Search Results for author: Geet Sethi

Found 3 papers, 1 papers with code

FlexShard: Flexible Sharding for Industry-Scale Sequence Recommendation Models

no code implementations8 Jan 2023 Geet Sethi, Pallab Bhattacharya, Dhruv Choudhary, Carole-Jean Wu, Christos Kozyrakis

Sequence-based deep learning recommendation models (DLRMs) are an emerging class of DLRMs showing great improvements over their prior sum-pooling based counterparts at capturing users' long term interests.

RecShard: Statistical Feature-Based Memory Optimization for Industry-Scale Neural Recommendation

no code implementations25 Jan 2022 Geet Sethi, Bilge Acun, Niket Agarwal, Christos Kozyrakis, Caroline Trippel, Carole-Jean Wu

EMBs exhibit distinct memory characteristics, providing performance optimization opportunities for intelligent EMB partitioning and placement across a tiered memory hierarchy.

To Index or Not to Index: Optimizing Exact Maximum Inner Product Search

1 code implementation5 Jun 2017 Firas Abuzaid, Geet Sethi, Peter Bailis, Matei Zaharia

The brute-force approach to solving exact MIPS is computationally expensive, thus spurring recent development of novel indexes and pruning techniques for this task.

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