This document discusses optimizations for running TensorFlow on Intel CPUs for deep learning. It outlines techniques for compiling TensorFlow from source with CPU optimizations, using proper data formats and batch sizes, and reading data with queues to leverage multi-core CPUs. It also covers distributed deep learning using TensorFlow Estimators, parameter servers, and model parallelism to distribute graphs across multiple machines. Resources for further information on Intel optimizations, installing libraries, and distributed TensorFlow are provided.

1. Intel Optimized
Tensorflow
Distributed Deep
Learning
GEETA CHAUHAN JUNE, 2017

2. Agenda
Tensorflow
Optimizations
for Intel CPUs
Distributed
Deep
Learning

3. Myth: GPUs are must for DL
 Leverage High Performance compute
tools
 Intel Python, Intel Math Kernel Library
(MKL), MKL-DNN
 Compile Tensorflow from Source for
CPU Optimizations
 Proper Data Format
 NCHW for CPUs vs Tensorflow default
NHWC
 Proper Batch size, using all cores &
memory
 Use Queues for Reading Data

4. Tensorflow CPU Optimizations
 Compile from source
 git clone https://github.com/tensorflow/tensorflow.git
 Run ./configure from Tensorflow source directory
 Select option MKL (CPU) Optimization
 Build pip package for install
 bazel build --config=mkl --copt=-DEIGEN_USE_VML -c opt
//tensorflow/tools/pip_package:build_pip_package
 Install the optimized TensorFlow wheel
 bazel-bin/tensorflow/tools/pip_package/build_pip_package
~/path_to_save_wheel
pip install --upgrade --user ~/path_to_save_wheel /wheel_name.whl

5. Distributed
Deep Learning
 Data Parallelism
 Tensorflow Estimator +
Experiments
 Parameter Server, Worker
cluster
 Intel BigDL Spark Cluster
 HyperTune Google Cloud ML
 Model Parallelism
 Tensorflow Model Towers
 Graph too large to fit on one
machine

6. Resources
 https://software.intel.com/en-us/articles/tensorflow-optimizations-on-
modern-intel-architecture
 https://software.intel.com/en-us/articles/how-to-install-the-python-
version-of-intel-daal-in-linux
 https://software.intel.com/en-us/articles/installing-intel-free-libs-and-
python-apt-repo
 https://www.tensorflow.org/deploy/distributed
 https://www.tensorflow.org/extend/estimators
 https://www.tensorflow.org/programmers_guide/reading_data#readin
g_from_files
 https://software.intel.com/en-us/articles/bigdl-distributed-deep-
learning-on-apache-spark

7. Questions?
Contact
https://www.linkedin.com/
in/geetachauhan/
geeta@svsg.co