Nov 24, 2020 · We study how to schedule dependent coflows of multiple DML jobs to minimize the total JCT in a shared cluster.
Dec 6, 2022 · We study the problem of scheduling the dependent coflows of multiple DML jobs to minimize the total. JCT in machine learning clusters. We ...
Dec 9, 2024 · In this paper, we study how to schedule dependent coflows of multiple DML jobs to minimize the total job completion time (JCT) in a shared ...
Efficient Online Scheduling for Coflow-aware Machine Learning Clusters. Author, Li, Wenxin · Chen, Sheng · Li, Keqiu · Qi, Heng · Xu, Renhai · Zhang, Song.
ABSTRACT. A coflow is a collection of related parallel flows that occur typically between two stages of a multi-stage compute task.
In this paper, we present Aalo that strikes a balance and efficiently schedules coflows without prior knowledge.
Missing: Machine | Show results with:Machine
A coflow is a collection of related parallel flows that occur typically between two stages of a multi-stage compute task in a network, such as shuffle flows ...
In this paper, we propose an Attention-Empowered Scalable Deep Reinforcement Learning Model to automatically generate coflow scheduling policies for online ...
In this paper, we address inter-coflow scheduling for two different objectives: decreasing communication time of data-intensive jobs and guaranteeing ...
Missing: Machine | Show results with:Machine
Coflow scheduling improves the networking performance at the application level in datacenters. Ideally, a coflow scheduler should provide tenants with ...