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General purpose computing on graphical processing units (GPGPU) is a paradigm shift in computing that promises a dramatic increase in performance. 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. A novel 3-D parallel fault simulation technique is proposed to achieve extremely high computation efficiency on the GPU. Global communication is minimized by concentrating as much work as possible on the local device's memory. We present results on a GPU platform from NVIDIA (a GeForce GTX 285 graphics card) that demonstrate a speedup of up to 63× and 4× compared to two other GPU-based fault simulators and up to 95× over a state-of-the-art algorithm on conventional processor architectures.