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Further improvements of parallel N-FINDR algorithm using NVidia GPUs

机译:使用NVidia GPU的并行N-FINDR算法的进一步改进

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Based on our previous work about parallel implementation on N-FINDR in cluster environment, we give some supplements and further developed parallel N-FINDR algorithms by using NVidia graphics processing units (GPUs). Two characterizes are presented. First, extended volume calculation is further considered. Our proposed method is only involved in matrix-vector or vector-vector multiplication, which is suitable to be performed on GPUs. Second, due to the limitation of constant memory providing for GPUs, two patterns for parallel implementation of N-FINDR are considered with the imagery in both reduced and original dimension. In experiments, our proposed algorithms greatly improved the performance of N-FINDR and obtained nearly real-time capability.
机译:基于我们以前在集群环境中在N-FINDR上并行执行的工作,我们提供了一些补充,并通过使用NVidia图形处理单元(GPU)进一步开发了并行N-FINDR算法。介绍了两个特征。首先,进一步考虑扩展体积计算。我们提出的方法仅涉及矩阵向量或向量向量乘法,适合在GPU上执行。其次,由于为GPU提供恒定内存的限制,考虑了N-FINDR并行实现的两种模式,图像尺寸和原始尺寸均如此。在实验中,我们提出的算法大大提高了N-FINDR的性能,并获得了几乎实时的功能。

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