Francisco F. Rivera

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We extend a model of locality and the subsequent process of locality improvement previously developed for the case of sparse algebra codes in monoprocessors to the case of NUMA shared memory multiprocessors (SMPs). In particular the product of a sparse matrix by a dense vector (SpM/spl times/V) is studied. In the model, locality is established at run-time(More)
Pattern recognition methods based on the theory of fuzzy sets are tested for their ability to classify electron microscopy images of biological specimens. The concept of fuzzy sets was chosen for its ability to represent classes of objects that are vaguely described from the measured data. A number of partitional clustering algorithms and an extensive set(More)
This paper presents a new LogP-based model, called LoOgGP, which allows an accurate characterization of MPI applications based on microbenchmark measurements. This new model is an extension of LogP for long messages in which both overhead and gap parameters perform a linear dependency with message size. The LoOgGP model has been fully integrated into a(More)
19 The RBT approach also suggests other interesting avenues for work. Randomization appears to ooer new strategies for linear systems solution that are well-suited to high-performance computers. High-performance machines tend to favor algorithmic simplicity. The RBT trades naive time complexity (the number of`steps' performed by a sequential algorithm) for(More)
Principal component analysis is a classical multivariate technique. This is a basic tool in the eld of image processing. Due to the iterative performing and the high computational cost of this algorithms over conventional computers , they are good candidates for the pipeline processing. In this work we analyse this code from the vectorization approach and(More)