Fargraph: Optimizing Graph Workload on RDMA-Based Far Memory Architecture

Authors: Jing Wang, Chao Li, Taolei Wang, Lu Zhang, Pengyu Wang, Junyi Mei, and Minyi Guo (Shanghai Jiao Tong University)

Abstract: Disaggregated architecture brings new opportunities to memory-consuming applications like graph analytics. It allows one to outspread memory access pressure from local to far memory, providing an attractive alternative to disk-based processing. In this paper, we take the first step to analyze the impact of graph processing workload on disaggregated architecture. We design Fargraph, a far memory coordination strategy for enhancing graph processing workloads on top of an RDMA-based far memory system.

Best Poster Finalist (BP): no

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