UMA-MF: A Unified Multi-CPU/GPU Asynchronous Computing Framework for SGD-Based Matrix Factorization

Recent research has shown that collaborative computing of CPUs and GPUs in the same system can effectively accelerate large-scale SGD-based matrix factorization (MF), but it faces the problem of limited scalability due to parameter synchronization in the server. Theoretically, asynchronous methods c...

Ausführliche Beschreibung

Gespeichert in:

Bibliographische Detailangaben
Veröffentlicht in:	IEEE transactions on parallel and distributed systems Jg. 34; H. 11; S. 2978 - 2993
Hauptverfasser:	Huang, Yizhi, Liu, Yan, Bai, Yang, Chen, Si, Li, Renfa
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	New York IEEE 01.11.2023 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Schlagworte:	Algorithms Central processing units Communication Computation Computer architecture CPUs Datasets Factorization Graphics processing units Matrix factorization Microprocessors multi-CPU/GPU parallel systems Parameters Pipelining (computers) Rings (mathematics) Safety Scalability stochastic gradient descent Stochastic processes Synchronism System effectiveness Topology Training
ISSN:	1045-9219, 1558-2183
Online-Zugang:	Volltext
Tags:	Tag hinzufügen Keine Tags, Fügen Sie den ersten Tag hinzu!

Schreiben Sie den ersten Kommentar!