4,933 research outputs found
Partition Around Medoids Clustering on the Intel Xeon Phi Many-Core Coprocessor
Abstract. The paper touches upon the problem of implementation Partition Around Medoids (PAM) clustering algorithm for the Intel Many Integrated Core architecture. PAM is a form of well-known k-Medoids clustering algorithm and is applied in various subject domains, e.g. bioinformatics, text analysis, intelligent transportation systems, etc. An optimized version of PAM for the Intel Xeon Phi coprocessor is introduced where OpenMP parallelizing technology, loop vectorization, tiling technique and efficient distance matrix computation for Euclidean metric are used. Experimental results for different data sets confirm the efficiency of the proposed algorithm
Viewpoints: A high-performance high-dimensional exploratory data analysis tool
Scientific data sets continue to increase in both size and complexity. In the
past, dedicated graphics systems at supercomputing centers were required to
visualize large data sets, but as the price of commodity graphics hardware has
dropped and its capability has increased, it is now possible, in principle, to
view large complex data sets on a single workstation. To do this in practice,
an investigator will need software that is written to take advantage of the
relevant graphics hardware. The Viewpoints visualization package described
herein is an example of such software. Viewpoints is an interactive tool for
exploratory visual analysis of large, high-dimensional (multivariate) data. It
leverages the capabilities of modern graphics boards (GPUs) to run on a single
workstation or laptop. Viewpoints is minimalist: it attempts to do a small set
of useful things very well (or at least very quickly) in comparison with
similar packages today. Its basic feature set includes linked scatter plots
with brushing, dynamic histograms, normalization and outlier detection/removal.
Viewpoints was originally designed for astrophysicists, but it has since been
used in a variety of fields that range from astronomy, quantum chemistry, fluid
dynamics, machine learning, bioinformatics, and finance to information
technology server log mining. In this article, we describe the Viewpoints
package and show examples of its usage.Comment: 18 pages, 3 figures, PASP in press, this version corresponds more
closely to that to be publishe
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