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@ -12,11 +12,11 @@ Machine:
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System: CentOS release 6.3 (Final), Docker 1.12.1.
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PaddlePaddle: paddlepaddle/paddle:latest (TODO: will rerun after 0.11.0)
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- MKL-DNN tag v0.10
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- MKLML 2018.0.20170720
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PaddlePaddle: paddlepaddle/paddle:latest (for MKLML and MKL-DNN), paddlepaddle/paddle:latest-openblas (for OpenBLAS)
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- MKL-DNN tag v0.11
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- MKLML 2018.0.1.20171007
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- OpenBLAS v0.2.20
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(TODO: will rerun after 0.11.0)
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On each machine, we will test and compare the performance of training on single node using MKL-DNN / MKLML / OpenBLAS respectively.
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@ -31,15 +31,26 @@ Input image size - 3 * 224 * 224, Time: images/second
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| BatchSize | 64 | 128 | 256 |
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|--------------|-------| -----| --------|
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| OpenBLAS | 7.82 | 8.62 | 10.34 |
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| MKLML | 11.02 | 12.86 | 15.33 |
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| MKL-DNN | 27.69 | 28.8 | 29.27 |
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| OpenBLAS | 7.80 | 9.00 | 10.80 |
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| MKLML | 12.12 | 13.70 | 16.18 |
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| MKL-DNN | 28.46 | 29.83 | 30.44 |
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chart on batch size 128
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TBD
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- ResNet-50
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| BatchSize | 64 | 128 | 256 |
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|--------------|-------| ------| -------|
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| OpenBLAS | 25.22 | 25.68 | 27.12 |
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| MKLML | 32.52 | 31.89 | 33.12 |
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| MKL-DNN | 81.69 | 82.35 | 84.08 |
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chart on batch size 128
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TBD
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- ResNet
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- GoogLeNet
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### Laptop
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