Sampling is a widely used technique to increase efficiency in database and data mining applications operating on large dataset. In this paper we present a scalable sampling imple...
— As network infrastructures with 10 Gb/s bandwidth and beyond have become pervasive and as cost advantages of large commodity-machine clusters continue to increase, research and...
Philip Werner Frey, Romulo Goncalves, Martin L. Ke...
Distributed-system observation tools require an efficient data structure to store and query the partial-order of execution. Such data structures typically use vector timestamps to...
A metascalable (or “design once, scale on new architectures”) parallel computing framework has been developed for large spatiotemporal-scale atomistic simulations of materials...
Ken-ichi Nomura, Richard Seymour, Weiqiang Wang, H...
Regression problems on massive data sets are ubiquitous in many application domains including the Internet, earth and space sciences, and finances. In many cases, regression algori...