: Many classification problems involve high dimensional inputs and a large number of classes. Multiclassifier fusion approaches to such difficult problems typically centre around s...
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...
Parallel programming is elusive. The relative performance of di erent parallel implementations varies with machine architecture, system and problem size. How to compare di erent i...
The GCA (Global Cellular Automata) model consists of a collection of cells which change their states synchronously depending on the states of their neighbors like in the classical...
Transactional Memory (TM) is a promising technique that simplifies parallel programming for shared-memory applications. To date, most TM systems have been designed to efficientl...