一种利用古印度吠陀数学经典在低端处理器上实现快速BCD除法的算法

D. Sengupta, M. Sultana, A. Chaudhuri
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引用次数: 8

摘要

在过去的十年或二十年里,随着加载了更多高速缓存存储器的快速处理器的推出,技术世界发生了快速发展。因此,系统架构需要更好的发展,以适应不断增长的技术进步的需求。组件的小型化和VLSI集成导致大量高级存储芯片被嫁接到更小的空间上,从而在普通应用程序的耗尽限制内访问更多的物理内存。但是内存有限的低端处理器仍然渴望快速的应用程序,由于空间和时间的复杂性,这些设备正在慢慢地超出界限。四种基本运算——加、减、乘、除构成了任何类型应用的基础。在这四种方法中,后一种方法,即除法,是一种非常昂贵和耗时的操作。针对内存有限的低端处理器,提出了一种基于古印度吠陀数学经典的快速除法算法。该算法的新颖之处在于,它只需要非常少的内存来执行,但执行除法机制比文献中的传统除法算法快得多,并且同样适用于高端处理器。该算法已在传统的中档桌面处理器上进行了测试,并提供了位数大于50(15位数字)的结果,这是传统算法可计算数的上限。据观察,吠陀除法算法可以除目前形式中最多38位(127位)的数字,如果修改它可以除更大的数字。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
An algorithm facilitating fast BCD division on low end processors using Ancient Indian Vedic Mathematics Sutras
The last decade or two has witnessed a rapid evolution of the technological world with the introduction of fast processors loaded with higher amount of cache memories. Accordingly, the system architecture demanded better development to suit the rising demand for the technological advancements. Miniaturizations of components and VLSI integration have given rise to bulk advanced memory chips being grafted on even smaller amount of space thus giving access to higher amount of physical memory within exhaust limits of average applications. But the low end processors having limited memory still crave for fast applications, which are slowly going out of bounds for these devices due to the space and time complexity. The four elementary operations - addition, subtraction, multiplication and division form the basis for any type of application. Out of the four, the latter one, namely division, is a highly expensive and time consuming operation. This paper proposes a fast division algorithm based on Ancient Indian Vedic Mathematics Sutras for low end processors having limited memory. The novelty of the algorithm is that it requires a very small amount of memory for execution but performs the division mechanism much faster than the conventional division algorithms in literature, and is equally suitable for high end processors also. The algorithm has been tested on conventional mid range desktop processors and has furnished results with numbers having number of bits greater than 50 (15 digit numbers), the upper ceiling of computable numbers for conventional algorithms. It has been observed that the Vedic Division Algorithm can divide numbers having up to 38 digits (127 bits) in the present form, if modified it can divide even bigger numbers.
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