sabath

SABATH provides benchmarking infrastructure for evaluating scientific ML/AI models. It contains support for scientific machine learning surrogates from external repositories such as SciML-Bench.

Introduction

SABATH provides benchmarking infrastructure for evaluating scientific ML/AI models. It contains support for scientific machine learning surrogates from external repositories such as SciML-Bench.

The software dependences are explicitly exposed in the surrogate model definition, which allows the use of advanced optimization, communication, and hardware features. For example, distributed, multi-GPU training may be enabled with Horovod. Surrogate models may be implemented using TensorFlow, PyTorch, or MXNET frameworks.

Models

Models are collected so far at

1

References

  1. https://github.com/icl-utk-edu/sabath ↩︎

Last modified January 26, 2024: add software (2efdeb9)