Multi-resource scheduling algorithm based on EDA simulation software

doi:10.7523/j.issn.2095-6134.2021.05.014

Abstract

Abstract: In order to improve the resource utilization of electronic design automation(EDA) parallel simulation tasks and ensure fairness, on the basis of dominant resource fairness allocation(DRF), dominant resource fairness allocation algorithm considering license(LDRF) is proposed. On the one hand, the problem of fair scheduling of multiple types of resources is considered, satisfying the diversity of resource requirements of EDA tasks. On the other hand, the license resource scheduling of EDA tool is considered to avoid the reduction of utilization caused by the lack of license for hardware resources. The experimental simulation results show that under the condition of limited license, the CPU resource utilization of LDRF is increased by 60% compared with DRF, and the memory resource utilization rate is increased by 34%.

Key words: resource allocation, DRF algorithm, fairness, EDA software, license scheduling

CLC Number:

TP301.6

WANG Jing, CHEN Lan, ZHANG He, WANG Haiyong. Multi-resource scheduling algorithm based on EDA simulation software[J]. Journal of University of Chinese Academy of Sciences, 2021, 38(5): 696-701.

References

[1] Stok, Leon. The next 25 years in EDA:a cloudy future?[J]. IEEE Design & Test, 2014, 31(2):40-46.
[2] 刘军华, 杨海钢. 一种快速并行协同仿真的验证方法[J]. 微电子学, 2008, 38(4):66-69,89.
[3] 王超, 陈香兰, 周学海, 等. 异构多核平台上基于任务划分和调度的性能评估方法[J]. 中国科学院研究生院学报, 2012, 29(2):257-263.
[4] 常天海, 胡鉴. 基于FPGA的CRC并行算法研究与实现[J]. 微处理机, 2010, 31(2):47-50.
[5] Ghodsi A, Zaharia M, Hindman B, et al. Dominant resource fairness:fair allocation of multiple resource types[C]//Proceedings of the 8th USENIX Conference on NSDI. Berkeley:USENIX Association, 2011:24-37.
[6] Wang W, Liang B, Li B. Multi-resource fair allocation in heterogeneous cloud computing systems[J]. IEEE Transactions on Parallel & Distributed Systems, 2015, 26(10):2822-2835.
[7] 李杰, 张静, 李伟东, 等. 一种基于共享公平和时变资源需求的公平分配策略[J]. 计算机研究与发展, 2019, 56(7):1534-1544.
[8] Li W, Liu X, Zhang X, et al. A further analysis of the dynamic dominant resource fairness mechanism[C]//Proceedings of the 11th International Conference on Frontiers in Algorithmics. Berlin:Springer, 2017:163-174.
[9] 马宏星, 周学海, 高妍妍, 等. 一种集成可重构硬件的多核片上系统的软硬件任务划分与调度算法[J]. 中国科学院研究生院学报, 2010, 27(5):664-669.
[10] Doulamis N, Varvarigos E, Varvarigou T. Fair scheduling algorithms in grids[J]. IEEE Transactions on Parallel & Distributed Systems, 2007, 18(11):1630-1648.
[11] 柯尊旺, 于炯, 廖彬. 适应异构集群的Mesos多资源调度DRF增强算法[J]. 计算机应用, 2016, 36(5):1216-1221.
[12] 卢笛, 马建峰, 王一川, 等. 云计算下保障公平性的多资源分配算法[J]. 西安电子科技大学学报, 2014, 41(3):162-168.
[13] 刘晓茜, 杨寿保, 郭磊涛, 等. 网格市场中基于成本计算的任务调度研究[J]. 中国科学院研究生院学报, 2008, 25(3):379-385.
[14] Bouveret S, Lang J. Efficiency and envy-freeness in fair division of indivisible goods:logical representation and complexity[J]. Journal of Artificial Intelligence Research, 2008, 32:525-564.
[15] 洪雁, 何晓林. 基于帕累托最优的公平性探讨[J]. 科技创业月刊, 2006, 19(11):175-176.
[16] Lan T, Kao D, Chiang M, et al. An axiomatic theory of fairness in network resource allocation[C]//proceedings of the IEEE INFOCOM. Piscataway:IEEE, 2010:1-9.
[17] Kuenne R E. Equity:in theory and practice[J]. Southern Economic Journal, 1995, 61(3):885-886.
[18] 王寅峰, 董小社, 郭华, 等. 网格环境中软件共享系统的License管理器[J]. 华中科技大学学报(自然科学版), 2006, 34(s1):5-8.