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Paddle/benchmark/IntelOptimizedPaddle.md

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Benchmark

Machine:

  • Server
    • Intel(R) Xeon(R) Gold 6148 CPU @ 2.40GHz, 2 Sockets, 20 Cores per socket
  • Laptop
    • DELL XPS15-9560-R1745: i7-7700HQ 8G 256GSSD
    • i5 MacBook Pro (Retina, 13-inch, Early 2015)
  • Desktop
    • i7-6700k

System: CentOS release 6.3 (Final), Docker 1.12.1.

PaddlePaddle: paddlepaddle/paddle:latest (TODO: will rerun after 0.11.0)

  • MKL-DNN tag v0.10
  • MKLML 2018.0.20170720
  • OpenBLAS v0.2.20

On each machine, we will test and compare the performance of training on single node using MKL-DNN / MKLML / OpenBLAS respectively.

Benchmark Model

Server

Test on batch size 64, 128, 256 on Intel(R) Xeon(R) Gold 6148 CPU @ 2.40GHz

Input image size - 3 * 224 * 224, Time: images/second

  • VGG-19
BatchSize 64 128 256
OpenBLAS 7.82 8.62 10.34
MKLML 11.02 12.86 15.33
MKL-DNN 27.69 28.8 29.27

chart on batch size 128 TBD

  • ResNet
  • GoogLeNet

Laptop

TBD

Desktop

TBD