通用组合编码中全序数的GPU并行算法

Juan Mo, Jun Lu, Nan Wang, Zhuo Zhang, Yu Liu
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引用次数: 4

摘要

通用组合编码是一种新的编码方法,全序数在通用组合编码中起着重要的作用。本文提出了一种全序数GPU并行算法。将GPU在复杂、庞大并行计算方面的优势与CPU技术相结合,采用CPU+GPU异构程序开发模式实现整体有序计算。在原全序数计算串行程序中调用大数乘法计算核函数,实现全序数并行计算。在研究过程中,通过对程序代码进行多次优化,解决了一系列GPU并行问题。实验表明,GPU并行方法大大提高了整个序数的计算速度,从而提高了相关实验的计算效率。全序并行实现对相关实验数据的估计也具有重要意义,同时推动了通用组合编码的步伐。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
The GPU parallel algorithm of whole ordinal in universal combinatorics coding
Universal combinatorics coding is a new kind of coding method and whole ordinal plays an important role in universal combinatorics coding. Whole ordinal GPU parallel algorithm is proposed in this paper. Whole ordinal computing is implemented by combining the advantage of GPU in aspect of complicated and vast parallel computing with CPU technology, and employing CPU+GPU heterogeneous program development model. It makes whole ordinal parallel computing implement by calling kernel function of large number multiplication calculation in original serial program of computing whole ordinal. In the process of research, a series of GPU parallel problem are solved by optimizing program code many times. Experiments show that GPU parallel method improves the speed of calculating whole ordinal greatly, and then improves the computation efficiency of relevant experiments. Whole ordinal parallel implementation also has important meaning to estimating relevant experimental data and pushes the pace of universal combinatorics coding into practical at the same time.
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