Parallel computing has become the norm to gain performance in multicore and heterogeneous systems. Many programming models allow to exploit this parallelism with easy to use tools. In this work we focus on task-based programming models. The parallelism is expressed with pieces of work called tasks that have data dependencies among them, and therefore have to be executed in a certain order. However, tasks that don’t depend on any other running task can be executed in parallel
Task-based parallel programming models with explicit data dependencies, such as OmpSs, are gaining p...
Hardware heterogeneity is here to stay for high-performance computing. Large-scale systems are curre...
The increasing parallelism levels in modern computing systems has extolled the need for a holistic v...
© 2019 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for a...
Task-based programming models allow programmers to express applications as a collection of tasks wit...
Task-based programming models have gained a lot of attention for being able to explore high parallel...
Along with the popularity of multicore and manycore, task-based dataflow programming models obtain g...
© 2015 Elsevier B.V. All rights reserved. OmpSs is a programming model that provides a simple and po...
Task-based programming Task-based programming models such as OpenMP, Intel TBB and OmpSs are widely ...
Task Parallelism is a parallel programming model that provides code annotation constructs to outline...
Task-based programming models such as OpenMP, IntelTBB and OmpSs offer the possibility of expressing...
Distributed computing platforms are evolving to heterogeneous ecosystems with Clusters, Grids and Cl...
To help shrink the programmability-performance efficiency gap, we discuss that adaptive runtime syst...
As chip multi-processors (CMPs) are becoming more and more complex, software solutions such as paral...
Dynamic Task Scheduling is an enticing programming model aiming to ease the development of parallel ...
Task-based parallel programming models with explicit data dependencies, such as OmpSs, are gaining p...
Hardware heterogeneity is here to stay for high-performance computing. Large-scale systems are curre...
The increasing parallelism levels in modern computing systems has extolled the need for a holistic v...
© 2019 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for a...
Task-based programming models allow programmers to express applications as a collection of tasks wit...
Task-based programming models have gained a lot of attention for being able to explore high parallel...
Along with the popularity of multicore and manycore, task-based dataflow programming models obtain g...
© 2015 Elsevier B.V. All rights reserved. OmpSs is a programming model that provides a simple and po...
Task-based programming Task-based programming models such as OpenMP, Intel TBB and OmpSs are widely ...
Task Parallelism is a parallel programming model that provides code annotation constructs to outline...
Task-based programming models such as OpenMP, IntelTBB and OmpSs offer the possibility of expressing...
Distributed computing platforms are evolving to heterogeneous ecosystems with Clusters, Grids and Cl...
To help shrink the programmability-performance efficiency gap, we discuss that adaptive runtime syst...
As chip multi-processors (CMPs) are becoming more and more complex, software solutions such as paral...
Dynamic Task Scheduling is an enticing programming model aiming to ease the development of parallel ...
Task-based parallel programming models with explicit data dependencies, such as OmpSs, are gaining p...
Hardware heterogeneity is here to stay for high-performance computing. Large-scale systems are curre...
The increasing parallelism levels in modern computing systems has extolled the need for a holistic v...