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NETWORK DESIGN CONSIDERATIONS FOR EXASCALE SUPERCOMPUTERS

机译:Exascale超级计算机的网络设计考虑因素

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We consider the network design optimization for the Exascale class supercomputers by altering the widely analyzed and implemented torus networks. Our alteration scheme involves interlacing the torus networks with bypass links of lengths 6 hops, 9 hops, 12 hops, and mixed 6 and 12 hops. These bypass links are optimal resulting from exhaustive search of massive possibilities. Our case study is constructed by strategically coupling 288 racks of 6 × 6 × 36 nodes to a full system with 72 × 72 × 72 nodes. The peak performance of such a system is 0.56 Exa-flops when CPU-GPU complexes are adopted as a node module capable of 1.5 Tflops. Our design optimizes, simultaneously, the system performance, performancecost ratio, and power efficiency. The network diameter and the average node-to-node network distance, regarded as the performance metrics, got reduced, from the original 3D torus network, by 83.3% and 80.4%, respectively. Similarly, the performance-cost ratio and power efficiency are also increased 1.43 and 4.44 times, respectively.
机译:我们通过改变广泛分析和实施的Torus网络来考虑Exascale类超级计算机的网络设计优化。我们的改动方案涉及与长度6跳,9跳,12次跳跃和混合6和12跳的旁路连接的绕行环路。这些旁路链接是由穷举搜索大规模可能性的最佳选择。我们的案例研究是通过策略性地耦合288个6×6×36节点的288个机架,以具有72×72×72节点的完整系统。当CPU-GPU复合物采用作为能够1.5 TFLOPS的节点模块采用CPU-GPU复合物时,这种系统的峰值性能为0.56 exa-FLOPS。我们的设计同时优化,系统性能,PerformanceCTOST比率和功率效率。被视为性能指标的网络直径和平均节点网络距离从原始3D Torus网络减少83.3%和80.4%。类似地,性能成本比和功率效率也分别增加1.43和4.44倍。

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