A Method of Ultra-Large-Scale Matrix Inversion Using Block Recursion

Ultra-large-scale matrix inversion has been applied as the fundamental operation of numerous domains, owing to the growth of big data and matrix applications. Using cryptography as an example, the solution of ultra-large-scale linear equations over finite fields is important in many cryptanalysis sc...

Full description

Bibliographic Details
Main Authors: HouZhen Wang, Yan Guo, HuanGuo Zhang
Format: Article
Language:English
Published: MDPI AG 2020-11-01
Series:Information
Subjects:
Online Access:https://www.mdpi.com/2078-2489/11/11/523
id doaj-94850868ff874146ada5c7b7ac46bc8a
record_format Article
spelling doaj-94850868ff874146ada5c7b7ac46bc8a2020-11-25T04:05:26ZengMDPI AGInformation2078-24892020-11-011152352310.3390/info11110523A Method of Ultra-Large-Scale Matrix Inversion Using Block RecursionHouZhen Wang0Yan Guo1HuanGuo Zhang2Key Laboratory of Aerospace Information Security and Trusted Computing, Ministry of Education, School of Cyber Science and Engineering, Wuhan University, Wuhan 430072, ChinaKey Laboratory of Aerospace Information Security and Trusted Computing, Ministry of Education, School of Cyber Science and Engineering, Wuhan University, Wuhan 430072, ChinaKey Laboratory of Aerospace Information Security and Trusted Computing, Ministry of Education, School of Cyber Science and Engineering, Wuhan University, Wuhan 430072, ChinaUltra-large-scale matrix inversion has been applied as the fundamental operation of numerous domains, owing to the growth of big data and matrix applications. Using cryptography as an example, the solution of ultra-large-scale linear equations over finite fields is important in many cryptanalysis schemes. However, inverting matrices of extremely high order, such as in millions, is challenging; nonetheless, the need has become increasingly urgent. Hence, we propose a parallel distributed block recursive computing method that can process matrices at a significantly increased scale, based on Strassen’s method; furthermore, we describe the related well-designed algorithm herein. Additionally, the experimental results based on comparison show the efficiency and the superiority of our method. Using our method, up to 140,000 dimensions can be processed in a supercomputing center.https://www.mdpi.com/2078-2489/11/11/523cryptanalysismatrix inversionalgebraic attackdistributed computing
collection DOAJ
language English
format Article
sources DOAJ
author HouZhen Wang
Yan Guo
HuanGuo Zhang
spellingShingle HouZhen Wang
Yan Guo
HuanGuo Zhang
A Method of Ultra-Large-Scale Matrix Inversion Using Block Recursion
Information
cryptanalysis
matrix inversion
algebraic attack
distributed computing
author_facet HouZhen Wang
Yan Guo
HuanGuo Zhang
author_sort HouZhen Wang
title A Method of Ultra-Large-Scale Matrix Inversion Using Block Recursion
title_short A Method of Ultra-Large-Scale Matrix Inversion Using Block Recursion
title_full A Method of Ultra-Large-Scale Matrix Inversion Using Block Recursion
title_fullStr A Method of Ultra-Large-Scale Matrix Inversion Using Block Recursion
title_full_unstemmed A Method of Ultra-Large-Scale Matrix Inversion Using Block Recursion
title_sort method of ultra-large-scale matrix inversion using block recursion
publisher MDPI AG
series Information
issn 2078-2489
publishDate 2020-11-01
description Ultra-large-scale matrix inversion has been applied as the fundamental operation of numerous domains, owing to the growth of big data and matrix applications. Using cryptography as an example, the solution of ultra-large-scale linear equations over finite fields is important in many cryptanalysis schemes. However, inverting matrices of extremely high order, such as in millions, is challenging; nonetheless, the need has become increasingly urgent. Hence, we propose a parallel distributed block recursive computing method that can process matrices at a significantly increased scale, based on Strassen’s method; furthermore, we describe the related well-designed algorithm herein. Additionally, the experimental results based on comparison show the efficiency and the superiority of our method. Using our method, up to 140,000 dimensions can be processed in a supercomputing center.
topic cryptanalysis
matrix inversion
algebraic attack
distributed computing
url https://www.mdpi.com/2078-2489/11/11/523
work_keys_str_mv AT houzhenwang amethodofultralargescalematrixinversionusingblockrecursion
AT yanguo amethodofultralargescalematrixinversionusingblockrecursion
AT huanguozhang amethodofultralargescalematrixinversionusingblockrecursion
AT houzhenwang methodofultralargescalematrixinversionusingblockrecursion
AT yanguo methodofultralargescalematrixinversionusingblockrecursion
AT huanguozhang methodofultralargescalematrixinversionusingblockrecursion
_version_ 1724433955858415616