>mer. 21 juin 2023 at 16:36, Ludovic Courtès <[email protected]> wrote:
> Hey!
>
> The benchmark you posted, Cayetano, is:
>
> julia -e 'using Pkg; Pkg.add("BenchmarkTools"); using BenchmarkTools; N =
> 1000; A = rand(N, N); B = rand(N, N); @btime $A*$B'
>
> This is a matrix multiplication that gets delegated to the underlying
> BLAS right. Running it under ‘perf record’ confirms it:
>
> Samples: 139K of event 'cycles:u', Event count (approx.): 99624880590
> Overhead Command Shared Object Symbol
> 35.27% .julia-real libblas.so.3.9.0 [.] dgemm_
> 3.99% .julia-real libjulia-internal.so.1.8 [.] gc_mark_loop
> 2.60% .julia-real libjulia-internal.so.1.8 [.] apply_cl
> 1.06% .julia-real libjulia-internal.so.1.8 [.] jl_get_binding_
>
> We’re using libblas.so (presumably from the ‘lapack’ package) and not
> OpenBLAS, so no wonder it’s slow.
>
> Could it be that:
>
> "LIBBLAS=-lopenblas"
> "LIBBLASNAME=libopenblas"
>
> is ineffective? I think we have a lead!
Are we following all instructions here ?
https://docs.julialang.org/en/v1.8/devdocs/build/distributing/#Notes-on-BLAS-and-LAPACK
I’m thinking about the variables LIBLAPACK and LIBLAPACKNAME.
C.
