This paper advances the state-of-the-art in programming models for exploiting task-level parallelism on heterogeneous many-core systems, presenting a number of extensions to the OpenMP language inspired in the StarSs programming model. The proposed extensions allow the programmer to write portable code easily for a number of different platforms, relieving him/her from developing the specific code to off-load tasks to the accelerators and the synchronization of tasks. Our results obtained from the StarSs instantiations for SMPs, theCell, and GPUs report reasonable parallel performance. However, the real impact of our approach in is the productivity gains it yields for the programmer.Postprint (published version
Heterogeneous supercomputers that incorporate computational ac-celerators such as GPUs are increasin...
Parallel task-based programming models like OpenMP support the declaration of task data dependences....
Abstract—OpenMP has been very successful in exploiting structured parallelism in applications. With ...
This paper advances the state-of-the-art in programming models for exploiting task-level parallelism...
This paper advances the state-of-the-art in programming models for exploiting task-level parallelism...
OpenMP [13] is the dominant programming model for shared-memory parallelism in C, C++ and Fortran du...
OpenMP has evolved recently towards expressing unstructured parallelism, targeting the parallelizati...
With the introduction of more powerful and massively parallel embedded processors, embedded systems ...
In this paper, we present OMPSs, a programming model based on OpenMP and StarSs, that can also incor...
The emergence of System-on-Chip (SOC) design shows the growing popularity of the integration of mult...
With the introduction of more powerful and massively parallel embedded processors, embedded systems ...
Multiprocessor systems-on-chip (MPSoC) are evolving into heterogeneous architectures based on one ho...
As chip manufacturing processes are getting ever closer to what is physically possible, the projecti...
Editors: Michael Klemm; Bronis R. de Supinski et al.International audienceHeterogeneous supercompute...
The use of GPU accelerators is becoming common in HPC platforms due to the their effective performan...
Heterogeneous supercomputers that incorporate computational ac-celerators such as GPUs are increasin...
Parallel task-based programming models like OpenMP support the declaration of task data dependences....
Abstract—OpenMP has been very successful in exploiting structured parallelism in applications. With ...
This paper advances the state-of-the-art in programming models for exploiting task-level parallelism...
This paper advances the state-of-the-art in programming models for exploiting task-level parallelism...
OpenMP [13] is the dominant programming model for shared-memory parallelism in C, C++ and Fortran du...
OpenMP has evolved recently towards expressing unstructured parallelism, targeting the parallelizati...
With the introduction of more powerful and massively parallel embedded processors, embedded systems ...
In this paper, we present OMPSs, a programming model based on OpenMP and StarSs, that can also incor...
The emergence of System-on-Chip (SOC) design shows the growing popularity of the integration of mult...
With the introduction of more powerful and massively parallel embedded processors, embedded systems ...
Multiprocessor systems-on-chip (MPSoC) are evolving into heterogeneous architectures based on one ho...
As chip manufacturing processes are getting ever closer to what is physically possible, the projecti...
Editors: Michael Klemm; Bronis R. de Supinski et al.International audienceHeterogeneous supercompute...
The use of GPU accelerators is becoming common in HPC platforms due to the their effective performan...
Heterogeneous supercomputers that incorporate computational ac-celerators such as GPUs are increasin...
Parallel task-based programming models like OpenMP support the declaration of task data dependences....
Abstract—OpenMP has been very successful in exploiting structured parallelism in applications. With ...