ethanluoyc/lxm3

LXM3: XManager launch backend for HPC clusters

29
/ 100
Experimental

This tool helps machine learning researchers and data scientists efficiently run their computational experiments on high-performance computing (HPC) clusters. You define your Python-based experiment and specify the cluster environment, and it packages your code into a Singularity container, deploying and executing it on SGE or Slurm-managed clusters. This is for researchers who need to run many large-scale experiments and want a streamlined way to manage dependencies and execution across different HPC systems.

No commits in the last 6 months. Available on PyPI.

Use this if you are a machine learning researcher or data scientist who regularly runs complex Python experiments on HPC clusters and wants to simplify experiment deployment and dependency management.

Not ideal if you primarily run small-scale computations locally or on cloud platforms, or if your projects don't require containerized environments on traditional HPC systems.

machine-learning-research hpc-workflow experiment-management computational-science data-science-operations
No License Stale 6m
Maintenance 0 / 25
Adoption 5 / 25
Maturity 17 / 25
Community 7 / 25

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1

Language

Python

License

Last pushed

May 11, 2024

Commits (30d)

0

Dependencies

14

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