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HiTC: High-performance triangle counting on HBM-equipped FPGAs using HLS

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Thesis type
(Thesis) M.A.Sc.
Date created
Triangle counting (TC) is one of the fundamental computing patterns in graph computing and social networks. Due to its high memory-to-computation ratio and random memory access patterns, it is nontrivial to accelerate TC's performance. In this work, we propose a high performance TC (HiTC) accelerator to speed up triangle counting on high-bandwidth memory (HBM)-equipped FPGAs via software/hardware codesign. First, we propose hardware friendly reordering, tiling, and encoding techniques to address the random access issue and optimize bandwidth utilization. Based on that, we design streaming-based hardware accelerators on FPGAs which leverage HBM to achieve higher bandwidth and customize the computation pipeline for better computing throughput. Experiments using the SuiteSparse dataset show that our HiTC achieves a geomean speedup of 8.6x (up to 24.1x) over the Vitis TC FPGA library on the AMD-Xilinx HBM-based Alveo U280 FPGA. Compared to the software implementation on two 12-core Intel Xeon Silver 4214 CPUs, HiTC achieves a geomean speedup of 18.6x (up to 669.8x).
60 pages.
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Copyright is held by the author(s).
This thesis may be printed or downloaded for non-commercial research and scholarly purposes.
Supervisor or Senior Supervisor
Thesis advisor: Fang, Zhenman
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