A Highly Parallel Implementation of K-Means for Multithreaded Architecture

Conference · Wed Apr 06 00:00:00 EDT 2011

OSTI ID:1030877

Mackey, Patrick S; Feo, John T; Wong, Pak C; Chen, Yousu

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.

• Research Organization: Pacific Northwest National Lab. (PNNL), Richland, WA (United States). Environmental Molecular Sciences Lab. (EMSL)
• Sponsoring Organization: USDOE
• DOE Contract Number: AC05-76RL01830
• OSTI ID: 1030877
• Report Number(s): PNNL-SA-76703; 37300; 400470000; TRN: US201124%%508
• Resource Relation: Conference: Proceedings of the 19th High Performance Computing Symposia (HPC 2011): SCS Spring Simulation Multiconference (SpringSim 2011), April 3-7, 2011, Boston, MA
• Country of Publication: United States
• Language: English

Related Subjects

99 GENERAL AND MISCELLANEOUS//MATHEMATICS, COMPUTING, AND INFORMATION SCIENCE
ALGORITHMS
COMPUTER ARCHITECTURE
COMPUTERS
ELECTRIC POWER
IMPLEMENTATION
PERFORMANCE
PROGRAMMING
SEEDS
SIMULATION
Cray XMT
k-means
KKZ
HPC
clustering
Environmental Molecular Sciences Laboratory