FSimGP^2: An Efficient Fault Simulator with GPGPU
Min Li, Michael S. Hsiao · 2010
General Purpose computing on Graphical Processing Units (GPGPU) is a paradigm shift in computing that promises a dramatic increase in performance. But GPGPU also brings an unprecedented level of complexity in algorithmic design and software development. In this paper, we present an efficient parallel fault simulator, FSimGP2, that exploits the high degree of parallelism supported by a state-of-the-art graphic processing unit (GPU) with the NVIDIA Compute Unified Device Architecture (CUDA). A novel three-dimensional parallel fault simulation technique is proposed to achieve extremely high computation efficiency on the GPU. The experimental results demonstrate a speedup of up to 42× compared to another GPU-based fault simulator and up to 53× over a state-of-the-art algorithm on conventional processor architectures.