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一个针对并行模拟引擎的性能评测实例

Parallel Benchmark for Evaluating Parallel Simulation Engine
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摘要 SimK是由中科院计算所体系结构国家重点实验室开发的一个并行离散时间模拟引擎。基于已经发布的SimK1.0版本,对任务划分及同步推进阻塞控制进行了功能扩展,开发了SimK的1.1版本。同时由于缺乏一个专门对SimK模拟性能评测的Benchmark以及全面的评测结果,首先讨论了并行模拟引擎Benchmark的设计准则,之后介绍了开发的Benchmark-PassBall,并且使用它对SimK的强弱扩展性、组件负载不均衡情况下的强扩展性进行了评测,同时对比了组件负载不均衡和均衡情况下的加速比,探讨了模拟计算量的变化对模拟加速比的影响,并讨论了Benchmark的适用性。通过实验讨论得出:a)PassBall可以作为并行模拟引擎SimK性能评测的Benchmark,亦可用于其他并行模拟引擎性能的评测;b)SimK具有良好的强弱扩展性;c)负载平衡和模拟计算量都会对并行模拟加速比产生影响。 SimK is a parallel discrete event simulation engine developed by state key laboratory of computer architecture in institute of computing technology, chinese academy of sciences. Based on the released SimK-1. 0, we extended the function of task partition and the blocking controlling in the process of synchronization. We released version 1. 1 of SimK. On the other hand, as it lacks a benchmark to specifically SimK simulation performance and there is no compre- hensive evaluation data, we first proposed the rules of development Benchmark for parallel simulation engine. Then we introduced the example "PassBall". We used it to do the evaluation of SimK on the weak and strong scalability,as well as the strong scalability in unbalanced workload condition. Then we compared the speed-up ratio between the balanced workload and unbalanced workload condition in strong scalability test. The influence of simulated computing workload on speed-up ration from was also explored. We also discussed the applicability of the Benchmark. It can be concluded from our experiments as follows : a) our example "PassBall" is available to be the benchmark for SimK,as well as other parallel simulation engine, b)SimK has favorable strong and weak scalability, c)Both the load balance and the simulated computing workload will have effect on the speed-up ratio.
出处 《计算机科学》 CSCD 北大核心 2013年第3期41-45,共5页 Computer Science
基金 NSFC国家自然科学基金项目(61272132) NSFC国家杰出青年科学基金(60925009) NSFC创新研究群体科学基金(60921002) 973项目(2011CB302502) 中科院战略性先导专项(XDA06010401)资助
关键词 并行模拟 模拟引擎 扩展性 SimK BENCHMARK Parallel simulation, Simulation engine, Scalability, SimK, Benchmark
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参考文献15

  • 1SimK Project[OL].https://sourceforge.net/projects/simk/files/.
  • 2Torus[OL].http://en.wikipedia.org/wiki/Torus.
  • 3Andersen R,Lang K J.An algorithm for improving graph partitions[C] // Proceedings of the Nineteenth Annual ACM-SIAM Symposium on Discrete Algorithms.San Francisco,California,2008:651-660.
  • 4Hendricksom B,Leland R.The chaco user's guide:Version 2.0[M].Sandia National Laboratories,1994.
  • 5Boukerche A,Das S K.Dynamic load balancing strategies for conservative parallel simulations[C] //Proceedings of the Eleventh Workshop on Parallel and Distributed Simulation.Lockenhaus,Austria,1997:20-28.
  • 6Boukerche A,Das S K.Null messages cancellation through load balancing in distributed simulations[C] // Euro-Par' 99:Parallel Processing.vol.1685,1999:562-569.
  • 7Cao Z,Xu J,Chen M,et al.HPPNetSim:a parallel simulation of large-scale interconnection networks[C] //Proceedings of the 2009 Spring Simulation Multiconference.San Diego,California,2009:1-8.
  • 8Cheng Y,Bai L,Chen M,et al.P-GAS:Parallelizing a Cycle-Accurate Event-Driven Many-Core Processor Simulator Using Parallel Discrete Event Simulation[C] //Principles of Advanced and Distributed Simulation.2010:1-8.
  • 9范东睿,袁楠,张军超,周永彬,林伟,宋风龙,叶笑春,黄河,余磊,龙国平,张浩,刘磊.Godson-T:An Efficient Many-Core Architecture for Parallel Program Executions[J].Journal of Computer Science & Technology,2009,24(6):1061-1073. 被引量:11
  • 10Fujimoto R M.Parallel Discrete Event Simulation[J].Communications of the ACM,1990,33(10):30-53.

二级参考文献39

  • 1Asanovic K et al. The landscape of parallel computing research: A view from Berkeley. Technical Report No.UCB/EECS-2006-183, University of California, Berkeley, December 18, 2006.
  • 2Lee E A. The problem with threads. Computer, 2006, 39(5): 33-42.
  • 3Cantrill B, Bonwick J. Real-world concurrency. ACM Queue, 2008, 6(5): 16-25.
  • 4Adve S V, Adve V Set al. Parallel computing research at Illinois: The UPCRC agenda. Technical Report, University of Illinois at Urbana-Chmnpaign, November 2008.
  • 5Yuan N, Yu L, Fan D. An efficient and flexible task management for many-core architectures. In Proc. Workshop on Software and Hardware Challenges of Manycore Platforms, in Conjunction with the 35th International Symposium on Computer Architecture (ISCA-35), Beijing, China, June 22- 26, 2008, pp.1-17.
  • 6Blumofe R D, Leiserson C E. Scheduling multithreaded computations by work stealing. Journal of the ACM, 1999, 46(5): 720-748.
  • 7Palatin P, Lhuillier Y, Temam O. CAPSULE: Hardwareassisted parallel execution of component-based programs. In Proe. the 39th Annual IEEE/A CM International Symposium on Micro-Architecture, Washington, DC, USA: IEEE Computer Society, Dec. 9-13, 2006, pp.247-258.
  • 8Villa O, Palermo G, Silvano C. Efficiency and scalability of barrier synchronization on NoC based many-core architecture. In Proc. CASES2008, Atlanta, USA, Oct. 19-24, 2008, pp.81-90.
  • 9Carlson W W, Draper J Met al. Introduction to UPC and language specification. Technical Report No. CCS-TR-99- 157, University of California, Berkeley, 1999.
  • 10Numrich R W, Reid J. Co-array Fortran for parallel programming. SIGPLAN Fortran Forum, 1998, 17(2): 1-31.

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