基于Adleman-Lipton模型的快速矩阵乘法技术

Aran Nayebi
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引用次数: 7

摘要

在分布式存储电子计算机上,快速并行矩阵乘法算法的实现和关联已经产生了惊人的结果和见解。在这篇论文中,我们使用分子生物学的工具来证明基于残数系统中n模集的DNA的Strassen快速矩阵乘法算法的理论编码,从而证明了DNA计算数学的可行性。因此,提出了该模型在DNA计算范例中的通用可扩展实现,并可推广到所有快速矩阵乘法算法在DNA计算机上的应用。我们还讨论了这种可扩展实现的实际功能和问题。使用DNA进行矩阵计算的快速方法很重要,因为它们还允许使用DNA有效地实现其他算法(即反转、计算行列式和图论)。关键词:DNA计算,剩余数系统,逻辑和算术运算,Strassen算法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Fast matrix multiplication techniques based on the Adleman-Lipton model
On distributed memory electronic computers, the implementation and association of fast parallel matrix multiplication algorithms has yielded astounding results and insights. In this discourse, we use the tools of molecular biology to demonstrate the theoretical encoding of Strassen’s fast matrix multiplication algorithm with DNA based on an n-moduli set in the residue number system, thereby demonstrating the viability of computational mathematics with DNA. As a result, a general scalable implementation of this model in the DNA computing paradigm is presented and can be generalized to the application of all fast matrix multiplication algorithms on a DNA computer. We also discuss the practical capabilities and issues of this scalable implementation. Fast methods of matrix computations with DNA are important because they also allow for the efficient implementation of other algorithms (that is inversion, computing determinants, and graph theory) with DNA.   Key words: DNA computing, residue number system, logic and arithmetic operations, Strassen algorithm.
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