Title:
Parallel Shortest Path Algorithms for Solving Large-Scale Instances

dc.contributor.author Madduri, Kamesh
dc.contributor.author Bader, David A.
dc.contributor.author Berry, Jonathan W.
dc.contributor.author Crobak, Joseph R.
dc.date.accessioned 2007-05-24T17:23:16Z
dc.date.available 2007-05-24T17:23:16Z
dc.date.issued 2006-08-30
dc.description.abstract We present an experimental study of parallel algorithms for solving the single source shortest path problem with non-negative edge weights (NSSP) on large-scale graphs. We implement Meyer and Sander's Δ-stepping algorithm and report performance results on the Cray MTA-2, a multithreaded parallel architecture. The MTA-2 is a high-end shared memory system offering two unique features that aid the efficient implementation of irregular parallel graph algorithms: the ability to exploit fine-grained parallelism, and low-overhead synchronization primitives. Our implementation exhibits remarkable parallel speedup when compared with a competitive sequential algorithm, for low-diameter sparse graphs. For instance, Δ-stepping on a directed scale-free graph of 100 million vertices and 1 billion edges takes less than ten seconds on 40 processors of the MTA-2, with a relative speedup of close to 30. To our knowledge, these are the first performance results of a parallel NSSP problem on realistic graph instances in the order of billions of vertices and edges. en_US
dc.identifier.uri http://hdl.handle.net/1853/14449
dc.language.iso en_US en_US
dc.publisher Georgia Institute of Technology en_US
dc.relation.ispartofseries CSE Technical Reports; GT-CSE-06-19 en_US
dc.subject Multithreaded architecture en_US
dc.subject Non-negative edge weights (NSSP) en_US
dc.subject Parallel algorithms en_US
dc.subject Shared memory system en_US
dc.title Parallel Shortest Path Algorithms for Solving Large-Scale Instances en_US
dc.type Text
dc.type.genre Technical Report
dspace.entity.type Publication
local.contributor.corporatename College of Computing
local.contributor.corporatename School of Computational Science and Engineering
local.relation.ispartofseries College of Computing Technical Report Series
local.relation.ispartofseries School of Computational Science and Engineering Technical Report Series
relation.isOrgUnitOfPublication c8892b3c-8db6-4b7b-a33a-1b67f7db2021
relation.isOrgUnitOfPublication 01ab2ef1-c6da-49c9-be98-fbd1d840d2b1
relation.isSeriesOfPublication 35c9e8fc-dd67-4201-b1d5-016381ef65b8
relation.isSeriesOfPublication 5a01f926-96af-453d-a75b-abc3e0f0abb3
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