Explore projects

distributed deep learning examples on Summit for Keras, PyTorch, and TensorFlow.

python and workflow tools surrounding the cnms NUFEB water treatment analytics project.

An exascale scientific deep learning benchmark

The project aims to develop deterministic and stochastic accelerations to speed-up and better scale the training of deep learning models on large-scale computational environments.

The project aims to develop deterministic and stochastic accelerations to speed-up and better scale the training of deep learning models on large-scale computational environments.

Tutorials and scripts to use Summit in order to scale up your Python deep learning projects. It covers basics of data parallelism and goes over what to add in your code to parallelize your training process.

Intercept Library for IBM/Summit Burst Buffer.

Mirror of https://github.com/celeritas-project/celeritas

MCNP input/output utilities (deprecated)

Datasets from docking to various proteins in the SARS-CoV-2 genome.

Latin for "a root" (of a plant). Contains core routines for every day development.

Cross-platform Big-data Operational Workflow (crossBOW) aims to develop a data portal