0956a606ff
Currently, in case of GEMM and the pattern matching based optimizations, we use only the SLP Vectorizer out of two LLVM vectorizers. Since the Loop Vectorizer can get in the way of optimal code generation, we disable the Loop Vectorizer for the innermost loop using mark nodes and emitting the corresponding metadata. Reviewed-by: Tobias Grosser <tobias@grosser.es> Differential Revision: https://reviews.llvm.org/D36928 llvm-svn: 311473
158 lines
10 KiB
LLVM
158 lines
10 KiB
LLVM
; 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: // Loop Vectorizer Disabled
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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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