Physics Community Needs, Tools, and Resources for Machine Learning
Abstract
Machine learning (ML) is becoming an increasingly important component of cutting-edge physics research, but its computational requirements present significant challenges. In this white paper, we discuss the needs of the physics community regarding ML across latency and throughput regimes, the tools and resources that offer the possibility of addressing these needs, and how these can be best utilized and accessed in the coming years.
- Publication:
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arXiv e-prints
- Pub Date:
- March 2022
- DOI:
- 10.48550/arXiv.2203.16255
- arXiv:
- arXiv:2203.16255
- Bibcode:
- 2022arXiv220316255H
- Keywords:
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- Computer Science - Machine Learning;
- General Relativity and Quantum Cosmology;
- High Energy Physics - Experiment;
- Physics - Instrumentation and Detectors
- E-Print:
- Contribution to Snowmass 2021, 33 pages, 5 figures