High Performance Parallel Computing in Residue Number System

被引：0

作者：

Deryabin, Maxim ^{[1
]}

Chervyakov, Nikolay ^{[1
]}

Tchernykh, Andrei ^{[2
]}

Babenko, Mikhail ^{[1
]}

Shabalina, Mariia ^{[1
]}

机构：

[1] North Caucasus Fed Univ, Stavropol, Russia

[2] CICESE Res Ctr, Ensenada, Baja California, Mexico

来源：

INTERNATIONAL JOURNAL OF COMBINATORIAL OPTIMIZATION PROBLEMS AND INFORMATICS | 2018年 / 9卷 / 01期

关键词：

Residue Number System; High-Performance Computing; number systems; parallel computing;

D O I：

暂无

中图分类号：

O29 [应用数学];

学科分类号：

070104 ;

摘要：

Residue Number System (RNS) allows performing computation more efficiently. Natural parallelism of representation and processing of numbers makes this number system suitable for applying to high performance computing. We address the main features of application of RNS to high-performance parallel computing. We consider and analyze different stages of data processing in RNS. Based on this analysis, we describe the process of decomposition of algorithms using RNS.

引用

页码：62 / 67

页数：6

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