Add to ORKGCollective 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 describe how higher-order collective operations on dis-tributed object sets can be introduced in a structured way by means of reusable topology classes and C++ templates.
Abstract. Distributed Objects (DO) as de ned by OMG's CORBA ar-chitecture provide a model for o...
Our goal is to apply the software engineering advantages of object-oriented programming to the raw p...
The shared data-object model is designed to ease the implementation of parallel applications on loos...
jon @ rst.gmd.de Abstract. Collective operations on multiple distributed objects are a powerful mean...
In parallel object-oriented languages it is hard to elegantly express efficient data-parallel operat...
TACO (Topologies and Collections) is a template-based object platform that strongly supports distrib...
: This paper describes the collective object, a new abstraction providing support for collective op...
TACO (Topologies and Collections) is a template library that introduces the flavour of distributed d...
TACO (Topologies and Collections) is a template based object platform for cluster architectures, tha...
jon @ rst.gmd.de Abstract. Multicasts are a powerful means to implement coordinated operations on di...
Collective operations are common features of parallel programming models that are frequently used in...
The shared data-object model is designed to ease the implementation of parallel applications on loos...
AbstractWe propose a set-theoretic model for parallelism. The model is based on separate distributio...
AbstractA framework is presented for designing parallel programming languages whose semantics is fun...
A parallel program archetype aids in the development of reliable, efficient parallel applications wi...
Abstract. Distributed Objects (DO) as de ned by OMG's CORBA ar-chitecture provide a model for o...
Our goal is to apply the software engineering advantages of object-oriented programming to the raw p...
The shared data-object model is designed to ease the implementation of parallel applications on loos...
jon @ rst.gmd.de Abstract. Collective operations on multiple distributed objects are a powerful mean...
In parallel object-oriented languages it is hard to elegantly express efficient data-parallel operat...
TACO (Topologies and Collections) is a template-based object platform that strongly supports distrib...
: This paper describes the collective object, a new abstraction providing support for collective op...
TACO (Topologies and Collections) is a template library that introduces the flavour of distributed d...
TACO (Topologies and Collections) is a template based object platform for cluster architectures, tha...
jon @ rst.gmd.de Abstract. Multicasts are a powerful means to implement coordinated operations on di...
Collective operations are common features of parallel programming models that are frequently used in...
The shared data-object model is designed to ease the implementation of parallel applications on loos...
AbstractWe propose a set-theoretic model for parallelism. The model is based on separate distributio...
AbstractA framework is presented for designing parallel programming languages whose semantics is fun...
A parallel program archetype aids in the development of reliable, efficient parallel applications wi...
Abstract. Distributed Objects (DO) as de ned by OMG's CORBA ar-chitecture provide a model for o...
Our goal is to apply the software engineering advantages of object-oriented programming to the raw p...
The shared data-object model is designed to ease the implementation of parallel applications on loos...