7 citations · 8 across the 2 of their papers we have counts for
3 papers
cs.DC2022★ 1 cited
Hercules: Heterogeneity-Aware Inference Serving for At-Scale Personalized Recommendation
Liu Ke, Udit Gupta, Mark Hempstead +3
Personalized recommendation is an important class of deep-learning applications that powers a large collection of internet services and consumes a considerable amount of datacenter…
cs.DC2020
Understanding Capacity-Driven Scale-Out Neural Recommendation Inference
Michael Lui, Yavuz Yetim, Özgür Özkan +4
Deep learning recommendation models have grown to the terabyte scale. Traditional serving schemes--that load entire models to a single server--are unable to support this scale. One…
cs.DC2019★ 7 cited
RecNMP: Accelerating Personalized Recommendation with Near-Memory Processing
Liu Ke, Udit Gupta, Carole-Jean Wu +18
Personalized recommendation systems leverage deep learning models and account for the majority of data center AI cycles. Their performance is dominated by memory-bound sparse embed…