Welcome to Poseidon

Poseidon is an easy-to-use and efficient system architecture for large-scale deep learning.

This distribution of Poseidon uses the Tensorflow 1.0.1 client API. Poseidon can distribute python model scripts designed to run on a single node into a cluster with no changes to the scripts themselves. This allows for rapid prototyping of model scripts. Developers can focus on perfecting their models running on a single node and be reasonably confident that the model will run efficiently scaled to 32 nodes or more.


Poseidon allows deep learning applications written in popular languages and tested on single GPU nodes to easily scale onto a cluster environment with high performance, correctness, and low resource usage. This release has two packages, one for cpu-only machines and the other for machines with gpus.

Traditionally, distributing deep learning jobs has been difficult for two reasons. First of all, taking a model and parallelizing it has been a manual process that had to be done uniquely for every new deep learning model. Secondly, even if the technical challenge of parallelization can be achieved, speed-ups are not guaranteed because dataflow can bottleneck in many ways. Poseidon is built on top of state of the art research aimed at effectively distributing deep learning and it can automatically distribute most deep learning tasks to provide faster total throughput with no manual intervention.

Performance at a Glance

Poseidon can scale almost linearly in total throughput with additional machines while simultaneously incurring little additional overhead.