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Louis Feng
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Chakra: Advancing Performance Benchmarking and Co-design using Standardized Execution Traces


May 26, 2023
Srinivas Sridharan, Taekyung Heo, Louis Feng, Zhaodong Wang, Matt Bergeron, Wenyin Fu, Shengbao Zheng, Brian Coutinho, Saeed Rashidi, Changhai Man, Tushar Krishna

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Pre-train and Search: Efficient Embedding Table Sharding with Pre-trained Neural Cost Models


May 03, 2023
Daochen Zha, Louis Feng, Liang Luo, Bhargav Bhushanam, Zirui Liu, Yusuo Hu, Jade Nie, Yuzhen Huang, Yuandong Tian, Arun Kejariwal, Xia Hu

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* Accepted by MLSys 2023. Code available at https://github.com/daochenzha/neuroshard 
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Mystique: Accurate and Scalable Production AI Benchmarks Generation


Dec 16, 2022
Mingyu Liang, Wenyin Fu, Louis Feng, Zhongyi Lin, Pavani Panakanti, Srinivas Sridharan, Christina Delimitrou

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DreamShard: Generalizable Embedding Table Placement for Recommender Systems


Oct 05, 2022
Daochen Zha, Louis Feng, Qiaoyu Tan, Zirui Liu, Kwei-Herng Lai, Bhargav Bhushanam, Yuandong Tian, Arun Kejariwal, Xia Hu

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* Accepted by NeurIPS 2022 
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AutoShard: Automated Embedding Table Sharding for Recommender Systems


Aug 12, 2022
Daochen Zha, Louis Feng, Bhargav Bhushanam, Dhruv Choudhary, Jade Nie, Yuandong Tian, Jay Chae, Yinbin Ma, Arun Kejariwal, Xia Hu

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* Accepted by KDD 2022. Code available at https://github.com/daochenzha/autoshard 
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Building a Performance Model for Deep Learning Recommendation Model Training on GPUs


Jan 19, 2022
Zhongyi Lin, Louis Feng, Ehsan K. Ardestani, Jaewon Lee, John Lundell, Changkyu Kim, Arun Kejariwal, John D. Owens

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* 11 pages, 10 figures 
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Alternate Model Growth and Pruning for Efficient Training of Recommendation Systems


May 04, 2021
Xiaocong Du, Bhargav Bhushanam, Jiecao Yu, Dhruv Choudhary, Tianxiang Gao, Sherman Wong, Louis Feng, Jongsoo Park, Yu Cao, Arun Kejariwal

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