MagPIe: MPI's collective communication operations for clustered wide area systems
Proceedings of the seventh ACM SIGPLAN symposium on Principles and practice of parallel programming
Examining Locally Varying Weights for Nearest Neighbor Algorithms
ICCBR '97 Proceedings of the Second International Conference on Case-Based Reasoning Research and Development
Distributed Computing in a Heterogeneous Computing Environment
Proceedings of the 5th European PVM/MPI Users' Group Meeting on Recent Advances in Parallel Virtual Machine and Message Passing Interface
A parallel learning algorithm for text classification
Proceedings of the eighth ACM SIGKDD international conference on Knowledge discovery and data mining
MPICH-G2: a Grid-enabled implementation of the Message Passing Interface
Journal of Parallel and Distributed Computing - Special issue on computational grids
Subspace clustering for high dimensional data: a review
ACM SIGKDD Explorations Newsletter - Special issue on learning from imbalanced datasets
Automated Variable Weighting in k-Means Type Clustering
IEEE Transactions on Pattern Analysis and Machine Intelligence
MACLAW: A modular approach for clustering with local attribute weighting
Pattern Recognition Letters - Special issue: Evolutionary computer vision and image understanding
P3: P2P-based middleware enabling transfer and aggregation of computational resources
CCGRID '05 Proceedings of the Fifth IEEE International Symposium on Cluster Computing and the Grid - Volume 01
Locally adaptive metrics for clustering high dimensional data
Data Mining and Knowledge Discovery
Grid'5000: A Large Scale and Highly Reconfigurable Grid Experimental Testbed
GRID '05 Proceedings of the 6th IEEE/ACM International Workshop on Grid Computing
GPC'07 Proceedings of the 2nd international conference on Advances in grid and pervasive computing
A peer-to-peer framework for robust execution of message passing parallel programs on grids
PVM/MPI'05 Proceedings of the 12th European PVM/MPI users' group conference on Recent Advances in Parallel Virtual Machine and Message Passing Interface
Survey of clustering algorithms
IEEE Transactions on Neural Networks
Comparison between two coevolutionary feature weighting algorithms in clustering
Pattern Recognition
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The goal of clustering is to identify subsets called clusters which usually correspond to objects that are more similar to each other than they are to objects from other clusters. We have proposed the MACLAW method, a cooperative coevolution algorithm for data clustering, which has shown good results (Blansché and Gançarski, Pattern Recognit. Lett. 27(11), 1299---1306, 2006). However the complexity of the algorithm increases rapidly with the number of clusters to find. We propose in this article a parallelization of MACLAW, based on a message-passing paradigm, as well as the analysis of the application performances with experiment results. We show that we reach near optimal speedups when searching for 16 clusters, a typical problem instance for which the sequential execution duration is an obstacle to the MACLAW method. Further, our approach is original because we use the P2P-MP1 grid middleware (Genaud and Rattanapoka, Lecture Notes in Comput. Sci., vol. 3666, pp. 276---284, 2005) which both provides the message passing library and infrastructure services to discover computing resources. We also put forward that the application can be tightly coupled with the middleware to make the parallel execution nearly transparent for the user.