Performance Evaluation of PDES on Multi-core Clusters
Performance Evaluation of PDES on Multi-core Clusters
复制标题
PDES在多核集群上的性能评估
DOI：
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发表时间：
2010
期刊：
影响因子：
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通讯作者：
D. Ponomarev
中科院分区：
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作者：
Ketan Bahulkar;Nicole Hofmann;Deepak Jagtap;N. Abu;D. Ponomarev
超大规模集成电路和微架构设计的趋势已经迎来了多核时代，芯片上的内核数量预计将随着每一代处理器的增长而增长。很快，每个芯片都将拥有大量紧密集成的处理核心，其通信延迟将大大低于传统集群中的通信延迟。由这样的微处理器组成的集群在核心之间经历非均匀的延迟：同一芯片上的核心可以比不同芯片上的核心更快地通信，同一机器上的核心可以比不同机器上的核心更快地通信。在本文中，我们的性能特点的PDES模型的双四核机集群使用参数化修改版本的Phold，并行仿真的标准基准。我们研究了区域和远程通信模式的各种组合，以量化通信对仿真整体性能的影响。我们发现，通信量具有决定性的影响，必须在每个级别上优化这种通信，以最大限度地利用多核平台。我们表明，分区显着提高性能。我们还探讨了负载不平衡对应用程序性能的影响，并就如何为这些不同的环境进行分区提供了重要的见解。我们认为，这项研究是一个重要的第一步，在这个新兴的平台上的性能空间的特点。
Trends in VLSI and micro architecture design have ushered in the multi-core era, where the number of cores on a chip is expected to grow with every processor generation. Soon, each chip will have a large number of tightly integrated processing cores with communication latencies substantially lower than those present in conventional clusters. Clusters made of such microprocessors experience non-uniform latencies between cores: cores on the same chip can communicate faster than cores on different chips, cores on the same machine can communicate faster than cores on different machines. In this paper, we characterize the performance of PDES models on a cluster of dual quad-core machines using a parameterizable modified version of Phold, a standard benchmark for parallel simulation. We study various combinations of regional and remote communication patterns to quantify the impact of communication on overall performance of simulation. We discover that the amount of communication has determining impact and it’s essential to optimize this communication at each level to take maximum advantage of multi-core platform. We show that partitioning significantly improves performance. We also explore the impact of load imbalance on application performance and provide critical insight into how to partition for these different environments. We believe that this study represents a significant first step in characterizing the performance space for PDES on this emerging platform.