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ares89 avatar ares89 commented on August 18, 2024 2

solution is add environment variables. set OMP_NUM_THREADS=2 or some value else will work better.
reference:
1.https://software.intel.com/content/www/us/en/develop/articles/maximize-tensorflow-performance-on-cpu-considerations-and-recommendations-for-inference.html
2.https://github.com/mingfeima/convnet-benchmarks/blob/master/pytorch/run.sh#L16-L25
3.pytorch/pytorch#20156

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ares89 avatar ares89 commented on August 18, 2024

And also,Java+libtorch has 90% cpu load and pytorch+torchscript use only 50% cpu load . CPU is Intel Xeon E5-2680v4 , 56 cores

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ares89 avatar ares89 commented on August 18, 2024

https://github.com/NervanaSystems/nlp-architect/blob/7f71a16965355d2508e86d0e1d6726842bccb58e/nlp_architect/nn/torch/modules/embedders.py#L157
this is the IDCNN i use

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ares89 avatar ares89 commented on August 18, 2024

And also, same mechine,

  1. both Java+libtorch, IDCNN+CRF run slower than Bilstm+CRF.
  2. both pytorch+torchscript, IDCNN+CRF run faster than Bilstm+CRF.

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