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In this paper, we present RAG, an efficient Reliability Analysis tool based on Graphics processing units (GPU). RAG is a fault injection based parallel stochastic simulator implemented on a state-of-the-art GPU. A two-stage simulation framework is proposed to exploit the high computation efficiency of GPUs. Experimental results demonstrate the accuracy and performance of RAG. An average speedup of...
In this paper, we propose a novel parallel state justification tool, GACO, utilizing Ant Colony Optimization (ACO) on Graphical Processing Units (GPU). With the high degree of parallelism supported by the GPU, GACO is capable of launching a large number of artificial ants to search for the target state. A novel parallel simulation technique, utilizing partitioned navigation tracks as guides during...
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, , that exploits the high degree of parallelism supported by a state-of-the-art...
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...
In this paper parallel program was performed for the FDTD electromagnetic algorithm on a multi-core CPU computer with CUDA device. In the case of two-dimension FDTD method, computation times were measured and compared to investigate the efficiency of parallel FDTD application. The results show that CUDA parallel program can improve the computing performance efficiently which can be used for three-dimension...
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