Research Progress on Computing Resource Scheduling in Computing Power Network

In the evolution of computing power networks, the effective scheduling of computing resources has become a critical concern, driven by the diversification of computing demands and the increasing heterogeneity of resources. This paper provides a review of scheduling strategies for computing resources within these networks, analyzing methods that are relevant for the current landscape, including CPUs and GPUs. It emphasizes application scenarios and benefits across three key areas: improving resource utilization, balancing fairness and efficiency in scheduling, and minimizing job completion time. By synthesizing and evaluating existing methods, this paper identifies potential future research directions in computing resource scheduling, including the effective scheduling of heterogeneous resources, joint scheduling of multiple resources, cross-domain scheduling, and optimization of energy consumption. Furthermore, the paper addresses the significance of tackling future challenges in computing resource scheduling, focusing on three aspects: heterogeneous perception and measurement, large-scale multi-resource collaborative scheduling, and cross-domain communication.

Authors

Institutions

Publication Details

Published
2024-11-22
DOI
https://doi.org/10.1109/icicml63543.2024.10957997
Citations
1
Primary Topic
Distributed and Parallel Computing Systems
Type
article
Field-Weighted Citation Impact
0.35

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Research Progress on Computing Resource Scheduling in Computing Power Network

Xingping Wu, Songling Tang, Congfeng Jiang, Jianing Niu et al.
1 citations
Distributed and Parallel Computing Systems
0.35
article

Research Progress on Computing Resource Scheduling in Computing Power Network

Xingping Wu, Songling Tang, Congfeng Jiang, Jianing Niu, Chunpeng Wu, Long Yan, Yonghe Guo, Zhipeng Feng, Junming Liu, Xinyi Cai
article en
1 citations

Abstract

In the evolution of computing power networks, the effective scheduling of computing resources has become a critical concern, driven by the diversification of computing demands and the increasing heterogeneity of resources. This paper provides a review of scheduling strategies for computing resources within these networks, analyzing methods that are relevant for the current landscape, including CPUs and GPUs. It emphasizes application scenarios and benefits across three key areas: improving resource utilization, balancing fairness and efficiency in scheduling, and minimizing job completion time. By synthesizing and evaluating existing methods, this paper identifies potential future research directions in computing resource scheduling, including the effective scheduling of heterogeneous resources, joint scheduling of multiple resources, cross-domain scheduling, and optimization of energy consumption. Furthermore, the paper addresses the significance of tackling future challenges in computing resource scheduling, focusing on three aspects: heterogeneous perception and measurement, large-scale multi-resource collaborative scheduling, and cross-domain communication.

State Grid Corporation of China (China) (CN), Hangzhou Dianzi University (CN)
State Grid Corporation of China
Openalex Percentile: Top 33%
Distributed and Parallel Computing Systems
0.35
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Research Progress on Computing Resource Scheduling in Computing Power Network — Xingping Wu, Songling Tang, et al. · (2024) | TGRS Research Map | TGRS