julia - 当C++(LLVM)可以时，为什么Julia不优化此代码？

Question

在LLVM 6.0.0版中使用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 }

另请: https://godbolt.org/z/oPBFey

这在功能上等效于以下实现:

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++实现产生了截然不同的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无法为使用几乎相同版本的LLVM的实质上相同的代码产生与C++编译器相同的IR？

Answer 1

的简短答案是:
Julia和C++是具有不同语义和不同编译器的不同语言。

不同的语义意味着法律上的不同优化。
需要仔细检查一下这是否在C++中是合法的，而在Julia中却是非法的。
如果是的话，我会感到惊讶。

不同的编译器意味着编译器执行不同的操作。
C++编译器投入了数十年的时间，甚至可能花费了数亿美元的开发人员时间(即使其中很多是由开源志愿者捐赠的)；即使是像Clang这样的较年轻的编译器，也仍然可以直接基于GCC等较老的编译器数十年久经考验的思想来构建。

Julia编译器于2012年首次启动。
花费了更少的时间。实际上，直到2017年v0.6才真正拥有自己的优化器。
LLVM确实有Julia和Clang都使用的优化器。
但是他们使用的方式不同，它们启用了不同的 channel ，并且为它们提供了不同的信息(由于语义不同)。
另外，您正在运行LLVM之前查看代码。
(因此可能要看一下程序集的instread)。
两者之间的LLVM版本是否相同，仅取决于存在的指令，而与LLVM的优化无关，因为在运行代码之前您正在查看代码。