一个开源的互连网络模拟器,用于芯片多处理器和超级计算机

Pablo Abad Fidalgo, P. Prieto, L. G. Menezo, Adrian Colaso, Valentin Puente, J. Gregorio
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引用次数: 80

摘要

与其他计算机体系结构领域一样,互连网络的研究大多依赖于仿真工具。本文发布了一个开源工具,适用于从小型CMP到大型超级计算机互连网络的精确建模。TOPAZ的周期精确建模可以通过合成流量模式和应用程序跟踪独立使用,也可以毫不费力地在GEMS或GEM5等全系统评估系统中使用。事实上,我们提供了一个先进的接口,可以替代原来轻量级但乐观的GEMS和GEM5网络模拟器,对仿真时间的性能影响有限。我们的测试表明,在这种情况下,低估网络建模可能会在模拟系统的性能估计中导致高达50%的误差。为了最大限度地减少详细网络建模对仿真时间的影响,我们结合了能够降低较高计算工作量的机制,以这种方式减少了具有准确性能估计的完整系统仿真的速度。此外,为了评估大规模网络,我们将模拟器并行化,以便能够随着模拟农场中每个芯片可用的内核数量的增加而优化内存资源。这使我们能够模拟超过一百万个路由器的节点网络,在12核上运行的多线程模拟中效率高达70%。
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TOPAZ: An Open-Source Interconnection Network Simulator for Chip Multiprocessors and Supercomputers
As in other computer architecture areas, interconnection networks research relies most of the times on simulation tools. This paper announces the release of an open-source tool suitable to be used for accurate modeling from small CMP to large supercomputer interconnection networks. The cycle-accurate modeling of TOPAZ can be used standalone through synthetic traffic patterns and application-traces or within full-system evaluation systems such as GEMS or GEM5 effortlessly. In fact, we provide an advanced interface that enables the replacement of the original lightweight but optimistic GEMS and GEM5 network simulator with limited performance impact on the simulation time. Our tests indicate that in this context, underestimating network modeling could induce up to 50% error in the performance estimation of the simulated system. To minimize the impact of detailed network modeling on simulation time, we incorporate mechanisms able to attenuate the higher computational effort, reducing in this way the slowdown of the full system simulation with accurate performance estimations. Additionally, in order to evaluate large-scale networks, we parallelize the simulator to be able to optimize memory resources with the growing number of cores available per chip in the simulation farms. This allows us to simulate node networks exceeding one million of routers with up to 70% efficiency in a multithreaded simulation running on twelve cores.
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