NewGraph: Balanced Large-Scale Graph Processing on FPGAs with Low Preprocessing Overheads

Abstract

Large-scale graph processing has been widely required in various domains, including social network analysis, neural network modeling, database computing, etc. Performance of large-scale graph suffers from random and unpredictable data access pattern, which leads to drastic bandwidth degradation on caches, DRAMs, and disks. The support for high bandwidth random access makes SRAMs the promising solution for graph processing. Many FPGA based large-scale graph processing systems have been proposed in previous works and taken advantage of the SRAM resources.