World Scientific
  • Search
Skip main navigation

Cookies Notification

We use cookies on this site to enhance your user experience. By continuing to browse the site, you consent to the use of our cookies. Learn More
×
Our website is made possible by displaying certain online content using javascript.
In order to view the full content, please disable your ad blocker or whitelist our website www.worldscientific.com.

System Upgrade on Tue, Oct 25th, 2022 at 2am (EDT)

Existing users will be able to log into the site and access content. However, E-commerce and registration of new users may not be available for up to 12 hours.
For online purchase, please visit us again. Contact us at [email protected] for any enquiries.
Special Issue on Clusters, Clouds, and Data for Scientific Computing; Guest Editors: J. Dongarra & B. TourancheauNo Access

ROBUST SCALABLE VISUALIZED CLUSTERING IN VECTOR AND NON VECTOR SEMI-METRIC SPACES

    We describe an approach to data analytics on large systems using a suite of robust parallel algorithms running on both clouds and HPC systems. We apply this to cases where the data is defined in a vector space and when only pairwise distances between points are defined. We introduce improvements to known algorithms for functionality, features and performance but review state of the art as this is not broadly familiar. Visualization is valuable for steering complex analytics and we discuss it for both the non vector semi-metric case and for clustering high dimension vector spaces. We exploit deterministic annealing which is heuristic but has clear general principles that can give reasonably fast robust algorithms. We apply methods to several life sciences applications.