Architecture and Performance Studies of 3D-Hyper-FleX-LION for Reconfigurable All-to-All HPC Networks

Authors: Gengchen Liu, Roberto Proietti, Marjan Fariborz, Pouya Fotouhi, Xian Xiao, and S.J.Ben Yoo (University of California, Davis)

Abstract: While the Fat-Tree network topology represents the dominant state-of-art solution for large-scale HPC networks, its scalability in terms of power, latency, complexity and cost is significantly challenged by the ever-increasing communication bandwidth among tens of thousands of heterogeneous computing nodes. We propose 3D-Hyper-FleX-LION, a flat hybrid electronic-photonic interconnect network that leverages the multi-channel nature of modern multi-terabit switch ASICs (with 100 Gb/s granularity) and a reconfigurable all-to-all photonic fabric called Flex-LIONS. Compared to a Fat-Tree network interconnecting the same number of nodes and with the same oversubscription ratio, the proposed 3D-Hyper-FleX-LION offers a 20% smaller diameter, 3x lower power consumption, 10x fewer cable connections, and a 4x reduction in the number of transceivers. When bandwidth reconfiguration capabilities of Flex-LIONS are exploited for non-uniform traffic workloads, simulation results indicate that 3D-Hyper-FleX-LION can achieve up to 4x improvement in energy efficiency for synthetic traffic workloads with high locality compared to Fat-Tree.




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