JointPS: Joint Parameter Server Placement and Flow Scheduling for Machine Learning Clusters-Reference-Cited by-同舟云学术

JointPS: Joint Parameter Server Placement and Flow Scheduling for Machine Learning Clusters

Author:

Zhao Yangming¹^ORCID,Yang Cheng¹^ORCID,Zhao Gongming¹^ORCID,Hou Yunfei²^ORCID,Wang Ting³^ORCID,Qiao Chunming⁴^ORCID

Affiliation:

1. School of Computer Science and Technology, University of Science and Technology of China, Hefei, China

2. California State University San Bernardino, San Bernardino, CA, USA

3. Software Engineering Institute, East China Normal University, Shanghai, China

4. University at Buffalo, The State University of New York, Buffalo, NY, USA

Funder

National Natural Science Foundation of China

Natural Science Foundation of Anhui Province

Natural Science Foundation of Jiangsu Province

Hefei Municipal Natural Science Foundation

State Key Laboratory of Advanced Optical Communication Systems and Networks, China

Anhui Initiative in Quantum Information Technologies

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Computational Theory and Mathematics,Hardware and Architecture,Theoretical Computer Science,Software

Link

Reference44 articles.

1. TicTac: Accelerating distributed deep learning with communication scheduling;hashemi;Proc SysML,0

4. Learning multiple layers of features from tiny images;krizhevsky,0