: This paper presents a Data-Distributed Execution approach that exploits interation-level parallelism in loops operating over arrays. It performs data-dependency analysis, based o...
Abstract. As the disparity between processor and memory speed continues to widen, the exploitation of locality of reference in shared-memory multiprocessors becomes an increasingly...
We study the problem of classifying images into a given, pre-determined taxonomy. The task can be elegantly translated into the structured learning framework. Structured learning, ...
Symmetry in constraint problems can be exploited to greatly improve search performance. A form of symmetry that has been the subject of considerable research is value interchangeab...
ParaDisEO is a framework dedicated to the design of parallel and distributed metaheuristics including local search methods and evolutionary algorithms. This paper focuses on the la...