Optimizing Memory Performance for FPGA Implementation of PageRank

Recently, FPGA implementation of graph algorithms arising in many areas such as social networks has been studied. However, the irregular memory access pattern of graph algorithms makes obtaining high performance challenging. In this paper, we present an FPGA implementation of the classic PageRank algorithm. Our goal is to optimize the overall system performance, especially the cost of accessing the off-chip DRAM. We optimize the data layout so that most of memory accesses to the DRAM are sequential. Post-place-and-route results show that our design on a state-of-the-art FPGA can achieve a high clock rate of over 200 MHz. Based on a realistic DRAM access model, we build a simulator to estimate the execution time including memory access overheads. The simulation results show that our design achieves at least 96% of the theoretically best performance of the target platform. Compared with a baseline design, our optimized design dramatically reduces the number of random memory accesses and improves the execution time by at least 70%.