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Parallel Discrete Event Simulation for Multi-Core Systems: Analysis and Optimization

机译:多核系统的并行离散事件仿真:分析和优化

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Parallel Discrete Event Simulation (PDES) can substantially improve the performance and capacity of simulation, allowing the study of larger, more detailed models, in less time. PDES is a fine-grained parallel application whose performance and scalability is limited by communication latencies. Traditionally, PDES simulation kernels use message passing; often these simulators are written for distributed environments, and shared memory is used to optimize message passing among processes on the same machine. In this paper, we develop, characterize and optimize a thread-based version of a PDES simulator on three representative multi-core platforms. The multi-threaded implementation eliminates multiple message copying and significantly minimizes synchronization delays. We study the performance of the simulator on three hardware platforms: an Intel Core i7 machine, and a 48-core AMD Opteron Magny-Cours system, and a 64-core Tilera TilePro64. We discover that the three platforms encounter substantially different bottlenecks because of their different architectures. We identify these bottlenecks and propose mechanisms to overcome them. Our results show that multi-threaded implementation improves the performance over an MPI-based version by up to a factor of 3 on the Core i7, 1.4 on the AMD Magny-Cours, and 2.8 on the Tilera Tile64.
机译:并行离散事件模拟(PDES)可以大大提高模拟的性能和容量,从而可以在更短的时间内研究更大,更详细的模型。 PDES是一种细粒度的并行应用程序,其性能和可伸缩性受到通信延迟的限制。传统上,PDES仿真内核使用消息传递。通常,这些模拟器是为分布式环境编写的,共享内存用于优化同一台计算机上进程之间的消息传递。在本文中,我们在三个有代表性的多核平台上开发,表征和优化了基于线程的PDES仿真器版本。多线程实现消除了多个消息复制,并极大地减少了同步延迟。我们在三个硬件平台上研究了模拟器的性能:一台Intel Core i7机器,一个48核AMD Opteron Magny-Cours系统和一个64核Tilera TilePro64。我们发现这三个平台由于其体系结构的不同而遇到了根本不同的瓶颈。我们确定了这些瓶颈,并提出了克服这些瓶颈的机制。我们的结果表明,与基于MPI的版本相比,多线程实现将Core i7的性能提高了3倍,AMD Magny-Cours的性能提高了1.4倍,Tilera Tile64的性能提高了2.8倍。

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