Our paper “GraphACT: Accelerating GCN Training on CPU-FPGA Heterogeneous Platforms” has been accepted as a full paper at the 28th ACM/SIGDA International Symposium on Field-Programmable Gate Arrays (FPGA ’20). This paper describes a novel accelerator design for training GCNs on CPU-FPGA heterogeneous systems by incorporating multiple algorithm architecture co-optimizations.
