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Compiler-Assisted Source-to-Source Skeletonization of Application Models for System Simulation

机译:系统仿真应用模型的编译器辅助源到源骨架化

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Performance modeling of networks through simulation requires application endpoint models that inject traffic into the simulation models. Endpoint models today for system-scale studies consist mainly of post-mortem trace replay, but these off-line simulations may lack flexibility and scalability. On-line simulations running so-called skeleton applications run reduced versions of an application that generate traffic that is the same or similar to the full application. These skeleton apps have advantages for flexibility and scalability, but they often must be custom written for the simulator itself. Auto-skeletonization of existing application source code via compiler tools would provide endpoint models with minimal development effort. These source-to-source transformations have been only narrowly explored. We introduce a pragma language and corresponding Clang-driven source-to-source compiler that performs auto-skeletonization based on provided pragma annotations. We describe the compiler toolchain, validate the generated skeletons, and show scalability of the generated simulation models beyond 100K endpoints for example MPI applications. Overall, we assert that our proposed auto-skeletonization approach and the flexible skeletons it produces can be an important tool in realizing balanced exascale interconnect designs.
机译:通过仿真对网络进行性能建模需要将流量注入仿真模型的应用程序端点模型。如今,用于系统规模研究的端点模型主要由事后跟踪重播组成,但是这些离线模拟可能缺乏灵活性和可伸缩性。运行所谓的框架应用程序的在线模拟运行的应用程序的简化版本生成的流量与整个应用程序相同或相似。这些框架应用程序具有灵活性和可伸缩性方面的优势,但是它们通常必须针对模拟器本身进行定制编写。通过编译器工具对现有应用程序源代码进行自动骨架化将为端点模型提供最少的开发工作量。这些源到源的转换仅在狭窄的范围内进行了探索。我们介绍了一种杂注语言和相应的Clang驱动的源到源编译器,该编译器根据提供的杂注注释执行自动骨架化。我们描述了编译器工具链,验证了生成的框架,并显示了生成的仿真模型的可扩展性(例如MPI应用程序)超过了10万个端点。总体而言,我们断言,我们提出的自动骨架化方法及其产生的灵活骨架可能是实现平衡百亿亿级互连设计的重要工具。

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