Parallel and Distributed Association Mining: A Survey
IEEE Concurrency
The potential of the cell processor for scientific computing
Proceedings of the 3rd conference on Computing frontiers
Introduction to the cell multiprocessor
IBM Journal of Research and Development - POWER5 and packaging
FFTC: fastest Fourier transform for the IBM cell broadband engine
HiPC'07 Proceedings of the 14th international conference on High performance computing
A Parallel Point Matching Algorithm for Landmark Based Image Registration Using Multicore Platform
Euro-Par '09 Proceedings of the 15th International Euro-Par Conference on Parallel Processing
Interactive data mining on a CBEA cluster
HPCS'09 Proceedings of the 23rd international conference on High Performance Computing Systems and Applications
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The Cell Broadband Engine (CBE) is a new heterogeneous multi-core processor from IBM, Sony and Toshiba, and provides the potential to achieve an impressive level of performance for data mining algorithms. In this paper, we describe our implementation of three important classes of data mining algorithms: clustering (k-Means), classification (RBF network), and association rule mining (Apriori) on the CBE. We explain our parallelization methodology and describe the exploitation of thread- and data-level parallelism in each of the three algorithms. Finally we present experimental results on the Cell hardware, where we could achieve a high performance of up to 10 GFLOP/s and a speedup of up to 40.