Performance impact of resource contention in multicore systems
Performance impact of resource contention in multicore systems
复制标题
多核系统中资源争用的性能影响
DOI：
10.1109/ipdps.2010.5470399
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发表时间：
2010
期刊：
影响因子：
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通讯作者：
R. Biswas
中科院分区：
文献类型：
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作者：
R. Hood;Haoqiang Jin;P. Mehrotra;Johnny Chang;J. Djomehri;S. Gavali;D. Jespersen;K. Taylor;R. Biswas
商用多核处理器中的资源共享会对生产应用程序的性能产生重大影响。在本文中，我们使用差分性能分析方法来量化的成本竞争的资源中使用的几个多核处理器在高端计算机的内存层次结构。特别是，通过比较以不同模式将MPI进程绑定到核心的运行，我们可以隔离资源共享的影响。我们使用这种方法来衡量这种共享如何影响NASA感兴趣的四个应用程序的性能- OVERFLOW，MITgcm，Cart 3D和NCC。我们还使用HPCC基准测试和硬件计数器数据的子集来帮助解释和验证我们的发现。我们在使用四种不同四核微处理器的高端计算平台上进行研究-英特尔Clovertown，英特尔Harpertown，AMD Barcelona和英特尔Nehalem-EP。这些结果有助于我们进一步了解这些代码对其生产环境的要求，以及每台计算机提供性能的能力。
Resource sharing in commodity multicore processors can have a significant impact on the performance of production applications. In this paper we use a differential performance analysis methodology to quantify the costs of contention for resources in the memory hierarchy of several multicore processors used in high-end computers. In particular, by comparing runs that bind MPI processes to cores in different patterns, we can isolate the effects of resource sharing. We use this methodology to measure how such sharing affects the performance of four applications of interest to NASA — OVERFLOW, MITgcm, Cart3D, and NCC. We also use a subset of the HPCC benchmarks and hardware counter data to help interpret and validate our findings. We conduct our study on high-end computing platforms that use four different quad-core microprocessors — Intel Clovertown, Intel Harpertown, AMD Barcelona, and Intel Nehalem-EP. The results help further our understanding of the requirements these codes place on their production environments and also of each computer's ability to deliver performance.