articleFeb 23, 2013Closed access
Ligra
Indexed incrossref
Abstract
There has been significant recent interest in parallel frameworks for processing graphs due to their applicability in studying social networks, the Web graph, networks in biology, and unstructured meshes in scientific simulation. Due to the desire to process large graphs, these systems have emphasized the ability to run on distributed memory machines. Today, however, a single multicore server can support more than a terabyte of memory, which can fit graphs with tens or even hundreds of billions of edges. Furthermore, for graph algorithms, shared-memory multicores are generally significantly more efficient on a per core, per dollar, and per joule basis than distributed memory systems, and shared-memory…
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Authors
2Topics & keywords
Topics
Keywords
- Computer science
- Terabyte
- Parallel computing
- Out-of-core algorithm
- Distributed memory
- Theoretical computer science
- Distributed computing
- Graph
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