OpenMP [13] is the dominant programming model for shared-memory parallelism in C, C++ and Fortran due to its easy-to-use directive-based style, portability and broad support by compiler vendors. Similar characteristics are needed for a programming model for devices such as GPUs and DSPs that are gaining popularity to accelerate compute-intensive application regions. This paper presents extensions to OpenMP that provide that programming model. Our results demonstrate that a high-level programming model can provide accelerated performance comparable to hand-coded implementations in CUDA
Graphics Processing Units (GPU) have been widely adopted to accelerate the execution of HPC workload...
With the introduction of more powerful and massively parallel embedded processors, embedded systems ...
Accelerated computing is becoming more diverse as new vendors and architectures come into play. Alth...
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...
With the increasing prevalence of multicore processors, shared-memory programming models are essenti...
Abstract. A recent trend in mainstream computer nodes is the com-bined use of general-purpose multic...
In an ideal world, scientific applications would be expressed as high-level compositions of abstract...
Heterogeneous computing is increasingly being used in a diversity of computing systems, ranging from...
In this paper, we present OMPSs, a programming model based on OpenMP and StarSs, that can also incor...
OpenMP is an Application Programming Interface (API) widely accepted as a standard for high-level sh...
OpenMP enables productive software development that targets shared-memory general purpose systems. H...
CUDA and OpenCL are the most widely used programming models to exploit hardware accelerators. Both p...
OpenMP has established itself as the de facto standard for parallel programming on shared-memory pla...
Today’s High Performance Computing architectures exhibit significant compute power within each node ...
Graphics Processing Units (GPU) have been widely adopted to accelerate the execution of HPC workload...
With the introduction of more powerful and massively parallel embedded processors, embedded systems ...
Accelerated computing is becoming more diverse as new vendors and architectures come into play. Alth...
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...
With the increasing prevalence of multicore processors, shared-memory programming models are essenti...
Abstract. A recent trend in mainstream computer nodes is the com-bined use of general-purpose multic...
In an ideal world, scientific applications would be expressed as high-level compositions of abstract...
Heterogeneous computing is increasingly being used in a diversity of computing systems, ranging from...
In this paper, we present OMPSs, a programming model based on OpenMP and StarSs, that can also incor...
OpenMP is an Application Programming Interface (API) widely accepted as a standard for high-level sh...
OpenMP enables productive software development that targets shared-memory general purpose systems. H...
CUDA and OpenCL are the most widely used programming models to exploit hardware accelerators. Both p...
OpenMP has established itself as the de facto standard for parallel programming on shared-memory pla...
Today’s High Performance Computing architectures exhibit significant compute power within each node ...
Graphics Processing Units (GPU) have been widely adopted to accelerate the execution of HPC workload...
With the introduction of more powerful and massively parallel embedded processors, embedded systems ...
Accelerated computing is becoming more diverse as new vendors and architectures come into play. Alth...