Optimized Implementation of the HPCG Benchmark on Reconfigurable Hardware

Abstract

The HPCG benchmark represents a modern complement to the HPL benchmark in the performance evaluation of HPC systems, as it has been recognized as a more representative benchmark to reflect real-world applications. While typical workloads become more and more challenging, the semiconductor industry is battling with performance scaling and power efficiency on next-generation technology nodes. As a result, the industry is turning towards more customized compute architectures to help meet the latest performance requirements. In this paper, we present the details of the first FPGA-based implementation of HPCG that takes advantage of such customized compute architectures. Our results show that our high-performance multi-FPGA implementation, using 1 and 4 Xilinx Alveo U280 achieves up to 108.3 GFlops and 346.5 GFlops respectively, representing speed-ups of $104.1\times$ and $333.2\times$ over software running on a server with an Intel Xeon processor with no loss of accuracy. We also demonstrate that the FPGA-based solution achieves comparable performance with respect to modern GPUs and an up to $2.7\times$ improvement in terms of power efficiency compared to an NVIDIA Tesla V100. Finally, a theoretical evaluation, based on Berkeley’s Roofline model demonstrates that our implementation is near optimally tuned on the Xilinx Alveo U280.