EURASIP journal on advances in signal processing | |
Performance evaluation and analysis of distributed multi-agent optimization algorithms with sparsified directed communication | |
article | |
Fodor, Lidija1  Jakovetić, Dušan1  Krejić, Nataša1  Jerinkić, Nataša Krklec1  Škrbić, Srđan1  | |
[1] Department of Mathematics and Informatics, Faculty of Sciences, University of Novi Sad | |
关键词: Distributed optimization; High performance computing; Performance evaluation; | |
DOI : 10.1186/s13634-021-00736-4 | |
来源: SpringerOpen | |
【 摘 要 】
There has been significant interest in distributed optimization algorithms, motivated by applications in Big Data analytics, smart grid, vehicle networks, etc. While there have been extensive theory and theoretical advances, a proportionally small body of scientific literature focuses on numerical evaluation of the proposed methods in actual practical, parallel programming environments. This paper considers a general algorithmic framework of first and second order methods with sparsified communications and computations across worker nodes. The considered framework subsumes several existing methods. In addition, a novel method that utilizes unidirectional sparsified communications is introduced and theoretical convergence analysis is also provided. Namely, we prove R-linear convergence in the expected norm. A thorough empirical evaluation of the methods using Message Passing Interface (MPI) on a High Performance Computing (HPC) cluster is carried out and several useful insights and guidelines on the performance of algorithms and inherent communication-computational trade-offs in a realistic setting are derived.
【 授权许可】
CC BY
【 预 览 】
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