Rakesh Komuravelli

Learning to Collide: Recommendation System Model Compression with Learned Hash Functions

2022 · arXiv (Cornell University)

A key characteristic of deep recommendation models is the immense memory requirements of their embedding tables. These embedding tables can often reach hundreds of gigabytes which increases hardware requirements and training cost. A common technique …