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dc.contributor.authorZhao, Yuqing
dc.description.abstractProduct data parallel GPU processor has recently attracted many application developers attention. GPU architecture now has many advantages. It can provide easier programmability and increase generality. GPU maintains the tremendous memory bandwidth and computational power which make it better than traditional CPU in doing computational problems. For this project aims to develop efficient programs running on graphical processor unit (GPU). The project involves GPU programming and testing. This project presents the test graphics processing unit (GPU) after make a comparison between CPU and GPU in the same environment. In this way we can determine the computational efficiency of GPU over CPU. The test method is about accelerated FADI-FDTD which is fundamental alternating-direction-implicit finite-difference time-domain with CFS-CPML (complex frequency shifted convolution perfectly matched layer. Using CUDA architecture to program GPU for CUDA is both a hardware and software platform that enables NVIDIA GPU to execute programs written with C/C++ or other languages. The FADI-FDTD with CFS-CPML is further incorporated into the GPU to exploit data parallelism. Results show that GPU can gain a much higher efficient.en_US
dc.format.extent53 p.en_US
dc.rightsNanyang Technological University
dc.subjectDRNTU::Engineering::Electrical and electronic engineering::Computer hardware, software and systemsen_US
dc.titleDevelopment of efficient programs on GPUen_US
dc.typeFinal Year Project (FYP)en_US
dc.contributor.supervisorTan Eng Leongen_US
dc.contributor.schoolSchool of Electrical and Electronic Engineeringen_US
dc.description.degreeBachelor of Engineeringen_US
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Appears in Collections:EEE Student Reports (FYP/IA/PA/PI)
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