On benchmarking task scheduling algorithms for heterogeneous computing systems

2018 ◽  
Vol 74 (7) ◽  
pp. 3039-3070 ◽  
Author(s):  
Ashish Kumar Maurya ◽  
Anil Kumar Tripathi
Keyword(s):  
Task Scheduling ◽  
Heterogeneous Computing ◽  
Scheduling Algorithms ◽  
Computing Systems ◽  
Heterogeneous Computing Systems

scholarly journals Energy-Aware Task Scheduling on Heterogeneous Computing Systems With Time Constraint

IEEE Access ◽  
2020 ◽  
Vol 8 ◽  
pp. 23936-23950 ◽  
Author(s):  
Zexi Deng ◽  
Zihan Yan ◽  
Huimin Huang ◽  
Hong Shen
Keyword(s):  
Task Scheduling ◽  
Heterogeneous Computing ◽  
Time Constraint ◽  
Energy Aware ◽  
Computing Systems ◽  
Heterogeneous Computing Systems

Task Scheduling in Heterogeneous Computing Systems Based on Machine Learning Approach

2020 ◽  
Vol 34 (12) ◽  
pp. 2051012
Author(s):  
Hui Xie ◽  
Li Wei ◽  
Dong Liu ◽  
Luda Wang
Keyword(s):  
Task Scheduling ◽  
Heterogeneous Computing ◽  
Scheduling Algorithm ◽  
Computing System ◽  
Scheduling Problem ◽  
Computing Systems ◽  
Task Scheduling Algorithm ◽  
Machine Learning Approach ◽  
Heterogeneous Computing Systems ◽  
Regression Theory

Task scheduling problem of heterogeneous computing system (HCS), which with increasing popularity, nowadays has become a research hotspot in this domain. The task scheduling problem of HCS, which can be described essentially as assigning tasks to the proper processor for executing, has been shown to be NP-complete. However, the existing scheduling algorithm suffers from an inherent limitation of lacking global view. Here, we reported a novel task scheduling algorithm based on Multi-Logistic Regression theory (called MLRS) in heterogeneous computing environment. First, we collected the best scheduling plans as the historical training set, and then a scheduling model was established by which we could predict the following schedule action. Through the analysis of experimental results, it is interpreted that the proposed algorithm has better optimization effect and robustness.

Sign in / Sign up

Export Citation Format

Share Document