GPU Acceleration of Dense Matrix and Block Operations for Lanczos Method for Systems Over GF(2)


如何引用文章

全文:

开放存取 开放存取
受限制的访问 ##reader.subscriptionAccessGranted##
受限制的访问 订阅存取

详细

The algebraic operations with the dense matrices and blocks are bounding the scalability of block Lanczos–Montgomery method, that is used for the linear part in the RSA decomposition problem. This paper explores the possibility of implementation of the following algebraic operations over field \(\mathbb{F}_2\) on GPU: (1) multiplication of two 64k × 64k matrices; (2) multiplication of two N × 64k blocks. For matrix multiplication, we consider two algorithms: (a) the “naive” algorithm; (b) the “fast” algorithm by 4 Russians. For block multiplication, we consider just the “naive” algorithm. It seems that by now this is the only work where BLAS acceleration over \(\mathbb{F}_2\) are relatively successful accelerated on GPU.

作者简介

N. Zamarashkin

Marchuk Institute of Numerical Mathematics

编辑信件的主要联系方式.
Email: nikolai.zamarashkin@gmail.com
俄罗斯联邦, Moscow, 119333

D. Zheltkov

Marchuk Institute of Numerical Mathematics

编辑信件的主要联系方式.
Email: dmitry.zheltkov@gmail.com
俄罗斯联邦, Moscow, 119333


版权所有 © Pleiades Publishing, Ltd., 2019
##common.cookie##