A Comparison of Vivado HLS, SDSoC C++ and OpenCL for Porting a Matrix-vector-based Climate model mini-app to FPGAs

The High-Performance Computing (HPC) community's interest in FPGAs as accelerators has been renewed due to the introduction of High-Level Synthesis tools (HLS). HLS tools hide the complexity of FPGA programming through raising the abstraction level for programmers. They offer environments where traditional HPC programmers can use high-level languages such as C/C++ and OpenCL to implement HPC application kernels on FPGAs. However the use of an HLS environment implies trade-offs between the achievable performance and programmer effort. This paper presents a comparative study between three HLS programming methodologies, Xilinx Vivado HLS and Xilinx SDSoC using both OpenCL and C++, all targeting the Xilinx Zynq UltraScale+ MPSoC ZCU102. We use a matrix-vector kernel from the LFRic weather and climate model mini-app to compare the programming techniques, effort and resulting performance of an implementation using Vivado HLS with the higher level of abstraction provided by SDSoC C/C++ and OpenCL. We provide a comparative analysis of the design choices, scaling behaviour and peak performance. We find that Vivado HLS provides the highest performance due to the programmer's ability to exploit lowlevel FPGA features in the manual construction of the hardware system design, but near equivalent solutions can be obtained with OpenCL and C++, with automatic design generation resulting in reduced programmer effort.