Implicit Decomposition for Write-Efficient Connectivity Algorithms
Name
1710.02637.pdf
Description
Submitted version
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658.14 KB
Format
Adobe PDF
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Author(s)
Ben-David, Naama
Blelloch, Guy
Fineman, Jeremy
Gibbons, Phillip
Gu, Yan
McGuffey, Charles
Shun, Julian
Date Issued
2018
Journal
Proceedings - 2018 IEEE 32nd International Parallel and Distributed Processing Symposium, IPDPS 2018
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Version
Original manuscript
Abstract
© 2018 IEEE. The future of main memory appears to lie in the direction of new technologies that provide strong capacity-To-performance ratios, but have write operations that are much more expensive than reads in terms of latency, bandwidth, and energy. Motivated by this trend, we propose sequential and parallel algorithms to solve graph connectivity problems using significantly fewer writes than conventional algorithms. Our primary algorithmic tool is the construction of an o(n)-sized implicit decomposition of a bounded-degree graph G on n nodes, which combined with read-only access to G enables fast answers to connectivity and biconnectivity queries on G. The construction breaks the linear-write 'barrier', resulting in costs that are asymptotically lower than conventional algorithms while adding only a modest cost to querying time. For general non-sparse graphs on m edges, we also provide the first o(m) writes and O(m) operations parallel algorithms for connectivity and biconnectivity. These algorithms provide insight into how applications can efficiently process computations on large graphs in systems with read-write asymmetry.
MIT Department
Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory
Terms of Use
Creative Commons Attribution-Noncommercial-Share Alike
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DOI of Published Version
https://doi.org/10.1109/IPDPS.2018.00081
