[Octave-bug-tracker] [bug #58926] Octave gives wrong results with intel-mkl when diagonalizing large matrices

[anonymous]

Follow-up Comment #31, bug #58926 (project octave):

@Dmitri: Completely agree. I'm on Ryzen too and my OpenBLAS results were much
faster than OP's posted benchmarks. (Yours are slightly faster being 16
threads unlike my 12). That's what prompted my question to OP on whether he
was using precompiled OpenBLAS with untuned flags. If so, using a properly
built OpenBLAS would be very competitive with MKL, as far as Octave goes
anyway.


octave:7> format long g
octave:8> format compact
octave:9> clear all; n = 500; C = sin((1:n)' + (1:n).^2); for i = 100:-1:1,
tic; val(i) = max(eig(C)); t(i) = toc; end; clear i; assert(range(val)==0);
assert(all(abs(val - 16.914886497930) <= 1e-12)); [min(t), mean(t), median(t),
max(t), range(t), std(t)]
ans =
 Columns 1 through 4:
      0.1320030689239502       0.133814971446991       0.133613109588623     
0.1365499496459961
 Columns 5 and 6:
    0.004546880722045898   0.0008096358540892868



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