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49 lines
1004 B
49 lines
1004 B
7 years ago
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# Benchmark
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Machine:
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- Server
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- Intel(R) Xeon(R) Gold 6148M CPU @ 2.40GHz, 2 Sockets, 20 Cores per socket
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- Laptop
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- DELL XPS15-9560-R1745: i7-7700HQ 8G 256GSSD
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- i5 MacBook Pro (Retina, 13-inch, Early 2015)
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- Desktop
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- i7-6700k
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System: CentOS 7.3.1611
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PaddlePaddle: commit cfa86a3f70cb5f2517a802f32f2c88d48ab4e0e0
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- MKL-DNN tag v0.10
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- MKLML 2018.0.20170720
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- OpenBLAS v0.2.20
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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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## Benchmark Model
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### Server
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Test on batch size 64, 128, 256 on Intel(R) Xeon(R) Gold 6148M CPU @ 2.40GHz
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Input image size - 3 * 224 * 224, Time: images/second
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- VGG-19
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| BatchSize | 64 | 128 | 256 |
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|--------------|-------| -----| --------|
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| OpenBLAS | 7.86 | 9.02 | 10.62 |
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| MKLML | 11.80 | 13.43 | 16.21 |
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| MKL-DNN | 29.07 | 30.40 | 31.06 |
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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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TBD
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### Desktop
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TBD
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