Parallel Simulation of Many-Core Processor and Many-Core Clusters

Lü Huiwei; Cheng Yuan; Bai Lu; Chen Mingyu; Fan Dongrui; Sun Ninghui

Journal of Computer Research and Development > 2013 > 50(5): 1110-1117.

Lü Huiwei, Cheng Yuan, Bai Lu, Chen Mingyu, Fan Dongrui, Sun Ninghui. Parallel Simulation of Many-Core Processor and Many-Core Clusters[J]. Journal of Computer Research and Development, 2013, 50(5): 1110-1117.

Citation:

PDF (2975 KB)

Parallel Simulation of Many-Core Processor and Many-Core Clusters

1(State Key Laboratory of Computer Architecture (Institute of Computing Technology, Chinese Academy of Sciences), Beijing 100190) 2(University of Chinese Academy of Sciences, Beijing 100049)

More Information

Published Date: May 14, 2013

Graphical Abstract

Abstract

Abstract

Computer architecture simulator is an important tool for computer architecture researchers. Recent development of parallel architectures bring great challenge to computer simulations. On the target side, as processors move towards multi-core and many-core, the complexity of the target system is doubling in the speed of Moore’s law as the simulated target core number grows; on the host side, the speed of sequential simulation is halted as the speed of a single host processor halts. Due to the above two reasons, sequential simulation could no longer meet the challenge of new parallel architectures. In this paper, we will describe the necessity and feasibility of parallel simulation for parallel computer architectures using two examples: a many-core processor simulator and a many-core cluster simulator. For many-core processor simulator, we use parallel discrete event simulation (PDES) to speed it up 10.9 times without accuracy lost. For many-core cluster simulation, we simulated a cluster at 1024-core scale, with MPI/Pthreads runtime support.
- parallel simulation,
- many-core processor,
- many-core cluster,
- many-core processor simulation,
- MPI/Pthreads hybrid programming

FullText(HTML)

References (0)

[1]	Xu He, Wu Di, Lu Jiwu, Li Renfa. An Intrusion Detection Algorithm and Its Hardware Acceleration for CAN in Vehicles[J]. Journal of Computer Research and Development, 2023, 60(12): 2783-2796. DOI: 10.7544/issn1000-1239.202220035
[2]	Yin Shenglin, Zhang Xinglan, Zuo Liyu. Intrusion Detection System for Dual Route Deep Capsule Network[J]. Journal of Computer Research and Development, 2022, 59(2): 418-429. DOI: 10.7544/issn1000-1239.20200825
[3]	Ren Jiadong, Liu Xinqian, Wang Qian, He Haitao, Zhao Xiaolin. An Multi-Level Intrusion Detection Method Based on KNN Outlier Detection and Random Forests[J]. Journal of Computer Research and Development, 2019, 56(3): 566-575. DOI: 10.7544/issn1000-1239.2019.20180063
[4]	Shi Shengfei, Zhang Wei, Li Jianzhong. A Complex Event Detection Algorithm Based on Correlation Analysis[J]. Journal of Computer Research and Development, 2014, 51(8): 1871-1879. DOI: 10.7544/issn1000-1239.2014.20120813
[5]	Wang Qi'an and Chen Bing. Intrusion Detection System Using CVM Algorithm with Extensive Kernel Methods[J]. Journal of Computer Research and Development, 2012, 49(5): 974-982.
[6]	Mao Guojun and Zong Dongjun. An Intrusion Detection Model Based on Mining Multi-Dimension Data Streams[J]. Journal of Computer Research and Development, 2009, 46(4): 602-609.
[7]	Li Qinghua and Zhao Feng. The PBL Method: A Novel Parallel Error Detection Method for Intrusion Tolerance Systems[J]. Journal of Computer Research and Development, 2006, 43(8): 1411-1416.
[8]	Yang Wu, Yun Xiaochun, Li Jianhua. An Efficient Approach to Intrusion Detection Based on Boosting Rule Learning[J]. Journal of Computer Research and Development, 2006, 43(7): 1252-1259.
[9]	Mu Chengpo, Huang Houkuan, and Tian Shengfeng. A Survey of Intrusion-Detection Alert Aggregation and Correlation Techniques[J]. Journal of Computer Research and Development, 2006, 43(1): 1-8.
[10]	Wang Jin, Li Dequan, and Feng Dengguo. An Autonomous Agent-Based Adaptive Distributed Intrusion Detection System[J]. Journal of Computer Research and Development, 2005, 42(11): 1934-1939.