Download
By combining salient features from the TensorFlow deep learning framework with Apache Spark and Apache Hadoop, TensorFlowOnSpark enables distributed deep learning on a cluster of GPU and CPU servers. It enables both distributed TensorFlow training and inferencing on Spark clusters, with a goal to minimize the amount of code changes required to run existing TensorFlow programs on a shared grid.
Features
- Easily migrate existing TensorFlow programs with <10 lines of code change
- Support all TensorFlow functionalities: synchronous/asynchronous training, model/data parallelism, inferencing and TensorBoard
- Server-to-server direct communication achieves faster learning when available
- Allow datasets on HDFS and other sources pushed by Spark or pulled by TensorFlow
- Easily integrate with your existing Spark data processing pipelines
- Easily deployed on cloud or on-premise and on CPUs or GPUs
Project Samples
Categories
Machine LearningLicense
Apache License V2.0Follow TensorFlowOnSpark
Other Useful Business Software
Ship Agents Faster
Gemini Enterprise Agent Platform lets you rapidly build, scale, govern and optimize production-ready agents grounded in your organization's data. The platform enables developers to build custom or pre-built agents for virtually any use case. New customers get $300 in free credits.
Rate This Project
Login To Rate This Project
User Reviews
Be the first to post a review of TensorFlowOnSpark!