EVStore: Storage and Caching Capabilities for Scaling Embedding Tables in Deep Recommendation Systems
Published in 28th ACM International Conference on Architectural Support for Programming Languages and Operating Systems, 2023
This paper is about designing caching systems for embedding tables in deep recommendation systems
Recommended citation: Daniar H. Kurniawan, Ruipu Wang, Kahfi S. Zulkifli, Fandi A. Wiranata, John Bent, Ymir Vigfusson, and Haryadi S. Gunawi. 2023. EVStore: Storage and Caching Capabilities for Scaling Embedding Tables in Deep Recommendation Systems. In Proceedings of the 28th ACM International Conference on Architectural Support for Programming Languages and Operating Systems, Volume 2 (ASPLOS 2023). Association for Computing Machinery, New York, NY, USA, 281–294. https://doi.org/10.1145/3575693.3575718