.png){kind=icon}
返回
Memory limited algorithms for optimal task scheduling on parallel systems
.png){kind=icon}
PRE
AI
DOI：10.1016/j.jpdc.2016.03.003.png)
.png){kind=icon}
原文求助.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
To hilly benefit from a multi-processor system, tasks need to be scheduled optimally. Given that the task scheduling problem with communication delays, P vertical bar prec, c(ij)vertical bar C-max, is a well known strong NP-hard problem, exhaustive approaches are necessary. The previously proposed A* based algorithm retains its entire state space in memory and often runs out of memory before it finds an optimal solution. This paper investigates and proposes two memory limited optimal scheduling algorithms: Iterative Deepening A* (IDA*) and Depth-First Branch and Bound A* (BBA*). When finding a guaranteed near optimal schedule length is sufficient, the proposed algorithms can be combined, reporting the gap while they run. Problem specific pruning techniques, which are crucial for good performance, are studied for the two proposed algorithms. Extensive experiments are conducted to evaluate and compare the proposed algorithms with previous optimal algorithms. (C) 2016 Elsevier Inc. All rights reserved.
Keyword:
Optimal task scheduling
A*
Iterative Deepening A*
Depth-First Branch and Bound A*
Parallel systems
Memory limited
Iterative deepening
State space pruning
Optimisation algorithm
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
引用论文
.png){kind=icon}
分享收藏Mixed integer linear programming in process scheduling: Modeling, algorithms, and applications进程调度中的混合整数线性规划: 建模，算法和应用
PREAI
分享收藏分享收藏
查看更多内容