Lune

EuroSys2020顶会

Balancing efficiency and fairness in heterogeneous GPU clusters for deep learning

Shubham Chaudhary, Ramachandran Ramjee, Muthian Sivathanu, Nipun Kwatra, Srinidhi Viswanatha

2020年份
135被引次数
35顶会引用

摘要

We present Gandivafair, a distributed, fair share scheduler that balances conflicting goals of efficiency and fairness in GPU clusters for deep learning training (DLT). Gandivafair provides performance isolation between users, enabling multiple users to share a single cluster, thus, maximizing cluster efficiency. Gandivafair is the first scheduler that allocates cluster-wide GPU time fairly among active users.

问问这篇 Paper

问问你的智能体。

Lune 读过与它相关的顶会 Paper,每个回答都会注明依据哪几篇。

可以从这些问题问起

智能体调用

Lunesearch_papers

在 Lune 里问

免费开始,无需绑卡

lune papers get b90c974b-e69f-462a-bbc1-7d6be0416fc9

引用它的顶会 Paper35

问问它们各自怎么用它

相关 Paper

黄昏的海面,两侧是细线勾勒的悬崖