Large-scale scientific and engineering computation problems are usually complex and
consequently the development of parallel programs for solving these problems is a difficult …

Context: Multi-core architectures are becoming increasingly ubiquitous and software
professionals are seeking to leverage the capabilities of distributed-memory architectures …

Taco (Topologies and Collections) is a template based object platform for cluster
architectures, that provides the flavour of distributed data-parallel programming based on …

Parallel cluster architectures are an effective way to build high-performance computer
systems at a moderate price. Consequently, clusters will become very attractive to parallel …

Collective operations on distributed data sets foster a high-level data-parallel programming
style that eases many aspects of parallel programming significantly. In this paper we …

In the paper, we present first experimental results of a parallel implementation for a
simulated annealing-based heuristic. The heuristic has been developed for job shop …

High-level data-parallel programming with distributed object sets eases many aspects of
parallel programming. In this paper we describe the design and implementation of Taco, a …

TACO is a template library that implements higher-order parallel operations on distributed
object sets by means of reusable topology classes and C++ function templates. In this paper …

This paper presents an object-oriented approach to a high-level programming language for
parallel scientific computing and its realization by the compilation and runtime system …

TACO (Topologies and Collections) is a template library that introduces the flavour of
distributed data parallel processing by means of reusable topology classes and C++ …