Optimal multi-step k-nearest neighbor search
SIGMOD '98 Proceedings of the 1998 ACM SIGMOD international conference on Management of data
Accelerating exact k-means algorithms with geometric reasoning
KDD '99 Proceedings of the fifth ACM SIGKDD international conference on Knowledge discovery and data mining
Data mining: concepts and techniques
Data mining: concepts and techniques
High-dimensional nearest neighbor search with remote data centers
Knowledge and Information Systems
High Dimensional Similarity Search With Space Filling Curves
Proceedings of the 17th International Conference on Data Engineering
Mining distance-based outliers in near linear time with randomization and a simple pruning rule
Proceedings of the ninth ACM SIGKDD international conference on Knowledge discovery and data mining
The potential of the cell processor for scientific computing
Proceedings of the 3rd conference on Computing frontiers
CellSort: high performance sorting on the cell processor
VLDB '07 Proceedings of the 33rd international conference on Very large data bases
Implementation of a wide-angle lens distortion correction algorithm on the cell broadband engine
Proceedings of the 23rd international conference on Supercomputing
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
G-means improved for cell BE environment
Facing the multicore-challenge
G-means improved for cell BE environment
Facing the multicore-challenge
Interactive data mining on a CBEA cluster
HPCS'09 Proceedings of the 23rd international conference on High Performance Computing Systems and Applications
Parallelization of pagerank on multicore processors
ICDCIT'12 Proceedings of the 8th international conference on Distributed Computing and Internet Technology
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The STI Cell Broadband Engine architecture represents an interesting design point along the spectrum of chipsets with multiple processing elements. In this article we investigate key mining tasks such as clustering, classification, anomaly detection and PageRank on the Cell along the axes of performance, programming complexity and algorithm design. As part of our comparative analysis we juxtapose these algorithms with similar ones implemented on state-of-the-art uniprocessor and multicore architectures. For the workloads that are more oating point intensive, and where data is accessed in a streaming fashion the Cell processor is up to seven times faster than competing technologies, when the underlying algorithm uses the hardware efficiently. However, when required to write in a non-streaming fashion, as with PageRank, the processor is up to twenty times slower than competing processors. An outcome of our benchmark study, beyond the results on these particular algorithms is that we answer several higher level questions, which are designed to provide a fast and reliable estimate to application designers for how well other workloads will scale on the Cell.