Title:
Parallel Shortest Path Algorithms for Solving Large-Scale Instances
Parallel Shortest Path Algorithms for Solving Large-Scale Instances
Author(s)
Madduri, Kamesh
Bader, David A.
Berry, Jonathan W.
Crobak, Joseph R.
Bader, David A.
Berry, Jonathan W.
Crobak, Joseph R.
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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.
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Date Issued
2006-08-30
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Text
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Technical Report