JuliaSIMD / JuliaSIMD/LoopVectorization.jl
Reduction not found
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説明
Hi, here is a MWE of an unexpected error:
```
using LoopVectorization
function test(a, b)
#s = 0.0
@turbo for i in axes(a,1)
ai = 0.0
for j in axes(b,2)
bij = b[i, j]
ai += bij^2
end
ai = exp(ai)
a[i] = ai
end
return nothing
end
a = rand(256)
b = rand(256, 256)
test(a, b)
```
LoadError: LoadError: "Reduction not found."
Stacktrace:
[1] reduction_zero
@ $HOME\.julia\packages\LoopVectorization\7gWfp\src\modeling\costs.jl:649 [inlined]
[2] add_reduction_update_parent!(vparents::Vector{LoopVectorization.Operation}, deps::Vector{Symbol}, reduceddeps::Vector{Symbol}, ls::LoopVectorization.LoopSet, parent::LoopVectorization.Operation, instr::LoopVectorization.Instruction, reduction_ind::Int64, elementbytes::Int64)
@ LoopVectorization $HOME\.julia\packages\LoopVectorization\7gWfp\src\parse\add_compute.jl:255
If I use `a[i] = exp(ai)` instead of the last two lines, it works. It also works if the last two lines are `ai = exp(ai/2); a[i] = ai`. I feel the issue is related to your explanation in #498, but honestly I don't fully understand that. My general feeling there is that the error it gives is unnecessary and can be ignored if it can run... Is that correct?
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調査の方向性
Run the supplied Julia MWE with LoopVectorization and start by reading reduction_zero in src/modeling/costs.jl around line 649, then add_reduction_update_parent! in src/parse/add_compute.jl around line 255. Compare the failing assignment with the working variants and determine whether the reduction error is expected; done means the behavior is explained and the MWE no longer produces an unjustified error.
索引モデルが issue の本文から書いたものです。
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