2009 · 30 citations · 9 references
ComputingComputer ScienceHigh-performance ComputingComputational PhysicsParallel AlgorithmsParallel ComputingData ParallelismFinite Difference MethodsFinite Difference Time Domain AnalysisGraphics Processing Unit ComputingGraphics Processing UnitsParallel Numerical MethodsFinite Difference Time Domain SimulationGpu ArchitectureGpu Parallel AlgorithmsParallel Reduction AlgorithmsScientific Computing On GpusThread ParallelismThread-based ParallelismThread-level Parallelism
We present preliminary results of the acceleration of the three-dimensional (3D) alternating direction implicit finite-difference time-domain (ADI-FDTD) method on graphics processor units (GPUs). Although the ADI-FDTD iteration comprises two substeps, which each require solving a tridiagonal matrix system of equations over xy, xz, yz planes of the domain, the application of this scheme frees the time-step size from the Courant-Friedrichs-Lewy stability constraint. In our implementation we took advantage of the fine-grain thread parallelism and coarse-grained block parallelism of the GPU architecture, allowing us to use the parallel cyclic reduction method to simultaneously solve many tridiagonal systems of equations. We obtained a satisfactory speedup of the method indicating that GPUs represent an inexpensive source of computational power for accelerated ADI-FDTD simulations.
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