.png){kind=icon}
返回
Iterative list scheduling for heterogeneous computing
.png){kind=icon}
PRE
AI
DOI：10.1016/j.jpdc.2005.01.002.png)
.png){kind=icon}
原文求助.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
Optimal scheduling of parallel applications on distributed computing systems represented by directed acyclic graph (DAG) is NP-complete in the general case. List scheduling is a very popular heuristic method for DAG-based scheduling. However, it is more suited to homogenous distributed computing systems. This paper presents an iterative list scheduling algorithm to deal with scheduling on heterogeneous computing systems. The main idea in this iterative scheduling algorithm is to improve the quality of the schedule in an iterative manner using results from previous iterations. The algorithm first uses the heterogeneous earliest-finish-time (HEFT) algorithm to find an initial schedule and iteratively improves it. Hence the algorithm can potentially produce shorter schedule length. The simulation results show that in the majority of the cases, there is significant improvement to the initial schedule. The algorithm is also found to perform best when the tasks to processors ratio is large. (c) 2005 Elsevier Inc. All rights reserved.
Keyword:
task scheduling
heterogeneous computing systems
list scheduling
randomly generated DAGs
AI总结
对已上传原文的论文进行重点信息的提取，主要内容包括：简要概述、研究摘要、背景介绍、关键亮点、图文解析、展望与总结。
期刊
IF:
4
论文数:
3.8K
被引数:
4.8K
机构
暂无机构信息
引用论文
An optimal scheduling algorithm for minimizing the computing period of cyclic synchronous tasks on multiprocessors最小化多处理器上循环同步任务计算周期的最佳调度算法
PREAI
分享收藏
分享收藏Investigation of the optical properties of the Cr doped CuxO thin film deposited by thermionic vacuum arc plasma.png)
Optik
OptikIF0
PREAI
分享收藏
查看更多内容