Acceleration of the Lattice Boltzmann Method for Fluid Flow

FPGAs (Field-Programmable Gate Arrays) are becoming increasingly attractive for high-performance scientific computing. FPGAs are high volume, off-the-shelf semiconductor devices containing programmable logic components, embedded arithmetic units, embedded memories and a programmable interconnection network. FPGAs have remarkably increased their potential for high-performance computing by integrating much more programmable hardware resources and increasing their operating frequency, and therefore recent leading-edge FPGAs can have peak floating-point computation performance surpassing that of typical microprocessors [1]. By designing a custom computing machine (CCM) on FPGAs, the properties, e.g., parallelism, regularity and homogeneity, of a specific application can be efficiently exploited by customized data-paths, customized arithmetic units and customized memory systems.