当 C++ (LLVM) 可以时，为什么 Julia 不优化此代码？

Question

使用 LLVM 6.0.0 版的 C++ 编译器时，以下代码

bool isEven(int n) {
    bool ret = true;
    for (int i = 0; i < n; i ++) {
        ret = !ret;
    }
    return ret;
}

发出 LLVM IR

define zeroext i1 @_Z6isEveni(i32) local_unnamed_addr #0 !dbg !7 {
  call void @llvm.dbg.value(metadata i32 %0, metadata !14, metadata !DIExpression()), !dbg !18
  call void @llvm.dbg.value(metadata i8 1, metadata !15, metadata !DIExpression()), !dbg !19
  call void @llvm.dbg.value(metadata i32 0, metadata !16, metadata !DIExpression()), !dbg !20
  %2 = icmp slt i32 %0, 1, !dbg !21
  %3 = and i32 %0, 1, !dbg !23
  %4 = icmp eq i32 %3, 0, !dbg !23
  %5 = or i1 %4, %2, !dbg !23
  ret i1 %5, !dbg !24
}

declare void @llvm.dbg.value(metadata, metadata, metadata) #1

attributes #0 = { nounwind readnone uwtable "correctly-rounded-divide-sqrt-fp-math"="false" "disable-tail-calls"="false" "less-precise-fpmad"="false" "no-frame-pointer-elim"="false" "no-infs-fp-math"="false" "no-jump-tables"="false" "no-nans-fp-math"="false" "no-signed-zeros-fp-math"="false" "no-trapping-math"="false" "stack-protector-buffer-size"="8" "target-cpu"="x86-64" "target-features"="+fxsr,+mmx,+sse,+sse2,+x87" "unsafe-fp-math"="false" "use-soft-float"="false" }
attributes #1 = { nounwind readnone speculatable }

请参阅：https : //godbolt.org/z/oPBFey

这在功能上等同于以下实现：

julia> isEven(n::Int) = rem(n, 2) != 0
isEven (generic function with 1 method)

julia> @code_llvm debuginfo=:none isEven(7)

define i8 @julia_isEven_18796(i64) {
top:
  %1 = trunc i64 %0 to i8
  %2 = and i8 %1, 1
  %3 = xor i8 %2, 1
  ret i8 %3
}

julia>

但是，移植到 Julia 的原始 C++ 实现会导致非常不同的 LLVM IR：

julia> function isEven(n::Int)
           out = true
           for i in 0:n-1
               out = !out
           end
           return out
       end
isEven (generic function with 1 method)

julia> @code_llvm debuginfo=:none isEven(7)

define i8 @julia_isEven_18793(i64) {
top:
  %1 = add i64 %0, -1
  %2 = icmp sgt i64 %1, -1
  br i1 %2, label %L8.L12_crit_edge, label %L25

L8.L12_crit_edge:                                 ; preds = %top
  %min.iters.check = icmp ult i64 %0, 128
  br i1 %min.iters.check, label %scalar.ph, label %vector.ph

vector.ph:                                        ; preds = %L8.L12_crit_edge
  %n.vec = and i64 %0, -128
  br label %vector.body

vector.body:                                      ; preds = %vector.body, %vector.ph
  %index = phi i64 [ 0, %vector.ph ], [ %index.next, %vector.body ]
  %vec.phi = phi <32 x i8> [ <i8 1, i8 0, i8 0, i8 0, i8 0, i8 0, i8 0, i8 0, i8 0, i8 0, i8 0, i8 0, i8 0, i8 0, i8 0, i8 0, i8 0, i8 0, i8 0, i8 0, i8 0, i8 0, i8 0, i8 0, i8 0, i8 0, i8 0, i8 0, i8 0, i8 0, i8 0, i8 0>, %vector.ph ], [ %3, %vector.body ]
  %vec.phi8 = phi <32 x i8> [ zeroinitializer, %vector.ph ], [ %4, %vector.body ]
  %vec.phi9 = phi <32 x i8> [ zeroinitializer, %vector.ph ], [ %5, %vector.body ]
  %vec.phi10 = phi <32 x i8> [ zeroinitializer, %vector.ph ], [ %6, %vector.body ]
  %3 = xor <32 x i8> %vec.phi, <i8 1, i8 1, i8 1, i8 1, i8 1, i8 1, i8 1, i8 1, i8 1, i8 1, i8 1, i8 1, i8 1, i8 1, i8 1, i8 1, i8 1, i8 1, i8 1, i8 1, i8 1, i8 1, i8 1, i8 1, i8 1, i8 1, i8 1, i8 1, i8 1, i8 1, i8 1, i8 1>
  %4 = xor <32 x i8> %vec.phi8, <i8 1, i8 1, i8 1, i8 1, i8 1, i8 1, i8 1, i8 1, i8 1, i8 1, i8 1, i8 1, i8 1, i8 1, i8 1, i8 1, i8 1, i8 1, i8 1, i8 1, i8 1, i8 1, i8 1, i8 1, i8 1, i8 1, i8 1, i8 1, i8 1, i8 1, i8 1, i8 1>
  %5 = xor <32 x i8> %vec.phi9, <i8 1, i8 1, i8 1, i8 1, i8 1, i8 1, i8 1, i8 1, i8 1, i8 1, i8 1, i8 1, i8 1, i8 1, i8 1, i8 1, i8 1, i8 1, i8 1, i8 1, i8 1, i8 1, i8 1, i8 1, i8 1, i8 1, i8 1, i8 1, i8 1, i8 1, i8 1, i8 1>
  %6 = xor <32 x i8> %vec.phi10, <i8 1, i8 1, i8 1, i8 1, i8 1, i8 1, i8 1, i8 1, i8 1, i8 1, i8 1, i8 1, i8 1, i8 1, i8 1, i8 1, i8 1, i8 1, i8 1, i8 1, i8 1, i8 1, i8 1, i8 1, i8 1, i8 1, i8 1, i8 1, i8 1, i8 1, i8 1, i8 1>
  %index.next = add i64 %index, 128
  %7 = icmp eq i64 %index.next, %n.vec
  br i1 %7, label %middle.block, label %vector.body

middle.block:                                     ; preds = %vector.body
  %bin.rdx = xor <32 x i8> %vec.phi8, %vec.phi
  %bin.rdx14 = xor <32 x i8> %5, %bin.rdx
  %bin.rdx15 = xor <32 x i8> %6, %bin.rdx14
  %rdx.shuf = shufflevector <32 x i8> %bin.rdx15, <32 x i8> undef, <32 x i32> <i32 16, i32 17, i32 18, i32 19, i32 20, i32 21, i32 22, i32 23, i32 24, i32 25, i32 26, i32 27, i32 28, i32 29, i32 30, i32 31, i32 undef, i32 undef, i32 undef, i32 undef, i32 undef, i32 undef, i32 undef, i32 undef, i32 undef, i32 undef, i32 undef, i32 undef, i32 undef, i32 undef, i32 undef, i32 undef>
  %bin.rdx16 = xor <32 x i8> %bin.rdx15, %rdx.shuf
  %rdx.shuf17 = shufflevector <32 x i8> %bin.rdx16, <32 x i8> undef, <32 x i32> <i32 8, i32 9, i32 10, i32 11, i32 12, i32 13, i32 14, i32 15, i32 undef, i32 undef, i32 undef, i32 undef, i32 undef, i32 undef, i32 undef, i32 undef, i32 undef, i32 undef, i32 undef, i32 undef, i32 undef, i32 undef, i32 undef, i32 undef, i32 undef, i32 undef, i32 undef, i32 undef, i32 undef, i32 undef, i32 undef, i32 undef>
  %bin.rdx18 = xor <32 x i8> %bin.rdx16, %rdx.shuf17
  %rdx.shuf19 = shufflevector <32 x i8> %bin.rdx18, <32 x i8> undef, <32 x i32> <i32 4, i32 5, i32 6, i32 7, i32 undef, i32 undef, i32 undef, i32 undef, i32 undef, i32 undef, i32 undef, i32 undef, i32 undef, i32 undef, i32 undef, i32 undef, i32 undef, i32 undef, i32 undef, i32 undef, i32 undef, i32 undef, i32 undef, i32 undef, i32 undef, i32 undef, i32 undef, i32 undef, i32 undef, i32 undef, i32 undef, i32 undef>
  %bin.rdx20 = xor <32 x i8> %bin.rdx18, %rdx.shuf19
  %rdx.shuf21 = shufflevector <32 x i8> %bin.rdx20, <32 x i8> undef, <32 x i32> <i32 2, i32 3, i32 undef, i32 undef, i32 undef, i32 undef, i32 undef, i32 undef, i32 undef, i32 undef, i32 undef, i32 undef, i32 undef, i32 undef, i32 undef, i32 undef, i32 undef, i32 undef, i32 undef, i32 undef, i32 undef, i32 undef, i32 undef, i32 undef, i32 undef, i32 undef, i32 undef, i32 undef, i32 undef, i32 undef, i32 undef, i32 undef>
  %bin.rdx22 = xor <32 x i8> %bin.rdx20, %rdx.shuf21
  %rdx.shuf23 = shufflevector <32 x i8> %bin.rdx22, <32 x i8> undef, <32 x i32> <i32 1, i32 undef, i32 undef, i32 undef, i32 undef, i32 undef, i32 undef, i32 undef, i32 undef, i32 undef, i32 undef, i32 undef, i32 undef, i32 undef, i32 undef, i32 undef, i32 undef, i32 undef, i32 undef, i32 undef, i32 undef, i32 undef, i32 undef, i32 undef, i32 undef, i32 undef, i32 undef, i32 undef, i32 undef, i32 undef, i32 undef, i32 undef>
  %bin.rdx24 = xor <32 x i8> %bin.rdx22, %rdx.shuf23
  %8 = extractelement <32 x i8> %bin.rdx24, i32 0
  %cmp.n = icmp eq i64 %n.vec, %0
  br i1 %cmp.n, label %L25, label %scalar.ph

scalar.ph:                                        ; preds = %middle.block, %L8.L12_crit_edge
  %bc.resume.val = phi i64 [ %n.vec, %middle.block ], [ 0, %L8.L12_crit_edge ]
  %bc.merge.rdx = phi i8 [ %8, %middle.block ], [ 1, %L8.L12_crit_edge ]
  br label %L12

L12:                                              ; preds = %L12, %scalar.ph
  %value_phi2 = phi i8 [ %bc.merge.rdx, %scalar.ph ], [ %9, %L12 ]
  %value_phi3 = phi i64 [ %bc.resume.val, %scalar.ph ], [ %11, %L12 ]
  %9 = xor i8 %value_phi2, 1
  %10 = icmp eq i64 %value_phi3, %1
  %11 = add i64 %value_phi3, 1
  br i1 %10, label %L25, label %L12

L25:                                              ; preds = %L12, %middle.block, %top
  %value_phi6 = phi i8 [ 1, %top ], [ %9, %L12 ], [ %8, %middle.block ]
  ret i8 %value_phi6
}


julia> versioninfo()
Julia Version 1.3.1
Commit 2d5741174c (2019-12-30 21:36 UTC)
Platform Info:
  OS: macOS (x86_64-apple-darwin18.6.0)
  CPU: Intel(R) Core(TM) i7-7920HQ CPU @ 3.10GHz
  WORD_SIZE: 64
  LIBM: libopenlibm
  LLVM: libLLVM-6.0.1 (ORCJIT, skylake)

julia>

谁能解释为什么 Julia 无法使用几乎相同版本的 LLVM 为本质上相同的代码生成与 C++ 编译器相同的 IR？

Answer 1

简短的回答是：Julia 和 C++ 是不同的语言，具有不同的语义和不同的编译器。

不同的语义意味着不同的合法优化。需要仔细观察才能知道这在 C++ 中是否合法，但在 Julia 中是否非法。如果是的话我会感到惊讶。

不同的编译器意味着编译器会做不同的事情。C++ 编译器已经投入了数十年甚至可能数亿美元的开发人员时间（即使其中很大一部分是由开源志愿者捐赠的）；即使像 Clang 这样的较年轻的编译器仍然能够直接基于 GCC 等较旧的编译器数十年经过验证的想法进行构建。

Julia 编译器于 2012 年首次启动。投入的时间少得多。事实上，我不认为它实际上有自己的优化器，直到 2017 年的 v0.6。LLVM确实有一个优化器，Julia 和 Clang 都使用。但他们使用它的方式不同，他们启用了不同的通行证，并为其提供不同的信息（因为语义不同）。另外，您正在查看LLVM 运行之前的代码。（所以可能想看看汇编）。两者之间的 LLVM 版本相同仅与存在哪些指令有关，与 LLVM 执行的优化无关，因为您在运行之前查看代码。