53 lines
1.7 KiB
LLVM
53 lines
1.7 KiB
LLVM
; RUN: opt -S -loop-vectorize < %s 2>&1 -pass-remarks-analysis=.* | FileCheck %s
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; Test the optimization remark emitter for recognition
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; of a mathlib function vs. an arbitrary function.
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target datalayout = "e-m:o-i64:64-f80:128-n8:16:32:64-S128"
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target triple = "x86_64-apple-macosx10.14.0"
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@data = external local_unnamed_addr global [32768 x float], align 16
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; CHECK: loop not vectorized: library call cannot be vectorized
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define void @libcall_blocks_vectorization() {
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entry:
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br label %for.body
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for.cond.cleanup:
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ret void
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for.body:
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%indvars.iv = phi i64 [ 0, %entry ], [ %indvars.iv.next, %for.body ]
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%arrayidx = getelementptr inbounds [32768 x float], [32768 x float]* @data, i64 0, i64 %indvars.iv
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%t0 = load float, float* %arrayidx, align 4
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%sqrtf = tail call float @sqrtf(float %t0)
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store float %sqrtf, float* %arrayidx, align 4
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%indvars.iv.next = add nuw nsw i64 %indvars.iv, 1
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%exitcond = icmp eq i64 %indvars.iv.next, 32768
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br i1 %exitcond, label %for.cond.cleanup, label %for.body
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}
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; CHECK: loop not vectorized: call instruction cannot be vectorized
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define void @arbitrary_call_blocks_vectorization() {
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entry:
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br label %for.body
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for.cond.cleanup:
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ret void
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for.body:
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%indvars.iv = phi i64 [ 0, %entry ], [ %indvars.iv.next, %for.body ]
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%arrayidx = getelementptr inbounds [32768 x float], [32768 x float]* @data, i64 0, i64 %indvars.iv
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%t0 = load float, float* %arrayidx, align 4
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%sqrtf = tail call float @arbitrary(float %t0)
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store float %sqrtf, float* %arrayidx, align 4
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%indvars.iv.next = add nuw nsw i64 %indvars.iv, 1
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%exitcond = icmp eq i64 %indvars.iv.next, 32768
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br i1 %exitcond, label %for.cond.cleanup, label %for.body
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}
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declare float @sqrtf(float)
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declare float @arbitrary(float)
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