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

[anonymous]

Follow-up Comment #33, bug #58926 (project octave):

Building OpenBLAS from source is definitely recommended. It will use very good
CPU-probing during configuration to pick the most appropriate compiler flags
for your architecture. You can continue to use precompiled Octave with that
self-compiled OpenBLAS if you want, particularly if you will spend the
majority of the time executing linear algebra code and not interpreted code
like I/O or drawing graphs. You are of course welcome to build Octave from
source too but it's not essential based on what you've described.

OMP_NUM_THREADS controls the number of parallel threads used for large matrix
operations. It's a tuning parameter that you can experiment with after you
have built OpenBLAS. Common values are the number of physical cores or number
of threads. Your Intel i3 likely has 2 cores and 4 threads (might be called
"logical cores").

The objective of this experiment is not to tune one user's setup alone. It's
to quantifiably compare OpenBLAS (which is fully supported by Octave and is
cross-platform, cross-architecture) and MKL (which is not supported and is
heavily Intel-specific and nonfree in GNU classification) as a basis for
future recommendations. This thinking is also influencing HPC decisions in
academia, with Epyc Rome being seriously considered to replace older Xeons
with.

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