A highly parallel implementation of k-means for multithreaded architecture

Authors:
Patrick Mackey;John Feo;Pak Chung Wong;Yousu Chen
Affiliations:
Researcher at Pacific Northwest National Laboratory;Chief Scientist at Pacific Northwest National Laboratory;Chief Scientist at Pacific Northwest National Laboratory;Senior Research Engineer at Pacific Northwest National Laboratory
Venue:
Proceedings of the 19th High Performance Computing Symposia
Year:
2011

Citing 4
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Abstract

We present a parallel implementation of the popular k-means clustering algorithm for massively multithreaded computer systems, as well as a parallelized version of the KKZ seed selection algorithm. We demonstrate that as system size increases, sequential seed selection can become a bottleneck. We also present an early attempt at parallelizing k-means that highlights critical performance issues when programming massively multithreaded systems. For our case studies, we used data collected from electric power simulations and run on the Cray XMT.