Getting started with TensorFlow
Find information for getting started with TensorFlow.
The TensorFlow home page has various information, including Tutorials, How to documents, and a Getting Started guide.
Additional tutorials and examples are available from the community, for example:
Large Model Support (LMS)
This release of PowerAI includes a technology preview of large model support for TensorFlow. Large Model Support provides an approach to training large models and batch sizes that cannot fit in GPU memory. It does this by use of a graph editing library that takes the user model's computational graph and automatically adds swap-in and swap-out nodes for transferring tensors from GPU memory to system memory and vice versa during training.
For more information about TensorFlow LMS, see
/opt/DL/tensorflow/doc/README-LMS.md.
Distributed Deep Learning (DDL) custom operator for TensorFlow
The DDL custom operator uses IBM Spectrum™ MPI and NCCL to provide high-speed communications for distributed TensorFlow.
The DDL custom operator can be found in the ddl-tensorflow package. For more
information about DDL and about the TensorFlow operator, see:
/opt/DL/ddl/doc/README.md/opt/DL/ddl-tensorflow/doc/README.md/opt/DL/ddl-tensorflow/doc/README-API.md
Additional TensorFlow features
The PowerAI TensorFlow packages include TensorBoard.
The TensorFlow 1.12.0 package includes support for additional features:
- Hadoop Distributed File System (HDFS) support
- Amazon Web Services (AWS) S3 support
- Kafka support
- Google Compute Platform (GCP) support
- IGNITE dataset support
- NVIDIA Collective Communications Library (NCCL) 2
- CUDA compute capabilities: 3.7, 6.0, 7.0 for NVIDIA Tesla K80, P100, and V100 GPUs
- CUDA 10.0 support
High-Performance Models
PowerAI includes the tensorflow-performance-models package that contains a version of the TensorFlow CNN benchmark. This package contains implementations of several popular convolutional models, and is designed to be as fast as possible. The code supports both running on a single machine or running in distributed mode across multiple hosts. This version of tensorflow-performance-models is matched to the version of TensorFlow that is included in this release and has additional options to enable DDL and TensorFlow Large Model Support.