Insight Gained from Migrating a Machine Learning Model to Intelligence Processing Units-Reference-Cited by-同舟云学术

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Insight Gained from Migrating a Machine Learning Model to Intelligence Processing Units

Published:2024-07-17 Issue: Volume: Page:1-9
ISSN:
Container-title:Practice and Experience in Advanced Research Computing 2024: Human Powered Computing
language:
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Author:

Le Hieu¹^ORCID,He Zhenhua²^ORCID,Le Mai³^ORCID,Chakravorty Dhruva⁴^ORCID,Perez Lisa M.²^ORCID,Chilumuru Akhil⁴^ORCID,Yao Yan³^ORCID,Chen Jiefu³^ORCID

Affiliation:

1. Electrical and Computer Engineering, Texas A&M University, USA

2. High Performance Research Computing, High Performance Research Computing (HPRC), Texas A&M University, USA

3. University of Houston, USA

4. High Performance Research Computing (HPRC), Texas A&M University, USA

Funder

National Science Foundation

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3626203.3670527

Reference15 articles.

1. Nathan Baker. 2024. Unlocking a new era for scientific discovery with AI: How Microsoft’s AI screened over 32 million candidates to find a better battery. Retrieved March, 2024 from https://cloudblogs.microsoft.com/quantum/2024/01/09/unlocking-a-new-era-for-scientific-discovery-with-ai-how-microsofts-ai-screened-over-32-million-candidates-to-find-a-better-battery/

2. A quantitative study of irregular programs on GPUs

3. Graphcore documents. 2024. Graphcore documents. Retrieved March, 2024 from https://docs.graphcore.ai/en/latest/

4. Accelerated Materials Design of Lithium Superionic Conductors Based on First-Principles Calculations and Machine Learning Algorithms

5. Deep Residual Learning for Image Recognition

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