It this package work only with simple operations? Can I use SpinLock() inside cycle? Can I use variables declared outside cycle? (now I get UndefVarError: varname#661 not defined) Actually, I try to get a sum of multiple inversed matrices.

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:slight_smile: I want to do something like this: module A using Polyester, LinearAlgebra function f1() n = 1000 m = 10 mv = Vector{Matrix}(undef, n) sm = zeros(m, m) sdet = zero(Float64) l = Base.Threads.SpinLock() @inbounds @batch per=core for i = 1:n mv[i] = rand(m,m) lock(l) do s…

You could file an issue. But, you’re better off with something like using Polyester, LinearAlgebra function f3() n = 1000 m = 10 sms = Vector{Matrix{Float64}}(undef, Polyester.num_cores()) sdets = Vector{Float64}(undef, Polyester.num_cores()) d, r = divrem(n, Polyester.num_cores()) …

If you want to optimize the code further, it’s best to cut down on allocations: using VectorizedRNG function f4() n = 1000 m = 10 sms = Vector{Matrix{Float64}}(undef, Polyester.num_cores()) sdets = Vector{Float64}(undef, Polyester.num_cores()) d, r = divrem(n, Polyester.num_cores()) …

And with a little more work… using RecursiveFactorization function f5() n = 1000 m = 10 sms = Vector{Matrix{Float64}}(undef, Polyester.num_cores()) sdets = Vector{Float64}(undef, Polyester.num_cores()) d, r = divrem(n, Polyester.num_cores()) @batch for i = 1:min(Polyester.num_cores()…

Thank you very much! Using separate accumulators per thread instead of using a lock is a great idea. My current function is a little more complicated, and I save all matrices too in vector (there is no rand() it just for example), so I need linear indexes too (no problem to calculate them). One …

[image] Elrod: @batch I implemented this approach and get 9ms from 14 (1.5 times faster). Thanks a lot!

Questions about Polyester.jl

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John_Gibson September 18, 2021, 1:42pm 2

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