ExaSAT: An exascale co-design tool for performance modeling
ExaSAT: An exascale co-design tool for performance modeling
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ExaSAT：用于性能建模的百亿亿次协同设计工具
DOI：
10.1177/1094342014568690
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发表时间：
2015
期刊：
影响因子：
--
通讯作者：
J. Shalf
中科院分区：
文献类型：
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作者：
D. Unat;Cy P. Chan;Weiqun Zhang;Samuel Williams;J. Bachan;J. Bell;J. Shalf
设计HPC系统面临的一个新挑战是理解和预测兆级应用的需求。为了确定不同硬件设计的性能结果，分析模型是必不可少的，因为它们可以为协同设计中心和芯片设计人员提供快速反馈，而无需昂贵的仿真。然而，目前试图分析建模程序性能通常依赖于用户手动指定的性能模型。我们介绍的ExaSAT框架，自动提取参数化的性能模型直接从源代码使用编译器分析。参数化分析模型能够对各种不同性能指标的广泛硬件设计权衡和软件优化进行定量评估，主要关注数据移动作为指标。我们展示了ExaSAT框架的能力，从能源部燃烧协同设计中心的代理应用程序进行深度代码分析，以说明其价值的exascale协同设计过程。ExaSAT分析提供了对硬件和软件权衡的见解，并为使用周期精确的架构模拟器探索更有针对性的设计点奠定了基础。
One of the emerging challenges to designing HPC systems is understanding and projecting the requirements of exascale applications. In order to determine the performance consequences of different hardware designs, analytic models are essential because they can provide fast feedback to the co-design centers and chip designers without costly simulations. However, current attempts to analytically model program performance typically rely on the user manually specifying a performance model. We introduce the ExaSAT framework that automates the extraction of parameterized performance models directly from source code using compiler analysis. The parameterized analytic model enables quantitative evaluation of a broad range of hardware design trade-offs and software optimizations on a variety of different performance metrics, with a primary focus on data movement as a metric. We demonstrate the ExaSAT framework’s ability to perform deep code analysis of a proxy application from the Department of Energy Combustion Co-design Center to illustrate its value to the exascale co-design process. ExaSAT analysis provides insights into the hardware and software trade-offs and lays the groundwork for exploring a more targeted set of design points using cycle-accurate architectural simulators.