 * c2 + 4 * c4 + 1, 8 * c3 + 3, 256 * c1 + c5);
|
||||
; CHECK-NEXT: Stmt_for_body6(96 * c2 + 4 * c4 + 1, 8 * c3 + 4, 256 * c1 + c5);
|
||||
; CHECK-NEXT: Stmt_for_body6(96 * c2 + 4 * c4 + 1, 8 * c3 + 5, 256 * c1 + c5);
|
||||
; CHECK-NEXT: Stmt_for_body6(96 * c2 + 4 * c4 + 1, 8 * c3 + 6, 256 * c1 + c5);
|
||||
; CHECK-NEXT: Stmt_for_body6(96 * c2 + 4 * c4 + 1, 8 * c3 + 7, 256 * c1 + c5);
|
||||
; CHECK-NEXT: Stmt_for_body6(96 * c2 + 4 * c4 + 2, 8 * c3, 256 * c1 + c5);
|
||||
; CHECK-NEXT: Stmt_for_body6(96 * c2 + 4 * c4 + 2, 8 * c3 + 1, 256 * c1 + c5);
|
||||
; CHECK-NEXT: Stmt_for_body6(96 * c2 + 4 * c4 + 2, 8 * c3 + 2, 256 * c1 + c5);
|
||||
; CHECK-NEXT: Stmt_for_body6(96 * c2 + 4 * c4 + 2, 8 * c3 + 3, 256 * c1 + c5);
|
||||
; CHECK-NEXT: Stmt_for_body6(96 * c2 + 4 * c4 + 2, 8 * c3 + 4, 256 * c1 + c5);
|
||||
; CHECK-NEXT: Stmt_for_body6(96 * c2 + 4 * c4 + 2, 8 * c3 + 5, 256 * c1 + c5);
|
||||
; CHECK-NEXT: Stmt_for_body6(96 * c2 + 4 * c4 + 2, 8 * c3 + 6, 256 * c1 + c5);
|
||||
; CHECK-NEXT: Stmt_for_body6(96 * c2 + 4 * c4 + 2, 8 * c3 + 7, 256 * c1 + c5);
|
||||
; CHECK-NEXT: Stmt_for_body6(96 * c2 + 4 * c4 + 3, 8 * c3, 256 * c1 + c5);
|
||||
; CHECK-NEXT: Stmt_for_body6(96 * c2 + 4 * c4 + 3, 8 * c3 + 1, 256 * c1 + c5);
|
||||
; CHECK-NEXT: Stmt_for_body6(96 * c2 + 4 * c4 + 3, 8 * c3 + 2, 256 * c1 + c5);
|
||||
; CHECK-NEXT: Stmt_for_body6(96 * c2 + 4 * c4 + 3, 8 * c3 + 3, 256 * c1 + c5);
|
||||
; CHECK-NEXT: Stmt_for_body6(96 * c2 + 4 * c4 + 3, 8 * c3 + 4, 256 * c1 + c5);
|
||||
; CHECK-NEXT: Stmt_for_body6(96 * c2 + 4 * c4 + 3, 8 * c3 + 5, 256 * c1 + c5);
|
||||
; CHECK-NEXT: Stmt_for_body6(96 * c2 + 4 * c4 + 3, 8 * c3 + 6, 256 * c1 + c5);
|
||||
; CHECK-NEXT: Stmt_for_body6(96 * c2 + 4 * c4 + 3, 8 * c3 + 7, 256 * c1 + c5);
|
||||
; CHECK-NEXT: }
|
||||
; CHECK-NEXT: }
|
||||
; CHECK-NEXT: }
|
||||
; CHECK-NEXT: }
|
||||
;
|
||||
target datalayout = "e-m:e-i64:64-f80:128-n8:16:32:64-S128"
|
||||
target triple = "x86_64-unknown-unknown"
|
||||
|
||||
; Function Attrs: noinline nounwind uwtable
|
||||
define internal void @kernel_gemm(i32 %ni, i32 %nj, i32 %nk, double %alpha, double %beta, [1024 x double]* %C, [1024 x float]* %A, [1024 x double]* %B) #0 {
|
||||
entry:
|
||||
br label %entry.split
|
||||
|
||||
entry.split: ; preds = %entry
|
||||
br label %for.cond1.preheader
|
||||
|
||||
for.cond1.preheader: ; preds = %for.inc20, %entry.split
|
||||
%indvars.iv41 = phi i64 [ 0, %entry.split ], [ %indvars.iv.next42, %for.inc20 ]
|
||||
br label %for.cond4.preheader
|
||||
|
||||
for.cond4.preheader: ; preds = %for.inc17, %for.cond1.preheader
|
||||
%indvars.iv38 = phi i64 [ 0, %for.cond1.preheader ], [ %indvars.iv.next39, %for.inc17 ]
|
||||
br label %for.body6
|
||||
|
||||
for.body6: ; preds = %for.body6, %for.cond4.preheader
|
||||
%indvars.iv = phi i64 [ 0, %for.cond4.preheader ], [ %indvars.iv.next, %for.body6 ]
|
||||
%arrayidx8 = getelementptr inbounds [1024 x float], [1024 x float]* %A, i64 %indvars.iv41, i64 %indvars.iv
|
||||
%tmp = load float, float* %arrayidx8, align 4
|
||||
%conv = fpext float %tmp to double
|
||||
%arrayidx12 = getelementptr inbounds [1024 x double], [1024 x double]* %B, i64 %indvars.iv, i64 %indvars.iv38
|
||||
%tmp1 = load double, double* %arrayidx12, align 8
|
||||
%mul = fmul double %conv, %tmp1
|
||||
%arrayidx16 = getelementptr inbounds [1024 x double], [1024 x double]* %C, i64 %indvars.iv41, i64 %indvars.iv38
|
||||
%tmp2 = load double, double* %arrayidx16, align 8
|
||||
%add = fadd double %tmp2, %mul
|
||||
store double %add, double* %arrayidx16, align 8
|
||||
%indvars.iv.next = add nuw nsw i64 %indvars.iv, 1
|
||||
%exitcond = icmp ne i64 %indvars.iv.next, 1024
|
||||
br i1 %exitcond, label %for.body6, label %for.inc17
|
||||
|
||||
for.inc17: ; preds = %for.body6
|
||||
%indvars.iv.next39 = add nuw nsw i64 %indvars.iv38, 1
|
||||
%exitcond40 = icmp ne i64 %indvars.iv.next39, 1024
|
||||
br i1 %exitcond40, label %for.cond4.preheader, label %for.inc20
|
||||
|
||||
for.inc20: ; preds = %for.inc17
|
||||
%indvars.iv.next42 = add nuw nsw i64 %indvars.iv41, 1
|
||||
%exitcond43 = icmp ne i64 %indvars.iv.next42, 1024
|
||||
br i1 %exitcond43, label %for.cond1.preheader, label %for.end22
|
||||
|
||||
for.end22: ; preds = %for.inc20
|
||||
ret void
|
||||
}
|
||||
Loading…
Reference in New Issue
Block a user