We propose a simulation-based approach for performance modeling of parallel applications on high-performance computing platforms. Our approach enables full-system performance modeling: (1) the hardware platform is represented by an abstract yet high-fidelity model; (2) the computation and communication components are simulated at a functional level, where the simulator allows the use of the components native interface; this results in a (3) fast and accurate simulation of full HPC applications with minimal modifications to the application source code. This hardware/software hybrid modeling methodology allows for low overhead, fast, and accurate exascale simulation and can be easily carried out on a standard client platform (desktop or laptop). We demonstrate the capability and scalability of our approach with High Performance LINPACK (HPL), the benchmark used to rank supercomputers in the TOP500 list. Our results show that our modeling approach can accurately and efficiently predict the performance of HPL at the scale of the TOP500 list supercomputers. For instance, the simulation of HPL on Frontera takes less than five hours with an error rate of four percent.

中文翻译：

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基于仿真的 HPC 应用性能预测：HPL 案例研究

我们提出了一种基于仿真的方法，用于在高性能计算平台上对并行应用程序进行性能建模。我们的方法支持全系统性能建模：(1) 硬件平台由抽象但高保真的模型表示；(2) 计算和通信组件在功能级别进行模拟，其中模拟器允许使用组件本地接口；这导致 (3) 快速准确地模拟完整的 HPC 应用程序，而对应用程序源代码的修改最少。这种硬件/软件混合建模方法允许低开销、快速和准确的百亿亿次模拟，并且可以在标准客户端平台（台式机或笔记本电脑）上轻松执行。我们用高性能 LINPACK (HPL) 展示了我们方法的能力和可扩展性，用于在 TOP500 列表中对超级计算机进行排名的基准。我们的结果表明，我们的建模方法可以准确有效地预测 HPL 在 TOP500 列表超级计算机规模上的性能。例如，Frontera 上的 HPL 模拟耗时不到 5 小时，错误率为 4%。