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This paper presents a parallel arithmetic coding scheme in which supports a large degree of parallelism with a marginal cost in terms of the coding efficiency. The parallelism is brought by coding the bits using multiple arithmetic coders. We identify two types of losses in coding efficiency by breaking the dependency among the data: the loss by breaking the probability prediction process and the...
A novel parallel approach to run standard particle swarm optimization (SPSO) on Graphic Processing Unit (GPU) is presented in this paper. By using the general-purpose computing ability of GPU and based on the software platform of Compute Unified Device Architecture (CUDA) from NVIDIA, SPSO can be executed in parallel on GPU. Experiments are conducted by running SPSO both on GPU and CPU, respectively,...
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