2007 · 45 citations · 7 references
EngineeringComputer EngineeringComputer ScienceComputational Fluid DynamicsFluid DynamicsReconfigurable ComputingAccelerator ArchitectureData ParallelismHardware AccelerationLattice Boltzmann MethodsParallel ArchitecturesStream ProcessingData Path DesignLattice Boltzmann EquationLattice Boltzmann SimulationResource Utilization OptimizationStreamed ComputationStreaming ArchitecturesStreaming ComputationStreaming Data Processing
This paper presents an FPGA-based streaming computation for the lattice Boltzmann method (LBM) to simulate fluid flow with floating-point calculations. LBM is suitable for streaming computation because of its parallelism and regularity. We optimize the equations of LBM, and then formulate a streaming computation. To design an efficient data-path for throughput and hardware resource utilization, we introduce multiple cycle inputs and computing-unit sharing to the streaming data-path. The streaming accelerator implemented on a Virtex-4 FPGA with PCTExpress x8 interface achieves 2.93 and 2.46 times faster computation than a 3.4 GHz Pentium4 processor and a 2.2 GHz Opteron processor, respectively, for 2-dimensional time-dependent fluid dynamics problems.
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Lattice Boltzmann computational fluid dynamics in three dimensions
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