# Fancy LLVM loop transformation pass that deoptimize the code

**URL:** <https://discourse.julialang.org/t/fancy-llvm-loop-transformation-pass-that-deoptimize-the-code/128100>\
**Category:** Performance\
**Tags:** llvm\
**Created:** [April 15, 2025, 3:03pm UTC](https://discourse.julialang.org/t/fancy-llvm-loop-transformation-pass-that-deoptimize-the-code/128100 "2025-04-15T15:03:05Z")\
**Posts on this page:** 3\
**Page:** 1

<div class="post-metadata">

**Author:** ![JohnnyChen94](https://sea2.discourse-cdn.com/julialang/user_avatar/discourse.julialang.org/johnnychen94/32/29979_2.png) [@JohnnyChen94](https://discourse.julialang.org/u/JohnnyChen94)\
**Post date:** [April 15, 2025, 3:03pm UTC](https://discourse.julialang.org/t/fancy-llvm-loop-transformation-pass-that-deoptimize-the-code/128100/1 "2025-04-15T15:03:05Z")

</div>

Recently we’ve seen one strange performance regression report, and the following is a MWE we can get:

```julia
using BenchmarkTools

function rand_n_1(a,n)
    r = Vector{UInt}(undef,n)
    @inbounds for i in 1:n
        p = a[1] - a[2]
        a[1] = a[2]
        a[2] = a[3]
        a[3] = p
        r[i] = p
    end
    return r
end

function rand_n_2(a,n)
    r = Vector{UInt}(undef,n)
    @inbounds for i in 1:n
        p = a[1] - a[2]
        a[1] = a[2] * 2
        a[2] = a[3] * 3
        a[3] = p * 4
        r[i] = p
    end
    return r
end

a = UInt[1, 2, 3]

# 43.626 ms (3 allocations: 76.30 MiB)
@btime rand_n_1(a, 10^7);
# 20.388 ms (3 allocations: 76.30 MiB)
@btime rand_n_2(a, 10^7);

```

The `rand_n_2` is a baseline version, and I expect that `rand_n_1` is at least as fast as `rand_n_2`. But surprisingly, it isn’t.

By checking the LLVM IR, the slow version introduces an instead _overly smart_ optimization pass (unroll and vectorize the loop), while the fast version is more or less _scalar_.

Although we’ve found ways to rewrite the function structure so that Julia/llvm _fails to recognize the pattern_ and thus works around the performance regression, I’d like to know the suggested fix for such issues since both versions look good.

> **@code\_llvm rand\_n\_1(a, 10^7)**
>
> ```julia
> ; Function Signature: rand_n_1(Array{UInt64, 1}, Int64)
> ; @ /home/chenjiuning/Documents/ai/LazyFFTW/example3.jl:3 within `rand_n_1`
> define nonnull ptr @julia_rand_n_1_2870(ptr noundef nonnull align 8 dereferenceable(24) %"a::Array", i64 signext %"n::Int64") #0 {
> top:
> %gcframe1 = alloca [3 x ptr], align 16
> call void @llvm.memset.p0.i64(ptr align 16 %gcframe1, i8 0, i64 24, i1 true)
> %thread_ptr = call ptr asm "movq %fs:0, $0", "=r"() #12
> %tls_ppgcstack = getelementptr inbounds i8, ptr %thread_ptr, i64 -8
> %tls_pgcstack = load ptr, ptr %tls_ppgcstack, align 8
> store i64 4, ptr %gcframe1, align 8
> %frame.prev = getelementptr inbounds ptr, ptr %gcframe1, i64 1
> %task.gcstack = load ptr, ptr %tls_pgcstack, align 8
> store ptr %task.gcstack, ptr %frame.prev, align 8
> store ptr %gcframe1, ptr %tls_pgcstack, align 8
> ; @ /home/chenjiuning/Documents/ai/LazyFFTW/example3.jl:4 within `rand_n_1`
> ; ┌ @ boot.jl:647 within `Array`
> ; │┌ @ boot.jl:588 within `GenericMemory`
> %memorynew_empty = icmp eq i64 %"n::Int64", 0
> br i1 %memorynew_empty, label %retval, label %nonemptymem
> 
> L21: ; preds = %L21.preheader.new, %L21
> %value_phi5 = phi i64 [1, %L21.preheader.new], [%16, %L21]
> %niter = phi i64 [0, %L21.preheader.new], [%niter.next.3, %L21]
> ; └└
> ; @ /home/chenjiuning/Documents/ai/LazyFFTW/example3.jl:6 within `rand_n_1`
> ; ┌ @ essentials.jl:918 within `getindex`
> %0 = load i64, ptr %memoryref_data, align 8
> %1 = load <2 x i64>, ptr %memoryref_data19, align 8
> ; └
> ; ┌ @ int.jl:86 within `-`
> %2 = extractelement <2 x i64> %1, i64 0
> %3 = sub i64 %0, %2
> ; └
> ; @ /home/chenjiuning/Documents/ai/LazyFFTW/example3.jl:7 within `rand_n_1`
> ; ┌ @ array.jl:986 within `setindex!`
> ; │┌ @ array.jl:991 within `_setindex!`
> store <2 x i64> %1, ptr %memoryref_data, align 8
> ; └└
> ; @ /home/chenjiuning/Documents/ai/LazyFFTW/example3.jl:9 within `rand_n_1`
> ; ┌ @ array.jl:986 within `setindex!`
> ; │┌ @ array.jl:991 within `_setindex!`
> store i64 %3, ptr %memoryref_data52, align 8
> ; └└
> ; @ /home/chenjiuning/Documents/ai/LazyFFTW/example3.jl:10 within `rand_n_1`
> ; ┌ @ array.jl:986 within `setindex!`
> ; │┌ @ array.jl:991 within `_setindex!`
> %gep = getelementptr i64, ptr %invariant.gep, i64 %value_phi5
> store i64 %3, ptr %gep, align 8
> ; └└
> ; @ /home/chenjiuning/Documents/ai/LazyFFTW/example3.jl:6 within `rand_n_1`
> ; ┌ @ essentials.jl:918 within `getindex`
> %4 = load i64, ptr %memoryref_data, align 8
> %5 = load <2 x i64>, ptr %memoryref_data19, align 8
> ; └
> ; ┌ @ int.jl:86 within `-`
> %6 = extractelement <2 x i64> %5, i64 0
> %7 = sub i64 %4, %6
> ; └
> ; @ /home/chenjiuning/Documents/ai/LazyFFTW/example3.jl:7 within `rand_n_1`
> ; ┌ @ array.jl:986 within `setindex!`
> ; │┌ @ array.jl:991 within `_setindex!`
> store <2 x i64> %5, ptr %memoryref_data, align 8
> ; └└
> ; @ /home/chenjiuning/Documents/ai/LazyFFTW/example3.jl:9 within `rand_n_1`
> ; ┌ @ array.jl:986 within `setindex!`
> ; │┌ @ array.jl:991 within `_setindex!`
> store i64 %7, ptr %memoryref_data52, align 8
> ; └└
> ; @ /home/chenjiuning/Documents/ai/LazyFFTW/example3.jl:10 within `rand_n_1`
> ; ┌ @ array.jl:986 within `setindex!`
> ; │┌ @ array.jl:991 within `_setindex!`
> %gep.1 = getelementptr i64, ptr %memory_data, i64 %value_phi5
> store i64 %7, ptr %gep.1, align 8
> ; └└
> ; @ /home/chenjiuning/Documents/ai/LazyFFTW/example3.jl:6 within `rand_n_1`
> ; ┌ @ essentials.jl:918 within `getindex`
> %8 = load i64, ptr %memoryref_data, align 8
> %9 = load <2 x i64>, ptr %memoryref_data19, align 8
> ; └
> ; ┌ @ int.jl:86 within `-`
> %10 = extractelement <2 x i64> %9, i64 0
> %11 = sub i64 %8, %10
> ; └
> ; @ /home/chenjiuning/Documents/ai/LazyFFTW/example3.jl:7 within `rand_n_1`
> ; ┌ @ array.jl:986 within `setindex!`
> ; │┌ @ array.jl:991 within `_setindex!`
> store <2 x i64> %9, ptr %memoryref_data, align 8
> ; └└
> ; @ /home/chenjiuning/Documents/ai/LazyFFTW/example3.jl:9 within `rand_n_1`
> ; ┌ @ array.jl:986 within `setindex!`
> ; │┌ @ array.jl:991 within `_setindex!`
> store i64 %11, ptr %memoryref_data52, align 8
> ; └└
> ; @ /home/chenjiuning/Documents/ai/LazyFFTW/example3.jl:10 within `rand_n_1`
> ; ┌ @ array.jl:986 within `setindex!`
> ; │┌ @ array.jl:991 within `_setindex!`
> %gep.2 = getelementptr i64, ptr %gep, i64 2
> store i64 %11, ptr %gep.2, align 8
> ; └└
> ; @ /home/chenjiuning/Documents/ai/LazyFFTW/example3.jl:6 within `rand_n_1`
> ; ┌ @ essentials.jl:918 within `getindex`
> %12 = load i64, ptr %memoryref_data, align 8
> %13 = load <2 x i64>, ptr %memoryref_data19, align 8
> ; └
> ; ┌ @ int.jl:86 within `-`
> %14 = extractelement <2 x i64> %13, i64 0
> %15 = sub i64 %12, %14
> ; └
> ; @ /home/chenjiuning/Documents/ai/LazyFFTW/example3.jl:7 within `rand_n_1`
> ; ┌ @ array.jl:986 within `setindex!`
> ; │┌ @ array.jl:991 within `_setindex!`
> store <2 x i64> %13, ptr %memoryref_data, align 8
> ; └└
> ; @ /home/chenjiuning/Documents/ai/LazyFFTW/example3.jl:9 within `rand_n_1`
> ; ┌ @ array.jl:986 within `setindex!`
> ; │┌ @ array.jl:991 within `_setindex!`
> store i64 %15, ptr %memoryref_data52, align 8
> ; └└
> ; @ /home/chenjiuning/Documents/ai/LazyFFTW/example3.jl:10 within `rand_n_1`
> ; ┌ @ array.jl:986 within `setindex!`
> ; │┌ @ array.jl:991 within `_setindex!`
> %gep.3 = getelementptr i64, ptr %gep, i64 3
> store i64 %15, ptr %gep.3, align 8
> ; └└
> ; @ /home/chenjiuning/Documents/ai/LazyFFTW/example3.jl:11 within `rand_n_1`
> ; ┌ @ range.jl:921 within `iterate`
> %16 = add i64 %value_phi5, 4
> ; └
> %niter.next.3 = add i64 %niter, 4
> %niter.ncmp.3 = icmp eq i64 %niter.next.3, %unroll_iter
> br i1 %niter.ncmp.3, label %L183.loopexit.unr-lcssa, label %L21
> 
> L183.loopexit.unr-lcssa: ; preds = %L21.preheader, %L21
> %value_phi5.unr = phi i64 [1, %L21.preheader], [%16, %L21]
> %lcmp.mod.not = icmp eq i64 %xtraiter, 0
> br i1 %lcmp.mod.not, label %L183, label %L21.epil
> 
> L21.epil: ; preds = %L21.epil, %L183.loopexit.unr-lcssa
> %value_phi5.epil = phi i64 [%21, %L21.epil], [%value_phi5.unr, %L183.loopexit.unr-lcssa]
> %epil.iter = phi i64 [%epil.iter.next, %L21.epil], [0, %L183.loopexit.unr-lcssa]
> ; @ /home/chenjiuning/Documents/ai/LazyFFTW/example3.jl:6 within `rand_n_1`
> ; ┌ @ essentials.jl:918 within `getindex`
> %17 = load i64, ptr %memoryref_data, align 8
> %18 = load <2 x i64>, ptr %memoryref_data19, align 8
> ; └
> ; ┌ @ int.jl:86 within `-`
> %19 = extractelement <2 x i64> %18, i64 0
> %20 = sub i64 %17, %19
> ; └
> ; @ /home/chenjiuning/Documents/ai/LazyFFTW/example3.jl:7 within `rand_n_1`
> ; ┌ @ array.jl:986 within `setindex!`
> ; │┌ @ array.jl:991 within `_setindex!`
> store <2 x i64> %18, ptr %memoryref_data, align 8
> ; └└
> ; @ /home/chenjiuning/Documents/ai/LazyFFTW/example3.jl:9 within `rand_n_1`
> ; ┌ @ array.jl:986 within `setindex!`
> ; │┌ @ array.jl:991 within `_setindex!`
> store i64 %20, ptr %memoryref_data52, align 8
> ; └└
> ; @ /home/chenjiuning/Documents/ai/LazyFFTW/example3.jl:10 within `rand_n_1`
> ; ┌ @ array.jl:986 within `setindex!`
> ; │┌ @ array.jl:991 within `_setindex!`
> %gep.epil = getelementptr i64, ptr %invariant.gep, i64 %value_phi5.epil
> store i64 %20, ptr %gep.epil, align 8
> ; └└
> ; @ /home/chenjiuning/Documents/ai/LazyFFTW/example3.jl:11 within `rand_n_1`
> ; ┌ @ range.jl:921 within `iterate`
> %21 = add i64 %value_phi5.epil, 1
> ; └
> %epil.iter.next = add i64 %epil.iter, 1
> %epil.iter.cmp.not = icmp eq i64 %epil.iter.next, %xtraiter
> br i1 %epil.iter.cmp.not, label %L183, label %L21.epil
> 
> L183: ; preds = %retval, %L21.epil, %L183.loopexit.unr-lcssa
> %frame.prev110 = load ptr, ptr %frame.prev, align 8
> store ptr %frame.prev110, ptr %tls_pgcstack, align 8
> ; @ /home/chenjiuning/Documents/ai/LazyFFTW/example3.jl:12 within `rand_n_1`
> ret ptr %"new::Array"
> 
> nonemptymem: ; preds = %top
> ; @ /home/chenjiuning/Documents/ai/LazyFFTW/example3.jl:4 within `rand_n_1`
> ; ┌ @ boot.jl:647 within `Array`
> ; │┌ @ boot.jl:588 within `GenericMemory`
> %22 = icmp ult i64 %"n::Int64", 1152921504606846976
> br i1 %22, label %pass, label %fail
> 
> fail: ; preds = %nonemptymem
> call void @jl_argument_error(ptr nonnull @"_j_str_invalid GenericMemory siz...#1")
> unreachable
> 
> pass: ; preds = %nonemptymem
> %23 = shl nuw nsw i64 %"n::Int64", 3
> %ptls_field = getelementptr inbounds i8, ptr %tls_pgcstack, i64 16
> %ptls_load = load ptr, ptr %ptls_field, align 8
> %"Memory{UInt64}[]" = call noalias nonnull align 16 ptr @jl_alloc_genericmemory_unchecked(ptr %ptls_load, i64 %23, ptr nonnull @"+Core.GenericMemory#2873.jit") #13
> store i64 %"n::Int64", ptr %"Memory{UInt64}[]", align 8
> br label %retval
> 
> retval: ; preds = %pass, %top
> %memoryref_mem81 = phi ptr [%"Memory{UInt64}[]", %pass ], [@"jl_global#2872.jit", %top]
> ; │└
> ; │ @ boot.jl:648 within `Array`
> ; │┌ @ boot.jl:593 within `memoryref`
> %memory_data_ptr = getelementptr inbounds { i64, ptr }, ptr %memoryref_mem81, i64 0, i32 1
> %memory_data = load ptr, ptr %memory_data_ptr, align 8
> %gc_slot_addr_0 = getelementptr inbounds ptr, ptr %gcframe1, i64 2
> store ptr %memoryref_mem81, ptr %gc_slot_addr_0, align 8
> ; │└
> %ptls_field108 = getelementptr inbounds i8, ptr %tls_pgcstack, i64 16
> %ptls_load109 = load ptr, ptr %ptls_field108, align 8
> %"new::Array" = call noalias nonnull align 8 dereferenceable(32) ptr @ijl_gc_small_alloc(ptr %ptls_load109, i32 408, i32 32, i64 140686563959504) #8
> %"new::Array.tag_addr" = getelementptr inbounds i64, ptr %"new::Array", i64 -1
> store atomic i64 140686563959504, ptr %"new::Array.tag_addr" unordered, align 8
> %24 = getelementptr inbounds i8, ptr %"new::Array", i64 8
> store ptr %memory_data, ptr %"new::Array", align 8
> store ptr %memoryref_mem81, ptr %24, align 8
> %"new::Array.size_ptr" = getelementptr inbounds i8, ptr %"new::Array", i64 16
> store i64 %"n::Int64", ptr %"new::Array.size_ptr", align 8
> ; └
> ; @ /home/chenjiuning/Documents/ai/LazyFFTW/example3.jl:5 within `rand_n_1`
> br i1 %memorynew_empty, label %L183, label %L21.preheader
> 
> L21.preheader: ; preds = %retval
> %memoryref_data = load ptr, ptr %"a::Array", align 8
> %memoryref_data19 = getelementptr inbounds i64, ptr %memoryref_data, i64 1
> %memoryref_data52 = getelementptr inbounds i64, ptr %memoryref_data, i64 2
> ; @ /home/chenjiuning/Documents/ai/LazyFFTW/example3.jl:11 within `rand_n_1`
> %invariant.gep = getelementptr i64, ptr %memory_data, i64 -1
> %xtraiter = and i64 %"n::Int64", 3
> %25 = icmp ult i64 %"n::Int64", 4
> br i1 %25, label %L183.loopexit.unr-lcssa, label %L21.preheader.new
> 
> L21.preheader.new: ; preds = %L21.preheader
> %unroll_iter = and i64 %"n::Int64", -4
> br label %L21
> }
> 
> ```

> **@code\_llvm rand\_n\_2(a, 10^7)**
>
> ```julia
> ; Function Signature: rand_n_2(Array{UInt64, 1}, Int64)
> ; @ /home/chenjiuning/Documents/ai/LazyFFTW/example3.jl:15 within `rand_n_2`
> define nonnull ptr @julia_rand_n_2_2903(ptr noundef nonnull align 8 dereferenceable(24) %"a::Array", i64 signext %"n::Int64") #0 {
> top:
> %gcframe1 = alloca [3 x ptr], align 16
> call void @llvm.memset.p0.i64(ptr align 16 %gcframe1, i8 0, i64 24, i1 true)
> %thread_ptr = call ptr asm "movq %fs:0, $0", "=r"() #12
> %tls_ppgcstack = getelementptr inbounds i8, ptr %thread_ptr, i64 -8
> %tls_pgcstack = load ptr, ptr %tls_ppgcstack, align 8
> store i64 4, ptr %gcframe1, align 8
> %frame.prev = getelementptr inbounds ptr, ptr %gcframe1, i64 1
> %task.gcstack = load ptr, ptr %tls_pgcstack, align 8
> store ptr %task.gcstack, ptr %frame.prev, align 8
> store ptr %gcframe1, ptr %tls_pgcstack, align 8
> ; @ /home/chenjiuning/Documents/ai/LazyFFTW/example3.jl:16 within `rand_n_2`
> ; ┌ @ boot.jl:647 within `Array`
> ; │┌ @ boot.jl:588 within `GenericMemory`
> %memorynew_empty = icmp eq i64 %"n::Int64", 0
> br i1 %memorynew_empty, label %retval, label %nonemptymem
> 
> L21: ; preds = %L21.preheader.new, %L21
> %value_phi5 = phi i64 [1, %L21.preheader.new], [%28, %L21]
> %niter = phi i64 [0, %L21.preheader.new], [%niter.next.3, %L21]
> ; └└
> ; @ /home/chenjiuning/Documents/ai/LazyFFTW/example3.jl:18 within `rand_n_2`
> ; ┌ @ essentials.jl:918 within `getindex`
> %0 = load i64, ptr %memoryref_data, align 8
> %1 = load i64, ptr %memoryref_data19, align 8
> ; └
> ; ┌ @ int.jl:86 within `-`
> %2 = sub i64 %0, %1
> ; └
> ; @ /home/chenjiuning/Documents/ai/LazyFFTW/example3.jl:19 within `rand_n_2`
> ; ┌ @ int.jl:863 within `*` @ int.jl:88
> %3 = shl i64 %1, 1
> ; └
> ; ┌ @ array.jl:986 within `setindex!`
> ; │┌ @ array.jl:991 within `_setindex!`
> store i64 %3, ptr %memoryref_data, align 8
> ; └└
> ; @ /home/chenjiuning/Documents/ai/LazyFFTW/example3.jl:20 within `rand_n_2`
> ; ┌ @ essentials.jl:918 within `getindex`
> %4 = load i64, ptr %memoryref_data52, align 8
> ; └
> ; ┌ @ int.jl:863 within `*` @ int.jl:88
> %5 = mul i64 %4, 3
> ; └
> ; ┌ @ array.jl:986 within `setindex!`
> ; │┌ @ array.jl:991 within `_setindex!`
> store i64 %5, ptr %memoryref_data19, align 8
> ; └└
> ; @ /home/chenjiuning/Documents/ai/LazyFFTW/example3.jl:21 within `rand_n_2`
> ; ┌ @ int.jl:863 within `*` @ int.jl:88
> %6 = shl i64 %2, 2
> ; └
> ; ┌ @ array.jl:986 within `setindex!`
> ; │┌ @ array.jl:991 within `_setindex!`
> store i64 %6, ptr %memoryref_data52, align 8
> ; └└
> ; @ /home/chenjiuning/Documents/ai/LazyFFTW/example3.jl:22 within `rand_n_2`
> ; ┌ @ array.jl:986 within `setindex!`
> ; │┌ @ array.jl:991 within `_setindex!`
> %gep = getelementptr i64, ptr %invariant.gep, i64 %value_phi5
> store i64 %2, ptr %gep, align 8
> ; └└
> ; @ /home/chenjiuning/Documents/ai/LazyFFTW/example3.jl:18 within `rand_n_2`
> ; ┌ @ essentials.jl:918 within `getindex`
> %7 = load i64, ptr %memoryref_data, align 8
> %8 = load i64, ptr %memoryref_data19, align 8
> ; └
> ; ┌ @ int.jl:86 within `-`
> %9 = sub i64 %7, %8
> ; └
> ; @ /home/chenjiuning/Documents/ai/LazyFFTW/example3.jl:19 within `rand_n_2`
> ; ┌ @ int.jl:863 within `*` @ int.jl:88
> %10 = shl i64 %8, 1
> ; └
> ; ┌ @ array.jl:986 within `setindex!`
> ; │┌ @ array.jl:991 within `_setindex!`
> store i64 %10, ptr %memoryref_data, align 8
> ; └└
> ; @ /home/chenjiuning/Documents/ai/LazyFFTW/example3.jl:20 within `rand_n_2`
> ; ┌ @ essentials.jl:918 within `getindex`
> %11 = load i64, ptr %memoryref_data52, align 8
> ; └
> ; ┌ @ int.jl:863 within `*` @ int.jl:88
> %12 = mul i64 %11, 3
> ; └
> ; ┌ @ array.jl:986 within `setindex!`
> ; │┌ @ array.jl:991 within `_setindex!`
> store i64 %12, ptr %memoryref_data19, align 8
> ; └└
> ; @ /home/chenjiuning/Documents/ai/LazyFFTW/example3.jl:21 within `rand_n_2`
> ; ┌ @ int.jl:863 within `*` @ int.jl:88
> %13 = shl i64 %9, 2
> ; └
> ; ┌ @ array.jl:986 within `setindex!`
> ; │┌ @ array.jl:991 within `_setindex!`
> store i64 %13, ptr %memoryref_data52, align 8
> ; └└
> ; @ /home/chenjiuning/Documents/ai/LazyFFTW/example3.jl:22 within `rand_n_2`
> ; ┌ @ array.jl:986 within `setindex!`
> ; │┌ @ array.jl:991 within `_setindex!`
> %gep.1 = getelementptr i64, ptr %memory_data, i64 %value_phi5
> store i64 %9, ptr %gep.1, align 8
> ; └└
> ; @ /home/chenjiuning/Documents/ai/LazyFFTW/example3.jl:18 within `rand_n_2`
> ; ┌ @ essentials.jl:918 within `getindex`
> %14 = load i64, ptr %memoryref_data, align 8
> %15 = load i64, ptr %memoryref_data19, align 8
> ; └
> ; ┌ @ int.jl:86 within `-`
> %16 = sub i64 %14, %15
> ; └
> ; @ /home/chenjiuning/Documents/ai/LazyFFTW/example3.jl:19 within `rand_n_2`
> ; ┌ @ int.jl:863 within `*` @ int.jl:88
> %17 = shl i64 %15, 1
> ; └
> ; ┌ @ array.jl:986 within `setindex!`
> ; │┌ @ array.jl:991 within `_setindex!`
> store i64 %17, ptr %memoryref_data, align 8
> ; └└
> ; @ /home/chenjiuning/Documents/ai/LazyFFTW/example3.jl:20 within `rand_n_2`
> ; ┌ @ essentials.jl:918 within `getindex`
> %18 = load i64, ptr %memoryref_data52, align 8
> ; └
> ; ┌ @ int.jl:863 within `*` @ int.jl:88
> %19 = mul i64 %18, 3
> ; └
> ; ┌ @ array.jl:986 within `setindex!`
> ; │┌ @ array.jl:991 within `_setindex!`
> store i64 %19, ptr %memoryref_data19, align 8
> ; └└
> ; @ /home/chenjiuning/Documents/ai/LazyFFTW/example3.jl:21 within `rand_n_2`
> ; ┌ @ int.jl:863 within `*` @ int.jl:88
> %20 = shl i64 %16, 2
> ; └
> ; ┌ @ array.jl:986 within `setindex!`
> ; │┌ @ array.jl:991 within `_setindex!`
> store i64 %20, ptr %memoryref_data52, align 8
> ; └└
> ; @ /home/chenjiuning/Documents/ai/LazyFFTW/example3.jl:22 within `rand_n_2`
> ; ┌ @ array.jl:986 within `setindex!`
> ; │┌ @ array.jl:991 within `_setindex!`
> %gep.2 = getelementptr i64, ptr %gep, i64 2
> store i64 %16, ptr %gep.2, align 8
> ; └└
> ; @ /home/chenjiuning/Documents/ai/LazyFFTW/example3.jl:18 within `rand_n_2`
> ; ┌ @ essentials.jl:918 within `getindex`
> %21 = load i64, ptr %memoryref_data, align 8
> %22 = load i64, ptr %memoryref_data19, align 8
> ; └
> ; ┌ @ int.jl:86 within `-`
> %23 = sub i64 %21, %22
> ; └
> ; @ /home/chenjiuning/Documents/ai/LazyFFTW/example3.jl:19 within `rand_n_2`
> ; ┌ @ int.jl:863 within `*` @ int.jl:88
> %24 = shl i64 %22, 1
> ; └
> ; ┌ @ array.jl:986 within `setindex!`
> ; │┌ @ array.jl:991 within `_setindex!`
> store i64 %24, ptr %memoryref_data, align 8
> ; └└
> ; @ /home/chenjiuning/Documents/ai/LazyFFTW/example3.jl:20 within `rand_n_2`
> ; ┌ @ essentials.jl:918 within `getindex`
> %25 = load i64, ptr %memoryref_data52, align 8
> ; └
> ; ┌ @ int.jl:863 within `*` @ int.jl:88
> %26 = mul i64 %25, 3
> ; └
> ; ┌ @ array.jl:986 within `setindex!`
> ; │┌ @ array.jl:991 within `_setindex!`
> store i64 %26, ptr %memoryref_data19, align 8
> ; └└
> ; @ /home/chenjiuning/Documents/ai/LazyFFTW/example3.jl:21 within `rand_n_2`
> ; ┌ @ int.jl:863 within `*` @ int.jl:88
> %27 = shl i64 %23, 2
> ; └
> ; ┌ @ array.jl:986 within `setindex!`
> ; │┌ @ array.jl:991 within `_setindex!`
> store i64 %27, ptr %memoryref_data52, align 8
> ; └└
> ; @ /home/chenjiuning/Documents/ai/LazyFFTW/example3.jl:22 within `rand_n_2`
> ; ┌ @ array.jl:986 within `setindex!`
> ; │┌ @ array.jl:991 within `_setindex!`
> %gep.3 = getelementptr i64, ptr %gep, i64 3
> store i64 %23, ptr %gep.3, align 8
> ; └└
> ; @ /home/chenjiuning/Documents/ai/LazyFFTW/example3.jl:23 within `rand_n_2`
> ; ┌ @ range.jl:921 within `iterate`
> %28 = add i64 %value_phi5, 4
> ; └
> %niter.next.3 = add i64 %niter, 4
> %niter.ncmp.3 = icmp eq i64 %niter.next.3, %unroll_iter
> br i1 %niter.ncmp.3, label %L186.loopexit.unr-lcssa, label %L21
> 
> L186.loopexit.unr-lcssa: ; preds = %L21.preheader, %L21
> %value_phi5.unr = phi i64 [1, %L21.preheader], [%28, %L21]
> %lcmp.mod.not = icmp eq i64 %xtraiter, 0
> br i1 %lcmp.mod.not, label %L186, label %L21.epil
> 
> L21.epil: ; preds = %L21.epil, %L186.loopexit.unr-lcssa
> %value_phi5.epil = phi i64 [%36, %L21.epil], [%value_phi5.unr, %L186.loopexit.unr-lcssa]
> %epil.iter = phi i64 [%epil.iter.next, %L21.epil], [0, %L186.loopexit.unr-lcssa]
> ; @ /home/chenjiuning/Documents/ai/LazyFFTW/example3.jl:18 within `rand_n_2`
> ; ┌ @ essentials.jl:918 within `getindex`
> %29 = load i64, ptr %memoryref_data, align 8
> %30 = load i64, ptr %memoryref_data19, align 8
> ; └
> ; ┌ @ int.jl:86 within `-`
> %31 = sub i64 %29, %30
> ; └
> ; @ /home/chenjiuning/Documents/ai/LazyFFTW/example3.jl:19 within `rand_n_2`
> ; ┌ @ int.jl:863 within `*` @ int.jl:88
> %32 = shl i64 %30, 1
> ; └
> ; ┌ @ array.jl:986 within `setindex!`
> ; │┌ @ array.jl:991 within `_setindex!`
> store i64 %32, ptr %memoryref_data, align 8
> ; └└
> ; @ /home/chenjiuning/Documents/ai/LazyFFTW/example3.jl:20 within `rand_n_2`
> ; ┌ @ essentials.jl:918 within `getindex`
> %33 = load i64, ptr %memoryref_data52, align 8
> ; └
> ; ┌ @ int.jl:863 within `*` @ int.jl:88
> %34 = mul i64 %33, 3
> ; └
> ; ┌ @ array.jl:986 within `setindex!`
> ; │┌ @ array.jl:991 within `_setindex!`
> store i64 %34, ptr %memoryref_data19, align 8
> ; └└
> ; @ /home/chenjiuning/Documents/ai/LazyFFTW/example3.jl:21 within `rand_n_2`
> ; ┌ @ int.jl:863 within `*` @ int.jl:88
> %35 = shl i64 %31, 2
> ; └
> ; ┌ @ array.jl:986 within `setindex!`
> ; │┌ @ array.jl:991 within `_setindex!`
> store i64 %35, ptr %memoryref_data52, align 8
> ; └└
> ; @ /home/chenjiuning/Documents/ai/LazyFFTW/example3.jl:22 within `rand_n_2`
> ; ┌ @ array.jl:986 within `setindex!`
> ; │┌ @ array.jl:991 within `_setindex!`
> %gep.epil = getelementptr i64, ptr %invariant.gep, i64 %value_phi5.epil
> store i64 %31, ptr %gep.epil, align 8
> ; └└
> ; @ /home/chenjiuning/Documents/ai/LazyFFTW/example3.jl:23 within `rand_n_2`
> ; ┌ @ range.jl:921 within `iterate`
> %36 = add i64 %value_phi5.epil, 1
> ; └
> %epil.iter.next = add i64 %epil.iter, 1
> %epil.iter.cmp.not = icmp eq i64 %epil.iter.next, %xtraiter
> br i1 %epil.iter.cmp.not, label %L186, label %L21.epil
> 
> L186: ; preds = %retval, %L21.epil, %L186.loopexit.unr-lcssa
> %frame.prev110 = load ptr, ptr %frame.prev, align 8
> store ptr %frame.prev110, ptr %tls_pgcstack, align 8
> ; @ /home/chenjiuning/Documents/ai/LazyFFTW/example3.jl:24 within `rand_n_2`
> ret ptr %"new::Array"
> 
> nonemptymem: ; preds = %top
> ; @ /home/chenjiuning/Documents/ai/LazyFFTW/example3.jl:16 within `rand_n_2`
> ; ┌ @ boot.jl:647 within `Array`
> ; │┌ @ boot.jl:588 within `GenericMemory`
> %37 = icmp ult i64 %"n::Int64", 1152921504606846976
> br i1 %37, label %pass, label %fail
> 
> fail: ; preds = %nonemptymem
> call void @jl_argument_error(ptr nonnull @"_j_str_invalid GenericMemory siz...#1")
> unreachable
> 
> pass: ; preds = %nonemptymem
> %38 = shl nuw nsw i64 %"n::Int64", 3
> %ptls_field = getelementptr inbounds i8, ptr %tls_pgcstack, i64 16
> %ptls_load = load ptr, ptr %ptls_field, align 8
> %"Memory{UInt64}[]" = call noalias nonnull align 16 ptr @jl_alloc_genericmemory_unchecked(ptr %ptls_load, i64 %38, ptr nonnull @"+Core.GenericMemory#2906.jit") #13
> store i64 %"n::Int64", ptr %"Memory{UInt64}[]", align 8
> br label %retval
> 
> retval: ; preds = %pass, %top
> %memoryref_mem81 = phi ptr [%"Memory{UInt64}[]", %pass ], [@"jl_global#2905.jit", %top]
> ; │└
> ; │ @ boot.jl:648 within `Array`
> ; │┌ @ boot.jl:593 within `memoryref`
> %memory_data_ptr = getelementptr inbounds { i64, ptr }, ptr %memoryref_mem81, i64 0, i32 1
> %memory_data = load ptr, ptr %memory_data_ptr, align 8
> %gc_slot_addr_0 = getelementptr inbounds ptr, ptr %gcframe1, i64 2
> store ptr %memoryref_mem81, ptr %gc_slot_addr_0, align 8
> ; │└
> %ptls_field108 = getelementptr inbounds i8, ptr %tls_pgcstack, i64 16
> %ptls_load109 = load ptr, ptr %ptls_field108, align 8
> %"new::Array" = call noalias nonnull align 8 dereferenceable(32) ptr @ijl_gc_small_alloc(ptr %ptls_load109, i32 408, i32 32, i64 140686563959504) #8
> %"new::Array.tag_addr" = getelementptr inbounds i64, ptr %"new::Array", i64 -1
> store atomic i64 140686563959504, ptr %"new::Array.tag_addr" unordered, align 8
> %39 = getelementptr inbounds i8, ptr %"new::Array", i64 8
> store ptr %memory_data, ptr %"new::Array", align 8
> store ptr %memoryref_mem81, ptr %39, align 8
> %"new::Array.size_ptr" = getelementptr inbounds i8, ptr %"new::Array", i64 16
> store i64 %"n::Int64", ptr %"new::Array.size_ptr", align 8
> ; └
> ; @ /home/chenjiuning/Documents/ai/LazyFFTW/example3.jl:17 within `rand_n_2`
> br i1 %memorynew_empty, label %L186, label %L21.preheader
> 
> L21.preheader: ; preds = %retval
> %memoryref_data = load ptr, ptr %"a::Array", align 8
> %memoryref_data19 = getelementptr inbounds i64, ptr %memoryref_data, i64 1
> %memoryref_data52 = getelementptr inbounds i64, ptr %memoryref_data, i64 2
> ; @ /home/chenjiuning/Documents/ai/LazyFFTW/example3.jl:23 within `rand_n_2`
> %invariant.gep = getelementptr i64, ptr %memory_data, i64 -1
> %xtraiter = and i64 %"n::Int64", 3
> %40 = icmp ult i64 %"n::Int64", 4
> br i1 %40, label %L186.loopexit.unr-lcssa, label %L21.preheader.new
> 
> L21.preheader.new: ; preds = %L21.preheader
> %unroll_iter = and i64 %"n::Int64", -4
> br label %L21
> }
> 
> ```

---

<div class="post-metadata">

**Author:** ![vchuravy](https://sea2.discourse-cdn.com/julialang/user_avatar/discourse.julialang.org/vchuravy/32/8_2.png) [@vchuravy](https://discourse.julialang.org/u/vchuravy)\
**Post date:** [April 15, 2025, 7:34pm UTC](https://discourse.julialang.org/t/fancy-llvm-loop-transformation-pass-that-deoptimize-the-code/128100/2 "2025-04-15T19:34:38Z")

</div>

You can use Loopinfo to block vectorization or unrolling.

> **[GitHub - JuliaSIMD/LLVMLoopInfo.jl: Pass loop info to LLVM](https://github.com/JuliaSIMD/LLVMLoopInfo.jl)**
>
> Pass loop info to LLVM

---

<div class="post-metadata">

**Author:** ![foobar\_lv2](https://avatars.discourse-cdn.com/v4/letter/f/ee59a6/32.png) [@foobar\_lv2](https://discourse.julialang.org/u/foobar_lv2)\
**Post date:** [April 16, 2025, 11:27am UTC](https://discourse.julialang.org/t/fancy-llvm-loop-transformation-pass-that-deoptimize-the-code/128100/3 "2025-04-16T11:27:00Z")

</div>

An even smaller reproducer is

```julia
julia> function foo1(a)
       @inbounds begin
       p = a[1] - a[2]
       a[1] = a[2]
       a[2] = a[3]
       a[3] = p
       end
       p
       end
foo1 (generic function with 1 method)

julia> function foo2(a)
       @inbounds begin
       p = a[1] - a[2]
       a[1] = a[2]*2
       a[2] = a[3]*3
       a[3] = p*4
       end
       p
       end
foo2 (generic function with 1 method)

julia> @btime foo1($a)
  3.343 ns (0 allocations: 0 bytes)
0x0000000000000000

julia> @btime foo2($a)
  1.933 ns (0 allocations: 0 bytes)
0x0000000000000000

```

So you see that this has nothing to do with loop transformation passes.

What I think is the issue is the following: The entire thing is limited on the latency of store-load forwarding. LLVM decides to vectorize the adjacent loads and stores, such that the store-load forwarding unit has to deal with partially overlapping loads/stores. Is there maybe a slow-path or lack of support for that?

That is a part of cpu performance manuals / design that I’m not overly acquainted with. A quick google found e.g. [Auto-Vectorization and Store-to-Load-Forwarding | Emanuel’s Blog](https://eme64.github.io/blog/2024/06/24/Auto-Vectorization-and-Store-to-Load-Forwarding.html) that discusses the problem in context of java C2.

So I’d say that this is an issue of machine code generation, not even llvm IR-level passes.

I mean, the obvious approach would be: Store-load forwarding sucks, even if it succeeds. You want to keep a in registers the whole time!

That may or may not apply to your real problem. If `a` is largish, then latency of store-load forwarding doesn’t matter; if `a` is small, then just put it into registers instead of memory.

PS. By “keep it in registers” I mean the following code transformation:

```julia
julia> function rand_n_3(a,n)
           r = Vector{UInt}(undef,n)
           @inbounds begin a1 = a[1]; a2=a[2]; a3=a[3]; end
           @inbounds for i in 1:n
               p = a1 - a2
               a1 = a2
               a2 = a3
               a3 = p
               r[i] = p
           end
           @inbounds begin a[1]=a1; a[2]=a2;a[3]=a3; end
           return r
       end
rand_n_3 (generic function with 1 method)

julia> @btime rand_n_3(a, 10^7);
  5.832 ms (3 allocations: 76.30 MiB)

julia> @btime rand_n_1(a, 10^7);
  37.014 ms (3 allocations: 76.30 MiB)

```

PPS. This is on an older intel machine. I would not be overly shocked if some ARM or newer Zen had a store-load forwarding unit that can cope with this kind of partial overlap (but I wouldn’t be surprised to learn that they can’t deal with it either).

The bad code is:

```julia
julia> @code_native foo1(a)
	.text
	.file	"foo1"
	.section	.ltext,"axl",@progbits
	.globl	julia_foo1_4233 # -- Begin function julia_foo1_4233
	.p2align	4, 0x90
	.type	julia_foo1_4233,@function
julia_foo1_4233: # @julia_foo1_4233
; Function Signature: foo1(Array{UInt64, 1})
; ┌ @ REPL[11]:1 within `foo1`
# %bb.0: # %top
	#DEBUG_VALUE: foo1:a <- [$rdi+0]
	push	rbp
	mov	rbp, rsp
; │ @ REPL[11]:3 within `foo1`
; │┌ @ essentials.jl:918 within `getindex`
	mov	rcx, qword ptr [rdi]
	mov	rax, qword ptr [rcx]
; load1
	vmovups	xmm0, xmmword ptr [rcx + 8]
; │└
; │┌ @ int.jl:86 within `-`
; load2
	sub	rax, qword ptr [rcx + 8]
; │└
; │ @ REPL[11]:4 within `foo1`
; │┌ @ array.jl:986 within `setindex!`
; ││┌ @ array.jl:991 within `_setindex!`
; store1 NOOO, don't do it! This store partially overlaps with load1 (and encompasses) load2. 
	vmovups	xmmword ptr [rcx], xmm0
; │└└
; │ @ REPL[11]:6 within `foo1`
; │┌ @ array.jl:986 within `setindex!`
; ││┌ @ array.jl:991 within `_setindex!`
;store2 NOOO, this partially overlaps with load1
	mov	qword ptr [rcx + 16], rax
; ││└
	pop	rbp
	ret
.Lfunc_end0:
	.size	julia_foo1_4233, .Lfunc_end0-julia_foo1_4233
; └└
                                        # -- End function
	.section	".note.GNU-stack","",@progbits

```

PPPS. The annoying fact is that the auto vectorization is a _good_ thing if you don’t call `foo` repeatedly in a tight loop; but it messes up the internal state of the store-load forwarding unit, so that it becomes a pessimization if you call it repeatedly on the same `a` without enough delay for the writes to reach L1. In your example, llvm _knows_ that it does this operation repeatedly on the same `a`, so there is no excuse for the bad codegen; but for non-inlined `foo1` calls, it’s a trade-off.