DISCONTINUATION OF PROJECT.

This project will no longer be maintained by Intel.

Intel has ceased development and contributions including, but not limited to, maintenance, bug fixes, new releases, or updates, to this project.

Intel no longer accepts patches to this project.

If you have an ongoing need to use this project, are interested in independently developing it, or would like to maintain patches for the open source software community, please create your own fork of this project.

This repo is dedicated to improving Theano performance on CPU, especially in Intel® Xeon® and Intel® Xeon Phi™ processors.

Key Features

• New backend of Intel® MKL (version >= 2017.0 which includes neural network primitives)
• Advanced graph optimizations
• CPU friendly OPs
• Switch to Intel® MKL backend automatically in Intel® Architecture
• Out-of-box performance improvements for legacy models
• Transparently supports for Keras (Lasagne, etc.) workloads

Benchmark

• Hardwares
  • Intel® Xeon® CPU E5-2699 v4 @ 2.20GHz, 128GB RAM
  • Intel® Xeon Phi™ CPU 7250F @ 1.40GHz, 98G RAM
• Softwares
  • Script: convnet-benchmarks
  • Stock Theano, commit ID: 2fa3ce
  • Intel Theano, commit ID: e3f7b4, ver-1.1
• Terminologies
  • FWD, forward for inference
  • FWD+BWD, forward and backward for training
• Results

--

Performance Tips

• Add bias after convolution to archieve high performance since this sub-graph can be replaced with MKL Op
• Use group convolution OP, AbstractConvGroup
• Use New MKL OP: LRN

Branch Information

• master, stable and fully tested version based on 0.9dev2 with Intel® MKL backend
• nomkl-optimized, based on 0.9.0dev1 with generic optimizations
• others, experimental codes for different applications which may be merged into master and/or deleted soon

Installation

• Environment Setting

  Set Intel MKL library path into both LD_LIBRARY_PATH and LIBRARY_PATH

• Quick Commands

  git clone https://github.com/intel/theano.git intel-theano
  cd intel-theano
  python setup.py build
  python setup.py install --user [--mkl]   # Note: using 'mkl' option will check and download MKL if it is not available
  cp intel-theano/theanorc_icc_mkl ~/.theanorc
  

• Check Intel MKL

```
python theano/theano/sandbox/mkl/tests/test_mkl.py
     WARNING (theano.gof.cmodule): WARNING: your Theano flags `gcc.cxxflags` specify an `-march=X` flags.
     It is better to let Theano/g++ find it automatically, but we don't do it now
     mkl_available: True
     mkl_version: 20170209
     .
     ----------------------------------------------------------------------
     Ran 1 test in 2.213s

     OK
```

• Run Benchmark

```
python democase/alexnet/benchmark.py
```

• Install Guide (recommend to go througth this document and set up optimized softwares) https://github.com/intel/theano/blob/master/Install_Guide.pdf

Other Optimized Software

• Self-contained MKL in here
• Optimized Numpy in here

* Other names and trademarks may be claimed as the property of others.