; 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 ; ; opt %loadPolly -polly-opt-isl -polly-pattern-matching-based-opts=true \ ; -polly-target-throughput-vector-fma=1 \ ; -polly-target-latency-vector-fma=8 \ ; -polly-codegen -polly-target-1st-cache-level-associativity=8 \ ; -polly-target-2nd-cache-level-associativity=8 \ ; -polly-target-1st-cache-level-size=32768 \ ; -polly-target-vector-register-bitwidth=256 \ ; -polly-target-2nd-cache-level-size=262144 -gvn -licm -slp-vectorizer \ ; -mcpu=corei7 -stats -S < %s 2>&1 | FileCheck %s \ ; --check-prefix=AUTO-VECTORIZATION ; ; ; /* We isolate a set of partial tile prefixes, which contains only partial ; tile prefixes that have exactly Mr x Nr iterations of the two innermost ; loops produced by the optimization of the matrix multiplication. Mr and ; Nr are parameters of the micro-kernel (see getMicroKernelParams and ; getMacroKernelParams from lib/Transform/ScheduleOptimizer.cpp for ; details). This test check that in case it cannot be proved that ; the number of loop iterations can be evenly divided by tile sizes ; and we tile and unroll the point loops, it helps to get rid of ; the conditional expressions of the unrolled innermost loops, which ; prevents stores and loads of the unrolled loops from being sunk ; and hoisted. Otherwise, it causes a run-time regression in comparison ; to the vectorized code with sunk and hoisted memory accesses. */ ; /* C := A * B + C */ ; for (i = 0; i < 1020; i++) ; for (j = 0; j < 1020; j++) ; for (k = 0; k < 1020; ++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 <= 1019; c3 += 1) ; CHECK-NEXT: for (int c4 = 256 * c1; c4 <= min(1019, 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(1019, 96 * c2 + 95); c3 += 1) ; CHECK-NEXT: for (int c5 = 256 * c1; c5 <= min(1019, 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: { ; CHECK-NEXT: for (int c3 = 0; c3 <= 126; c3 += 1) ; CHECK-NEXT: for (int c4 = 0; c4 <= min(23, -24 * c2 + 254); c4 += 1) ; CHECK-NEXT: for (int c5 = 0; c5 <= min(255, -256 * c1 + 1019); c5 += 1) { ; CHECK-NEXT: // Loop Vectorizer Disabled ; 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: for (int c4 = 0; c4 <= min(23, -24 * c2 + 254); c4 += 1) ; CHECK-NEXT: for (int c5 = 0; c5 <= min(255, -256 * c1 + 1019); c5 += 1) { ; CHECK-NEXT: // Loop Vectorizer Disabled ; CHECK-NEXT: // Register tiling - Points ; CHECK-NEXT: { ; CHECK-NEXT: Stmt_for_body6(96 * c2 + 4 * c4, 1016, 256 * c1 + c5); ; CHECK-NEXT: Stmt_for_body6(96 * c2 + 4 * c4, 1017, 256 * c1 + c5); ; CHECK-NEXT: Stmt_for_body6(96 * c2 + 4 * c4, 1018, 256 * c1 + c5); ; CHECK-NEXT: Stmt_for_body6(96 * c2 + 4 * c4, 1019, 256 * c1 + c5); ; CHECK-NEXT: Stmt_for_body6(96 * c2 + 4 * c4 + 1, 1016, 256 * c1 + c5); ; CHECK-NEXT: Stmt_for_body6(96 * c2 + 4 * c4 + 1, 1017, 256 * c1 + c5); ; CHECK-NEXT: Stmt_for_body6(96 * c2 + 4 * c4 + 1, 1018, 256 * c1 + c5); ; CHECK-NEXT: Stmt_for_body6(96 * c2 + 4 * c4 + 1, 1019, 256 * c1 + c5); ; CHECK-NEXT: Stmt_for_body6(96 * c2 + 4 * c4 + 2, 1016, 256 * c1 + c5); ; CHECK-NEXT: Stmt_for_body6(96 * c2 + 4 * c4 + 2, 1017, 256 * c1 + c5); ; CHECK-NEXT: Stmt_for_body6(96 * c2 + 4 * c4 + 2, 1018, 256 * c1 + c5); ; CHECK-NEXT: Stmt_for_body6(96 * c2 + 4 * c4 + 2, 1019, 256 * c1 + c5); ; CHECK-NEXT: Stmt_for_body6(96 * c2 + 4 * c4 + 3, 1016, 256 * c1 + c5); ; CHECK-NEXT: Stmt_for_body6(96 * c2 + 4 * c4 + 3, 1017, 256 * c1 + c5); ; CHECK-NEXT: Stmt_for_body6(96 * c2 + 4 * c4 + 3, 1018, 256 * c1 + c5); ; CHECK-NEXT: Stmt_for_body6(96 * c2 + 4 * c4 + 3, 1019, 256 * c1 + c5); ; CHECK-NEXT: } ; CHECK-NEXT: } ; CHECK-NEXT: } ; CHECK-NEXT: } ; CHECK-NEXT: } ; ; AUTO-VECTORIZATION: fmul <4 x double> ; AUTO-VECTORIZATION: fadd <4 x double> ; AUTO-VECTORIZATION: 36 SLP - Number of vector instructions generated ; AUTO-VECTORIZATION: 146 licm - Number of instructions hoisted out of loop ; AUTO-VECTORIZATION: 1 licm - Number of load insts hoisted or sunk ; AUTO-VECTORIZATION: 32 licm - Number of memory locations promoted to registers ; target datalayout = "e-m:e-i64:64-f80:128-n8:16:32:64-S128" target triple = "x86_64-unknown-unknown" define internal void @kernel_gemm(i32 %ni, i32 %nj, i32 %nk, double %alpha, double %beta, [1020 x double]* %C, [1020 x double]* %A, [1020 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 [1020 x double], [1020 x double]* %A, i64 %indvars.iv41, i64 %indvars.iv %tmp = load double, double* %arrayidx8, align 8 %arrayidx12 = getelementptr inbounds [1020 x double], [1020 x double]* %B, i64 %indvars.iv, i64 %indvars.iv38 %tmp1 = load double, double* %arrayidx12, align 8 %mul = fmul double %tmp, %tmp1 %arrayidx16 = getelementptr inbounds [1020 x double], [1020 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, 1020 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, 1020 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, 1020 br i1 %exitcond43, label %for.cond1.preheader, label %for.end22 for.end22: ; preds = %for.inc20 ret void } attributes #0 = { nounwind uwtable "target-cpu"="x86-64" "target-features"="+aes,+avx,+cmov,+cx16,+fxsr,+mmx,+pclmul,+popcnt,+sse,+sse2,+sse3,+sse4.1,+sse4.2,+ssse3,+x87,+xsave,+xsaveopt" }