Nuclear Reactor Simulations on OpenCL FPGA Platform
Zheming Jin, Hal Finkel · 2019
Field-programmable gate arrays (FPGAs) are becoming a promising choice as a heterogeneous computing component for scientific computing when floating-point optimized architectures are added to the current FPGAs. The maturing high-level synthesis (HLS) tools, such as Intel FPGA SDK for OpenCL, provide a streamlined design flow to facilitate parallel application on FPGAs. In this paper, we evaluate and optimize the OpenCL implementations of three nuclear reactor simulation applications (XSBench, RSBench, and SimpleMOC kernel) on a heterogeneous computing platform that consists of a general-purpose CPU and an FPGA. We introduce the applications, and describe their OpenCL implementations and optimization methods on an Arria10-based FPGA platform. Compared with the baseline kernel implementations, our optimizations increase the performance of the three kernels by a factor of 35, 295, and 102, respectively. We compare the performance, power, and performance per watt of the three applications on an Intel Xeon 16-core CPU, an Nvidia Tesla K80 GPU, and an Intel Arria10 GX1150 FPGA. The performance per watt on the FPGA is competitive. For XSBench, the performance per watt on the FPGA is 1.43X higher than that on the CPU, and 2.58X lower than that on the GPU. For RSBench, the performance per watt on the FPGA is 3.6X higher than that on the CPU, and 5.8X lower than that on the GPU. For SimpleMOC kernel, the performance per watt on the FPGA is 1.74X higher than that on the CPU, and 1.65X lower than that on the GPU.