并行计算系统的波长路由互连“光集线器”

Y. Urino, K. Mizutani, Tatsuya Usuki, S. Nakamura
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引用次数: 2

摘要

为了解决并行计算系统中节点间的带宽瓶颈,我们提出了一种波长路由的节点间互连“光集线器”。光集线器的物理拓扑结构为星型网络,这使得光集线器在吞吐量、规模、能耗和生命周期成本等方面具有优势。其逻辑拓扑结构为全网状网络,在时延和可靠性方面具有优势。我们引入了多路径路由,通过用我们的包装函数取代传统的MPI函数,扩展了全网格拓扑(如Optical Hub)的有效带宽。利用并行计算模拟器SimGrid,在光学集线器并行计算系统上模拟了并行基准测试的执行时间。结果表明,采用光集线器的并行计算系统比传统的并行计算系统具有更高的性能和更低的能耗。我们还研究了光集线器的可扩展性,并表明在蜻蜓网络中节点数量大的情况下,光集线器的递归分层配置可以大大节省电缆数量。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Wavelength-routing interconnect "Optical Hub" for parallel computing systems
To solve the inter-node bandwidth bottleneck in parallel computing systems, we propose a wavelength-routing inter-node interconnect "Optical Hub". The physical topology of Optical Hub is star network, which leads to advantages in term of its throughput, size, energy consumption and life-time cost. The logical topology is full-mesh network, which leads to advantages in term of its latency and reliability. We introduced multi-path routings, which expand the effective bandwidth with the full-mesh topology such as Optical Hub, by replacing conventional MPI functions with our wrapper functions. We simulated execution time of parallel benchmarks on the parallel computing system with Optical Hub using parallel computing simulator SimGrid. As a result, we have confirmed that the parallel computing system with Optical Hub can achieve higher performance and lower energy consumption than conventional ones. We also examined the scalability of Optical Hub and showed that recursive hierarchical configurations of Optical Hub can save cable count drastically in case of large number of nodes against Dragonfly networks.
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