A Memory Profiling Framework for Stencil Computation on an FPGA Accelerator with High Level Synthesis

摘要

In this paper, we propose a framework to assist memory access optimization for stencil computation on an FPGA accelerator. Since the stencil computations such as scientific simulations need large amounts of data, efficient memory access is a key to achieving high performance on FPGA accelerators. Therefore, we implemented a stencil computation framework with a memory performance profiler on MaxCompiler, which is one of high level synthesis systems. The memory profiler enables us to measure clock cycles for various memory controller states; data transfer, stall, and idle. We also implemented simple stencil computations and practical FDTD electromagnetic field simulations on top of the framework with various parameters to evaluate and analyze memory performance. As a result of execution experiments of the simple stencil computations on a MAX34245A Data Flow Engine, it was demonstrated that approximately 70% of the peak memory performance could be achieved for various stencil types. On the other hand, the FDTD simulations, which need many data streams, could not hit this memory performance saturation point, because of increasing complexity of memory controller modules. Through the analysis of evaluation results obtained by our memory performance profiling framework, a promising memory access optimization approach for stencil computations in which the complexity of the memory controller is traded off against data access traffic is suggested.