MapReduce for Integer Factorization
Distributed, Parallel, and Cluster Computing
2010-01-05 v1
Abstract
Integer factorization is a very hard computational problem. Currently no efficient algorithm for integer factorization is publicly known. However, this is an important problem on which it relies the security of many real world cryptographic systems. I present an implementation of a fast factorization algorithm on MapReduce. MapReduce is a programming model for high performance applications developed originally at Google. The quadratic sieve algorithm is split into the different MapReduce phases and compared against a standard implementation.
Keywords
Cite
@article{arxiv.1001.0421,
title = {MapReduce for Integer Factorization},
author = {Javier Tordable},
journal= {arXiv preprint arXiv:1001.0421},
year = {2010}
}
Comments
6 pages, 3 tables