When using SOL on X86 CPUs we strongly recommend to set the following OMP env vars.
export OMP_PROC_BIND=TRUE
export OMP_NUM_THREADS=$(lscpu -b -p=Core,Socket | grep -v '^#' | sort -u | wc -l)
| SOL performance using X86 is really really bad, what can I do? | |
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tl;dr; run once: python3 -m sol fix-omp --yesUnfortunately some python packages (e.g., torch or sklearn) ship their own version of libgomp.so. This causes that the application uses
multiple OpenMP runtimes, which can cause a series of problems. If you don't
define OMP_NUM_THREADS, then only the very first loaded OpenMP
runtime runs multi-threaded. Even worse, if you define
OMP_NUM_THREADS, all runtimes run in parallel, but use different
threadpools, so whenever you switch from one to the other, you will have
significant overhead due to swapping the threads. The python3 -m sol
fix-omp --yes command detects conflicting versions of
libgomp.so and replaces them with a symlink to the system's own
version of libgomp.so, so that all libraries use the same
threadpool.
If you need to run this fixing within your script, because you are using a fully
automated process, then you can use:
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