… The process of architectural convergence which was described above brings with it the
hope that we can, over the next few years, establish scalable parallel computing as the normal …

Recent advances in data-intensive computing for science discovery are fueling a dramatic
growth in the use of data-intensive iterative computations. The utility computing model …

… Over the last few years, a number of important research activities in algorithms and architectures
have been pursued as part of this new approach to scalable parallel computing. In this …

… He is currently an associate professor in the Department of Computer Sciences at the
University of Minnesota, His current research interests include scalable parallel computing and …

As the gap between processor and memory speeds widens, system designers will inevitably
incorporate increasingly deep memory hierarchies to maintain the balance between …

Massively parallel computers, built of standard RISC components, take an increasing share
of the supercomputing market, and are expected to replace most conventional vector …

As multi-core personal computers (PC) have become popular and widely available for various
computation tasks, developing parallel computing methods are imperative for taking the …

… His research interests include scalable parallel computing, artificial intelligence, object
oriented databases. and object based distributed computing. He is the author ofover 25 research …

This paper presents a parallel computing Smoothed Particle Hydrodynamics (SPH)
framework for geophysical granular flows scalable on large CPU clusters. The framework is …

… In the domain of scalable parallel computing (from a dozen of cores to potentially a dozen
of thousands or more), SyDPaCC [31, 32] is a framework for Coq that supports the systematic …