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Is there a way to disable this? In an HPC environment, I don't want routines going multi-core without my explicit permission, under any circumstances. I will al
by goerz 9y ago
Is there a way to disable this? In an HPC environment, I don't want routines going multi-core without my explicit permission, under any circumstances. I will already have manually set up the parallelization to be at the highest logical level. If using Python, that usually means I have planned out the number of processes to be equal to the number of cores. If each process then starts doing its own multicore calculation (badly load-balanced!) it overtaxes the node and slows everything down.
I really wish numpy/pandas/scipy wouldn't do this kind of uncontrollable parallelization.
- yaroslavvb 9y agoUnderlying implementations often have a way to disable parallelism, ie, OMP_NUM_THREADS=1 or MKL_NUM_THREADS=1