Reliable and efficient RAR-based distributed model training in computing power network
Artikel i vetenskaplig tidskrift, 2024

The computing power network (CPN) is a novel network technology that integrates computing power from the cloud, edge, and terminals using IP/optical cross-layer networks for distributed computing. CPNs can provide an effective solution for distributed model training (DMT). As a bandwidth optimization architecture based on data parallelism, ring all-reduce (RAR) is widely used in DMT. However, any node or link failure on the ring can interrupt or block the requests deployed on the ring. Meanwhile, due to the resource competition of batch RAR-based DMT requests, inappropriate scheduling strategies will also lead to low training efficiency or congestion. As far as we know, there is currently no research that considers the survivability of rings in scheduling strategies for RAR-based DMT. To fill this gap, we propose a scheduling scheme for RAR-based DMT requests in CPNs to optimize the allocation of computing and wavelength resources considering the time dimension while ensuring reliability. In practical scenarios, service providers may focus on different performance metrics. We formulate an integer linear programming (ILP) model and a RAR-based DMT deployment algorithm (RDDA) to solve this problem considering four optimization objectives under the premise of the minimum blocking rate: minimum computing resource consumption, minimum wavelength resource consumption, minimum training time, and maximum reliability. Simulation results demonstrate that our model satisfies the reliability requirements while achieving corresponding optimal performance for DMT requests under four optimization objectives.

Författare

Ling Chen

Beijing University of Posts and Telecommunications (BUPT)

Yajie Li

Beijing University of Posts and Telecommunications (BUPT)

Tibet University

Carlos Natalino Da Silva

Chalmers, Elektroteknik, Kommunikation, Antenner och Optiska Nätverk

Yongcheng Li

Soochow University

Boxin Zhang

Beijing University of Posts and Telecommunications (BUPT)

Yingbo Fan

Beijing University of Posts and Telecommunications (BUPT)

Wei Wang

Beijing University of Posts and Telecommunications (BUPT)

Yongli Zhao

Beijing University of Posts and Telecommunications (BUPT)

Jie Zhang

Beijing University of Posts and Telecommunications (BUPT)

Journal of Optical Communications and Networking

1943-0620 (ISSN) 19430639 (eISSN)

Vol. 16 5 527-540

Ämneskategorier

Kommunikationssystem

Datavetenskap (datalogi)

DOI

10.1364/JOCN.511165

Mer information

Senast uppdaterat

2024-07-15