LAGraph: Linear Algebra, Network Analysis Libraries, and the Study of Graph Algorithms

被引：4

作者：

Szarnyas, Gabor ^{[1
]}

Bader, David A. ^{[2
]}

Davis, Timothy A. ^{[3
]}

Kitchen, James ^{[4
]}

Mattson, Timothy G. ^{[5
]}

McMillan, Scott ^{[6
]}

Welch, Erik ^{[4
]}

机构：

[1] CWI Amsterdam, Amsterdam, Netherlands

[2] New Jersey Inst Technol, Newark, NJ 07102 USA

[3] Texas A&M Univ, College Stn, TX 77843 USA

[4] Anaconda Inc, Austin, TX USA

[5] Intel Corp, Santa Clara, CA 95051 USA

[6] Carnegie Mellon Univ, Software Engn Inst, Pittsburgh, PA 15213 USA

来源：

2021 IEEE INTERNATIONAL PARALLEL AND DISTRIBUTED PROCESSING SYMPOSIUM WORKSHOPS (IPDPSW) | 2021年

基金：

美国安德鲁·梅隆基金会;

关键词：

Graph Processing; Graph Algorithms; Graph Analytics; Linear Algebra; GraphBLAS;

D O I：

10.1109/IPDPSW52791.2021.00046

中图分类号：

TP3 [计算技术、计算机技术];

学科分类号：

0812 ;

摘要：

Graph algorithms can be expressed in terms of linear algebra. GraphBLAS is a library of low-level building blocks for such algorithms that targets algorithm developers. LAGraph builds on top of the GraphBLAS to target users of graph algorithms with high-level algorithms common in network analysis. In this paper, we describe the first release of the LAGraph library, the design decisions behind the library, and performance using the GAP benchmark suite. LAGraph, however, is much more than a library. It is also a project to document and analyze the full range of algorithms enabled by the GraphBLAS. To that end, we have developed a compact and intuitive notation for describing these algorithms. In this paper, we present that notation with examples from the GAP benchmark suite.

引用

页码：243 / 252

页数：10

共 50 条

[41] Performance and energy analysis of OpenMP runtime systems with dense linear algebra algorithms
Ferreira Lima, Joao Vicente
Rais, Issam
Lefevre, Laurent
Gautier, Thierry
INTERNATIONAL JOURNAL OF HIGH PERFORMANCE COMPUTING APPLICATIONS, 2019, 33 (03): : 431 - 443
[42] Performance and Energy Analysis of OpenMP Runtime Systems with Dense Linear Algebra Algorithms
Lima, Joao V. F.
Rais, Issam
Lefevre, Laurent
Gautier, Thierry
2017 INTERNATIONAL SYMPOSIUM ON COMPUTER ARCHITECTURE AND HIGH PERFORMANCE COMPUTING WORKSHOPS (SBAC-PADW), 2017, : 7 - 12
[43] LINEAR ALGORITHMS FOR GRAPH SEPARATION PROBLEMS
DJIDJEV, HN
LECTURE NOTES IN COMPUTER SCIENCE, 1988, 318 : 216 - 222
[44] Graphulo: Linear Algebra Graph Kernels for NoSQL Databases
Gadepally, Vijay
Bolewski, Jake
Hook, Dan
Hutchison, Dylan
Miller, Ben
Kepner, Jeremy
2015 IEEE 29TH INTERNATIONAL PARALLEL AND DISTRIBUTED PROCESSING SYMPOSIUM WORKSHOPS, 2015, : 822 - 830
[45] A Linear Algebra Approach to Some Problems of Graph Theory
Kalinina, Elizaveta A.
Khitrov, Gennady M.
2017 ELEVENTH INTERNATIONAL CONFERENCE ON COMPUTER SCIENCE AND INFORMATION TECHNOLOGIES (CSIT), 2017, : 5 - 8
[46] Formal methods for high-performance linear algebra libraries
Gunnels, John A.
van de Geijn, Robert A.
IFIP Advances in Information and Communication Technology, 2001, 60 : 193 - 208
[47] Rapid development of high-performance linear algebra libraries
Bientinesi, Paolo
Gunnels, John A.
Gustavson, Fred G.
Henry, Greg M.
Myers, Margaret
Quintana-Orti, Enrique S.
van de Geijn, Robert A.
APPLIED PARALLEL COMPUTING: STATE OF THE ART IN SCIENTIFIC COMPUTING, 2006, 3732 : 376 - 384
[48] Formal methods for high-performance linear algebra libraries
Gunnels, JA
van de Geijn, RA
ARCHITECTURE OF SCIENTIFIC SOFTWARE, 2001, 60 : 193 - 210
[49] Parallelizing dense and banded linear algebra libraries using SMPSs
Badia, Rosa M.
Herrero, Jose R.
Labarta, Jesus
Perez, Josep M.
Quintana-Orti, Enrique S.
Quintana-Orti, Gregorio
CONCURRENCY AND COMPUTATION-PRACTICE & EXPERIENCE, 2009, 21 (18): : 2438 - 2456
[50] Multilevel Approaches to Fine Tune Performance of Linear Algebra Libraries
Gheibi, Sanaz
Banerjee, Tania
Ranka, Sanjay
Sahni, Sartaj
2019 IEEE 19TH INTERNATIONAL SYMPOSIUM ON SIGNAL PROCESSING AND INFORMATION TECHNOLOGY (ISSPIT 2019), 2019,

← 1 2 3 4 5 →