SIAM Journal on Numerical Analysis, Vol. 37, No. 1 (Nov. - Dec., 1999), pp. 105-130 (26 pages) The simplest finite difference approximations for spatial derivatives are centered, explicit, and applied ...
A modification of the central-difference method is given which greatly improves the convergence when applied to a certain class of singular eigenvalue problems, including the Klein-Gordon equation.
Developed a CUDA version of the FDTD method and achieved a speedup 40x. Implemented on a NVIDIA Quadro FX 3800 GPU, which has 192 SPs, 1GB global memory, and a memory bandwidth of 51.2 GB/s.
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