大规模集群的指令级模拟

E. León, R. Riesen, A. Maccabe, P. Bridges
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引用次数: 34

摘要

指令级仿真对于评估新架构是必要的。然而,单节点模拟不能预测超级计算机上并行应用程序的行为。我们提出了一个可扩展的模拟器,将周期精确节点模拟器与超级计算机网络模型相结合。我们的模拟器在数百个内核上执行IBM的Mambo PowerPC模拟器的单个实例。我们将NIC仿真器集成到Mambo中,并对网络进行建模,而不是完全模拟它。这解耦了各个节点模拟器,使我们的设计具有可伸缩性。我们的模拟器在数百个节点上运行未经修改的并行消息传递应用程序。我们可以更改网络和详细的节点参数,将网络流量直接注入缓存,并使用不同的策略来决定什么时候这样做是有利的。本文详细介绍了我们的仿真器,对其进行了评估,并论证了其可扩展性。我们通过评估缓存注入对并行应用程序性能的影响来证明它对架构研究的适用性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Instruction-level simulation of a cluster at scale
Instruction-level simulation is necessary to evaluate new architectures. However, single-node simulation cannot predict the behavior of a parallel application on a supercomputer. We present a scalable simulator that couples a cycle-accurate node simulator with a supercomputer network model. Our simulator executes individual instances of IBM's Mambo PowerPC simulator on hundreds of cores. We integrated a NIC emulator into Mambo and model the network instead of fully simulating it. This decouples the individual node simulators and makes our design scalable. Our simulator runs unmodified parallel message-passing applications on hundreds of nodes. We can change network and detailed node parameters, inject network traffic directly into caches, and use different policies to decide when that is an advantage. This paper describes our simulator in detail, evaluates it, and demonstrates its scalability. We show its suitability for architecture research by evaluating the impact of cache injection on parallel application performance.
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