It has caused a lot of frustration. See #9118. I think the easiest right
now is
for p in procs()
@spawnat p blas_set_num_threads(k)
end
2015-03-17 23:19 GMT-04:00 Sheehan Olver <dlfivefi...@gmail.com>:
> Hi,
>
> I've created the following to test the performance of parallel processing
> on our departments server. But the @everywhere isn't working because
> "ERROR: k not defined". What's wrong? And any advice on improving the
> test? (Right now for small n there is little benefit for > 12 processes,
> but this seems expected behaviour to me. There are many other processes
> maxing out CPU simultaneous with the test.)
>
> Sheehan
>
>
>
> function timemat(n,m,b,p)
> rmprocs(procs()[2:end])
> tms=Array(Float64,p,b)
> for j=1:p
> for k=1:b
> @everywhere blas_set_num_threads(k)
>
> # following line is just to make sure everything is precompiled
> @parallel (+) for k=1:2p
> last(randn(n,n)\[1;zeros(n-1)])
> end;
>
> tms[j,k]=@elapsed(@parallel (+) for k=1:m
> last(randn(n,n)\[1;zeros(n-1)])
> end)
>
> println("procs=$j blas=$k $(tms[j,k])")
> end
> addprocs(1)
> end
> tms
> end
>
>
