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引用次数: 16
摘要
随着计算系统的性能发展到百亿亿级,单个处理器中最小的元素可以极大地影响整个计算机系统(例如其功耗)。随着未来几代处理器的开发,门级的仿真是必要的,以确保在制造之前满足必要的目标性能基准。目前可用的最常见的仿真工具要么使用单个节点,要么使用小型集群,因此在开发过程中造成了瓶颈。本文主要研究了利用超级计算机系统对逻辑门电路模型进行大规模并行仿真。这项性能研究的重点是利用Rensselaer的乐观仿真系统(ROSS)的OpenSPARC T2处理器设计。我们在24核SMP机器和IBM Blue Gene/L上对横杆组件进行了模拟。使用单个SMP内核作为基准,我们在1024个Blue Gene/L内核上进行的性能实验表明,执行速度提高了131倍以上。我们的结果利用了Blue Gene/L系统的平衡计算和网络能力。
Modeling Large Scale Circuits Using Massively Parallel Discrete-Event Simulation
As computing systems grow to exascale levels of performance, the smallest elements of a single processor can greatly affect the entire computer system (e.g. its power consumption). As future generations of processors are developed, simulation at the gate level is necessary to ensure that the necessary target performance benchmarks are met prior to fabrication. The most common simulation tools available today utilize either a single node or small clusters and as such create a bottleneck in the development process. This paper focuses on the massively parallel simulation of logic gate circuit models using supercomputer systems. The focus of this performance study leverages the OpenSPARC T2 processor design using Rensselaer's Optimistic Simulation System (ROSS). We conduct simulations of the crossbar component on both a 24-core SMP machine and an IBM Blue Gene/L. Using a single SMP core as the baseline, our performance experiments on 1024 cores of the Blue Gene/L demonstrate more than 131-times faster execution. Our results capitalize on the balanced compute and network power of the Blue Gene/L system.