dmlc--dgl
mszarma
52 行
2.1 KiB
Python
52 行
2.1 KiB
Python
"""
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CPU Best Practices
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=====================================================
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This chapter focus on providing best practises for environment setup
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to get the best performance during training and inference on the CPU.
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Intel
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`````````````````````````````
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Hyper-treading
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---------------------------
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For specific workloads as GNN’s domain, suggested default setting for having best performance
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is to turn off hyperthreading.
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Turning off the hyper threading feature can be done at BIOS [#f1]_ or operating system level [#f2]_ [#f3]_ .
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OpenMP settings
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---------------------------
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During training on CPU, the training and dataloading part need to be maintained simultaneously.
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Best performance of parallelization in OpenMP
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can be achieved by setting up the optimal number of working threads and dataloading workers.
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**GNU OpenMP**
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Default BKM for setting the number of OMP threads with Pytorch backend:
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``OMP_NUM_THREADS`` = number of physical cores – ``num_workers``
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Number of physical cores can be checked by using ``lscpu`` ("Core(s) per socket")
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or ``nproc`` command in Linux command line.
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Below simple bash script example for setting the OMP threads and ``pytorch`` backend dataloader workers:
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.. code:: bash
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cores=`nproc`
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num_workers=4
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export OMP_NUM_THREADS=$(($cores-$num_workers))
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python script.py --gpu -1 --num_workers=$num_workers
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Depending on the dataset, model and CPU optimal number of dataloader workers and OpemMP threads may vary
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but close to the general default advise presented above [#f4]_ .
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.. rubric:: Footnotes
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.. [#f1] https://www.intel.com/content/www/us/en/support/articles/000007645/boards-and-kits/desktop-boards.html
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.. [#f2] https://aws.amazon.com/blogs/compute/disabling-intel-hyper-threading-technology-on-amazon-linux/
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.. [#f3] https://aws.amazon.com/blogs/compute/disabling-intel-hyper-threading-technology-on-amazon-ec2-windows-instances/
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.. [#f4] https://software.intel.com/content/www/us/en/develop/articles/how-to-get-better-performance-on-pytorchcaffe2-with-intel-acceleration.html
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"""
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