Minimizing Cost of Scheduling Tasks on Heterogeneous Multicore Embedded Systems

被引：27
|
作者：
Liu, Jing [1 ,2 ,7 ]
Li, Kenli [1 ,8 ]
Zhu, Dakai [3 ]
Han, Jianjun [4 ]
Li, Keqin [5 ,6 ]
机构：
[1] Hunan Univ, Coll Informat Sci & Engn, Changsha 410082, Hunan, Peoples R China
[2] Wuhan Univ Sci & Technol, Coll Comp Sci & Technol, Wuhan 430065, Peoples R China
[3] Univ Texas San Antonio, Dept Comp Sci, One UTSA Circle, San Antonio, TX 78249 USA
[4] Huazhong Univ Sci & Technol, Dept Comp Sci & Technol, Wuhan 430074, Peoples R China
[5] Hunan Univ, Changsha, Hunan, Peoples R China
[6] SUNY Coll New Paltz, Dept Comp Sci, New Paltz, NY 12561 USA
[7] Hubei Prov Key Lab Intelligent Informat Proc & Re, Wuhan 430065, Peoples R China
[8] Natl Supercomp Ctr Changsha, Changsha 410082, Hunan, Peoples R China
来源：
ACM TRANSACTIONS ON EMBEDDED COMPUTING SYSTEMS | 2017年 / 16卷 / 02期
基金：
中国国家自然科学基金;
关键词：
Graph grouping; heterogeneous multicore systems; task scheduling; time and resource constraints; REAL-TIME TASKS; ENERGY; ASSIGNMENT;
D O I：
10.1145/2935749
中图分类号：
TP3 [计算技术、计算机技术];
学科分类号：
0812 ;
摘要：
Cost savings are very critical in modern heterogeneous computing systems, especially in embedded systems. Task scheduling plays an important role in cost savings. In this article, we tackle the problem of scheduling tasks on heterogeneous multicore embedded systems with the constraints of time and resources for minimizing the total cost, while considering the communication overhead. This problem is NP-hard and we propose several heuristic techniques-ISGG, RLD, and RLDG-to address the problem. Experimental results show that the proposed algorithms significantly outperform the existing approaches in terms of cost savings.
引用
收藏
页数：25
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