基于fpga平台的LGCA流体动力学高性能计算

Changdao Du, Iman Firmansyah, Y. Yamaguchi
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引用次数: 0

摘要

晶格气体元胞自动机(LGCA)模拟是典型的高性能计算(HPC)应用,通常用于模拟流体流动。由于LGCA的计算局部性和离散性,这些模拟可以通过使用gpu或多核cpu等并行计算设备来实现高性能。然而,许多研究也表明,最先进的现场可编程门阵列(fpga)具有巨大的并行计算潜力和高效能的高性能计算。本文提出了一种基于fpga的LGCA方法流体仿真体系结构设计。我们的设计利用LGCA算法内的时间和空间并行性来扩展FPGA上的性能。我们还提出了一种特定于应用程序的缓存结构来克服内存带宽瓶颈。此外,我们的开发过程是基于提高生产力的高级综合(HLS)方法。在Xilinx Vcu 1525 FPGA上的实验结果表明,我们的设计能够达到每秒17130.2亿次晶格更新(MLUPS)。
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High-Performance Computation of LGCA Fluid Dynamics on an FPGA-Based Platform
Lattice Gas Cellular Automata (LGCA) simulations are typical High-Performance Computing (HPC) applications commonly used to simulate fluid flows. Due to the computational locality and discretization of LGCA, these simulations can achieve high performance by using parallel computing devices like GPUs or multi-core CPUs. Nevertheless, many studies also have shown that state-of-the-art Field Programmable Gate Arrays (FPGAs) have enormous parallel computing potential and power-efficient for high-performance computations. In this paper, we present an FPGA-based fluid simulation architecture design for the LGCA method. Our design exploits both temporal and spatial parallelism inside the LGCA algorithm to scale up the performance on FPGA. We also propose an application-specific cache structure to overcome the memory bandwidth bottleneck. Furthermore, our development process is based on the High-Level Synthesis (HLS) approach that increases productivity. Experimental results on a Xilinx Vcu 1525 FPGA show that our design is able to achieve 17130.2 Million Lattice Updates Per Second (MLUPS).
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