Building a Performance Model for Deep Learning Recommendation Model Training on GPUs-Reference-Cited by-同舟云学术

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Building a Performance Model for Deep Learning Recommendation Model Training on GPUs

Published:2022-12 Issue: Volume: Page:
ISSN:
Container-title:2022 IEEE 29th International Conference on High Performance Computing, Data, and Analytics (HiPC)
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Author:

Lin Zhongyi¹,Feng Louis²,Ardestani Ehsan K.²,Lee Jaewon²,Lundell John²,Kim Changkyu²,Kejariwal Arun²,Owens John D.¹

Affiliation:

1. University of California, Davis,Department of Elect. & Comp. Engr.,Davis,California

2. Meta Platforms, Inc.,Menlo Park,California

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10106277/10106278/10106317.pdf?arnumber=10106317

Reference36 articles.

1. A Comprehensive Survey of Neighborhood-Based Recommendation Methods

2. Explaining collaborative filtering recommendations

3. PyTorch: An imperative style, high-performance deep learning library;paszke;Advances in Neural IInformation Processing Systems,2019

4. Wide & Deep Learning for Recommender Systems

Cited by 1 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Proteus: Simulating the Performance of Distributed DNN Training;IEEE Transactions on Parallel and Distributed Systems;2024-10

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