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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Vishnu, A. Agarwal, K. |
| Copyright Year | 2015 |
| Description | Author affiliation: Adv. Comput., Math. & Data Div., Pacific Northwest Nat. Lab., Richland, WA, USA (Vishnu, A.; Agarwal, K.) |
| Abstract | In this paper, we propose a work-stealing runtime - Library for Work Stealing (LibWS) - using MPI one-sided model for designing scalable FP-Growth - defacto frequent pattern mining algorithm - on large scale systems. LibWS provides locality efficient and highly scalable work-stealing techniques for load balancing on a variety of data distributions. We also propose a novel communication algorithm for FP-growth data exchange phase, which reduces the communication complexity from state-of-the-art θ(p) to θ(f + p/f), for p processes and f frequent attributed-ids. FP-Growth is implemented using LibWS and evaluated on several work distributions and support counts. An experimental evaluation of the FP-Growth on LibWS using 4096 processes on an InfiniBand Cluster demonstrates excellent efficiency for several work distributions (91% efficiency for Power-law and 93% for Poisson). The proposed distributed FPTree merging algorithm provides 38x communication speedup on 4096 cores. |
| Starting Page | 138 |
| Ending Page | 147 |
| File Size | 1571056 |
| Page Count | 10 |
| File Format | |
| ISBN | 9781467365987 |
| DOI | 10.1109/CLUSTER.2015.30 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2015-09-08 |
| Publisher Place | USA |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Algorithm design and analysis Merging Complexity theory Runtime Data mining Clustering algorithms Synchronization Work Stealing Frequent Pattern Mining MPI |
| Content Type | Text |
| Resource Type | Article |
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