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Title: PuLP/XtraPuLP : Partitioning Tools for Extreme-Scale Graphs

Abstract

PuLP/XtraPulp is software for partitioning graphs from several real-world problems. Graphs occur in several places in real world from road networks, social networks and scientific simulations. For efficient parallel processing these graphs have to be partitioned (split) with respect to metrics such as computation and communication costs. Our software allows such partitioning for massive graphs.

Authors:
 [1];  [1];  [2]
  1. Sandia National Laboratories
  2. Penn State University
Publication Date:
Research Org.:
Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)
Sponsoring Org.:
USDOE
OSTI Identifier:
1343414
Report Number(s):
PuLP/XtraPuLP; 005141MLTPL00
SCR #2139
DOE Contract Number:
AC04-94AL85000
Resource Type:
Software
Software Revision:
00
Software Package Number:
005141
Software CPU:
MLTPL
Source Code Available:
Yes
Country of Publication:
United States

Citation Formats

Slota, George M, Rajamanickam, Sivasankaran, and Madduri, Kamesh. PuLP/XtraPuLP : Partitioning Tools for Extreme-Scale Graphs. Computer software. Vers. 00. USDOE. 21 Sep. 2017. Web.
Slota, George M, Rajamanickam, Sivasankaran, & Madduri, Kamesh. (2017, September 21). PuLP/XtraPuLP : Partitioning Tools for Extreme-Scale Graphs (Version 00) [Computer software].
Slota, George M, Rajamanickam, Sivasankaran, and Madduri, Kamesh. PuLP/XtraPuLP : Partitioning Tools for Extreme-Scale Graphs. Computer software. Version 00. September 21, 2017.
@misc{osti_1343414,
title = {PuLP/XtraPuLP : Partitioning Tools for Extreme-Scale Graphs, Version 00},
author = {Slota, George M and Rajamanickam, Sivasankaran and Madduri, Kamesh},
abstractNote = {PuLP/XtraPulp is software for partitioning graphs from several real-world problems. Graphs occur in several places in real world from road networks, social networks and scientific simulations. For efficient parallel processing these graphs have to be partitioned (split) with respect to metrics such as computation and communication costs. Our software allows such partitioning for massive graphs.},
doi = {},
year = 2017,
month = 9,
note =
}

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