Summary of Mess: Modern Electronic Structure Simulations, by Hatem Helal and Andrew Fitzgibbon
MESS: Modern Electronic Structure Simulations
by Hatem Helal, Andrew Fitzgibbon
First submitted to arxiv on: 5 Jun 2024
Categories
- Main: Machine Learning (cs.LG)
- Secondary: Materials Science (cond-mat.mtrl-sci); Computational Physics (physics.comp-ph)
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| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary This paper introduces MESS, a modern electronic structure simulation package implemented in JAX, which porting the ESS code to the ML world. MESS is designed to optimize both ease of use and high performance by harnessing hardware acceleration of tensor programs defined in Python. The authors outline the costs and benefits of following software development practices used in ML for this important scientific workload. MESS shows significant speedups on widely available hardware accelerators and opens a clear pathway towards combining ESS with ML. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary MESS is a new electronic structure simulation package that makes it easier to use and faster than previous versions. It’s designed to work well with machine learning (ML) models, which are becoming more important in chemistry, biology, and materials science. The authors compared MESS to other software packages and found that it’s faster and can be used more easily. |
Keywords
» Artificial intelligence » Machine learning
