High performance data clustering: a comparative analysis of performance for GPU, RASC, MPI, and OpenMP implementations

Luobin Yang, Steve C. Chiu, Wei-Keng Liao, Michael A. Thomas
2013 Journal of Supercomputing  
Compared to Beowulf clusters and shared-memory machines, GPU and FPGA are emerging alternative architectures that provide massive parallelism and great computational capabilities. These architectures can be utilized to run compute-intensive algorithms to analyze ever-enlarging datasets and provide scalability. In this paper, we present four implementations of K-means data clustering algorithm for different high performance computing platforms. These four implementations include a CUDA
more » ... tion for GPUs, a Mitrion C implementation for FPGAs, an MPI implementation for Beowulf compute clusters, and an OpenMP implementation for shared-memory machines. The comparative analyses of the cost of each platform, difficulty level of programming for each platform, and the performance of each implementation are presented.
doi:10.1007/s11227-013-0906-y pmid:25309040 pmcid:PMC4189017 fatcat:fy4wccng2rhongg52ylgrfpxsa