[1]刘齐坚,王韦刚,高鹏程.基于GSLF-SSA的异构多核处理器任务调度[J].计算机技术与发展,2024,34(07):48-54.[doi:10.20165/j.cnki.ISSN1673-629X.2024.0121]
　LIU Qi-jian,WANG Wei-gang,GAO Peng-cheng.Task Scheduling for Heterogeneous Multi-core Processors Based on GSLF-SSA[J].,2024,34(07):48-54.[doi:10.20165/j.cnki.ISSN1673-629X.2024.0121]
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基于GSLF-SSA的异构多核处理器任务调度()

《计算机技术与发展》[ISSN:1006-6977/CN:61-1281/TN]

卷:
34
期数:
2024年07期
页码:
48-54
栏目:
软件技术与工程
出版日期:
2024-07-10

文章信息/Info

Title:
Task Scheduling for Heterogeneous Multi-core Processors Based on GSLF-SSA
文章编号:
1673-629X(2024)07-0048-07
作者:
刘齐坚; 王韦刚; 高鹏程
南京邮电大学 电子与光学工程学院、柔性电子(未来技术)学院,江苏 南京 210023
Author(s):
LIU Qi-jian; WANG Wei-gang; GAO Peng-cheng
School of Electronic and Optical Engineering & School of Flexible Electronics (Future Technology),Nanjing University of Posts and Telecommunications,Nanjing 210023,China
关键词:
异构多核处理器; 麻雀搜索算法; 有向无环图; 任务调度; 黄金正弦; 莱维飞行
Keywords:
heterogeneous multi-core processors; sparrow search algorithm; directed acyclic graph; task scheduling; golden sinusoidal; Levy Fligh
分类号:
TP181
DOI:
10.20165/j.cnki.ISSN1673-629X.2024.0121
摘要:
为了提高异构多核处理器平台的计算性能,从任务调度的角度出发,提出了一种使用黄金正弦和莱维飞行机制改进的麻雀搜索算法(Fusion of Golden Sinusoidal and Levy Flight in Sparrow Search Algorithm,GSLF-SSA)来优化异构多核处理器的任务调度。 通过对异构任务调度的分析,将异构任务建模为 DAG(Directed Acyclic Graph)任务模型,通过对其优先级进行随机编码分配,实现了 GSLF-SSA 算法求解域从连续到离散的映射,使该算法更能适用于异构多核任务调度之中。 将DAG 任务的最优调度长度作为算法的适应度值进行迭代寻优,通过与目前应用广泛的麻雀搜索算法(SSA)、混合式任务调度算法(IHSSA)、人工蜂群算法(ABC)等多种启发式算法在异构任务调度环境下的实验对比表明,GSLF-SSA 能获得更优的调度长度与更短的调度执行时间。
Abstract:
To enhance the computational performance of heterogeneous multi-core processor platforms,we propose an improved Sparrow Search Algorithm called the Fusion of Golden Sinusoidal and Levy Flight in Sparrow Search Algorithm (GSLF-SSA) to optimize task scheduling on heterogeneous multi-core processors. Through an analysis of heterogeneous task scheduling,we model these tasks as a Directed Acyclic Graph (DAG) task model. By randomly encoding priorities for these DAG tasks,the GSLF-SSA algorithm achieves a mapping of the solution domain from continuous to discrete,making it more adaptable for heterogeneous multi-core task scheduling. The algorithm iteratively refines its fitness value using the optimal scheduling length of DAG tasks. Experimental comparisons with several widely used heuristic algorithms in the context of heterogeneous task scheduling, including Sparrow Search Algorithm ( SSA), an improved task scheduling algorithm based on hybrid optimization strategy (IHSSA),and Artificial Bee Colony Algorithm (ABC), dem-onstrate that GSLF-SSA achieves superior scheduling lengths and shorter scheduling execution time.

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更新日期/Last Update: 2024-07-10