The DOI matches its Crossref record; 162 of the 162 references it cites were found in a registry or an index.
Ligra: a lightweight graph processing framework for shared memory
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 algorithms tend to be simpler than their distributed counterparts.
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Roy, A., Mihailovic, I., & Zwaenepoel, W. (2013) · Proceedings of the Twenty-Fourth ACM Symposium on Operating Systems Principles · doi:10.1145/2517349.2522740 · Cited by 673
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Processing data where it makes sense: Enabling in-memory computation
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Metadata
- Authors
- Shun, J., & Blelloch, G. E.
- Venue
- Proceedings of the 18th ACM SIGPLAN symposium on Principles and practice of parallel programming
- Publisher
- ACM
- Published
- 2013-02-23
- Pages
- 135-146
- OpenAlex
- W2000041758
- Cited by
- 798
- References
- 162
- FWCI
- 30.72
- Type
- conference paper
- Language
- en
- Open access
- closed
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- Shun, J., & Blelloch, G. E. (2013). Ligra: a lightweight graph processing framework for shared memory. Proceedings of the 18th ACM SIGPLAN symposium on Principles and practice of parallel programming. https://doi.org/10.1145/2442516.2442530
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
