Level-3 Cholesky Factorization Routines Improve Performance of Many Cholesky Algorithms

Author:

Gustavson Fred G.1,Waśniewski Jerzy2,Dongarra Jack J.3,Herrero José R.4,Langou Julien5

Affiliation:

1. IBM T.J. Watson Research Center, Emeritus and Umeå University, Adjunct

2. Technical University of Denmark

3. University of Tennessee, Oak Ridge National Laboratory and University of Manchester

4. Universitat Politècnica de Catalunya, BarcelonaTech

5. University of Colorado at Denver

Abstract

Four routines called DPOTF3i, i = a,b,c,d, are presented. DPOTF3i are a novel type of level-3 BLAS for use by BPF ( B locked P acked F ormat) Cholesky factorization and LAPACK routine DPOTRF. Performance of routines DPOTF3i are still increasing when the performance of Level-2 routine DPOTF2 of LAPACK starts decreasing. This is our main result and it implies, due to the use of larger block size nb , that DGEMM, DSYRK, and DTRSM performance also increases! The four DPOTF3i routines use simple register blocking. Different platforms have different numbers of registers. Thus, our four routines have different register blocking sizes. BPF is introduced. LAPACK routines for POTRF and PPTRF using BPF instead of full and packed format are shown to be trivial modifications of LAPACK POTRF source codes. We call these codes BPTRF. There are two variants of BPF: lower and upper. Upper BPF is “identical” to Square Block Packed Format (SBPF). “LAPACK” implementations on multicore processors use SBPF. Lower BPF is less efficient than upper BPF. Vector inplace transposition converts lower BPF to upper BPF very efficiently. Corroborating performance results for DPOTF3i versus DPOTF2 on a variety of common platforms are given for nnb as well as results for large n comparing DBPTRF versus DPOTRF.

Funder

Ministerio de Educación, Cultura y Deporte

Publisher

Association for Computing Machinery (ACM)

Subject

Applied Mathematics,Software

Cited by 1 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. A Square Block Format for Symmetric Band Matrices;Parallel Processing and Applied Mathematics;2014

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3