Understanding capacity-driven scale-out neural recommendation inference

M Lui, Y Yetim, Ö Özkan, Z Zhao… - … Analysis of Systems …, 2021 - ieeexplore.ieee.org
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 …
被引用次数：52 相关文章

Understanding Capacity-Driven Scale-Out Neural Recommendation Inference

M Lui, Y Yetim, O Ozkan, Z Zhao, SY Tsai… - … Analysis of Systems …, 2021 - computer.org
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 …

Understanding Capacity-Driven Scale-Out Neural Recommendation Inference

M Lui, Y Yetim, Ö Özkan, Z Zhao, SY Tsai… - arXiv e …, 2020 - ui.adsabs.harvard.edu
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 …

Understanding Capacity-Driven Scale-Out Neural Recommendation Inference

M Lui, Y Yetim, O Ozkan, Z Zhao… - … Analysis of Systems …, 2021 - asu.elsevierpure.com
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 …

Understanding Capacity-Driven Scale-Out Neural Recommendation Inference

M Lui, Y Yetim, Ö Özkan, Z Zhao, SY Tsai… - arXiv preprint arXiv …, 2020 - arxiv.org
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 …