_______ ______ _
| ____\ \ / / ___|| |_ ___ _ __ ___
| _| \ \ / /\___ \| __/ _ \| '__/ _ \
| |___ \ V / ___) | || (_) | | | __/
|_____| \_/ |____/ \__\___/|_| \___| -- Groupability-aware caching systems for DRS
This repository contains the implementation code for paper:
EVSTORE: Storage and Caching Capabilities for Scaling
Embedding Tables in Deep Recommendation Systems
Maintainer: Daniar H. Kurniawan, Email: daniar@uchicago.edu
Feel free to contact Daniar for any suggestions/feedback, bug reports, or general discussions.
Please consider citing our EVStore paper at ASPLOS 2023 if you use EVStore. The bib entry is
@InProceedings{Daniar-EVStore,
Author = {Daniar H. Kurniawan and Ruipu Wang and Kahfi S. Zulkifli and Fandi A. Wiranata and John Bent and Ymir Vigfusson and Haryadi S. Gunawi},
Title = "EVSTORE: Storage and Caching Capabilities for Scaling
Embedding Tables in Deep Recommendation Systems",
Booktitle = {Proceedings of the 28th International Conference on Architectural Support for Programming Languages and Operating Systems (ASPLOS)},
Address = {Vancouver, Canada},
Month = {MARCH},
Year = {2023}
}
Please follow the experiments detailed in Experiments.md.
The DLRM code in this repository is based on Facebook DLRM. The cache benchmark repository is based on Cache2k and Cacheus.