Add to ORKGVarious tasks can run efficiently in parallel on current processor architectures. However, writing software to coordinate workflow between tasks is a challenge. In this paper, three task parallel paradigms are evaluated. Two are iterator-based, namely lightweight Tasks, which encompass little overhead, and Futures providing support for continuations. The third paradigm, Reactive programming is based on observers. In a case study, based on processing data streams in an embedded system, we evaluate these paradigms on efficiency, expressiveness and composability.status: publishe
Abstract. Programming paradigms are designed to express algorithms elegantly and efficiently. There ...
The shift toward multicore processors has transformed the software and hardware landscape in the las...
Parallel computing is notoriously challenging due to the difficulty in developing correct and effici...
Various tasks can run efficiently in parallel on current processor architectures. However, writing s...
Task-based programming models for shared memory -- such as Cilk Plus and OpenMP 3 -- are well establ...
It has become common knowledge that parallel programming is needed for scientific applications, part...
Parallel task-based programming models like OpenMP support the declaration of task data dependences....
The larger flexibility that task parallelism offers with respect to data parallelism comes at the co...
Task-based programming models for shared memory—such as Cilk Plus and OpenMP 3—are well established ...
International audienceTask-based paradigm models can be an alternative to MPI. The user defines atom...
Challenges introduced by highly hybrid many-cores architectures have a lasting impact on the portabi...
Task-based programming models for shared memory -- such as Cilk Plus and OpenMP 3 -- are well establ...
Parallel programming on SMP and multi-core architectures is hard. In this paper we present a program...
none5Current embedded computing architectures are moving to many-core concepts in order to sustain e...
Today’s processors exploit the fine grain data parallelism that exists in many applications via ILP ...
Abstract. Programming paradigms are designed to express algorithms elegantly and efficiently. There ...
The shift toward multicore processors has transformed the software and hardware landscape in the las...
Parallel computing is notoriously challenging due to the difficulty in developing correct and effici...
Various tasks can run efficiently in parallel on current processor architectures. However, writing s...
Task-based programming models for shared memory -- such as Cilk Plus and OpenMP 3 -- are well establ...
It has become common knowledge that parallel programming is needed for scientific applications, part...
Parallel task-based programming models like OpenMP support the declaration of task data dependences....
The larger flexibility that task parallelism offers with respect to data parallelism comes at the co...
Task-based programming models for shared memory—such as Cilk Plus and OpenMP 3—are well established ...
International audienceTask-based paradigm models can be an alternative to MPI. The user defines atom...
Challenges introduced by highly hybrid many-cores architectures have a lasting impact on the portabi...
Task-based programming models for shared memory -- such as Cilk Plus and OpenMP 3 -- are well establ...
Parallel programming on SMP and multi-core architectures is hard. In this paper we present a program...
none5Current embedded computing architectures are moving to many-core concepts in order to sustain e...
Today’s processors exploit the fine grain data parallelism that exists in many applications via ILP ...
Abstract. Programming paradigms are designed to express algorithms elegantly and efficiently. There ...
The shift toward multicore processors has transformed the software and hardware landscape in the las...
Parallel computing is notoriously challenging due to the difficulty in developing correct and effici...