Parallel programming on SMP and multi-core architectures is hard. In this paper we present a programming model for those environments based on automatic function level parallelism that strives to be easy, flexible, portable, and performant. Its main trait is its ability to exploit task level parallelism by analyzing task dependencies at run time. We present the programming environment in the context of algorithms from several domains and pinpoint its benefits compared to other approaches. We discuss its execution model and its scheduler. Finally we analyze its performance and demonstrate that it offers reasonable performance without tuning, and that it can rival highly tuned libraries with minimal tuning effort.Peer Reviewe
Modern computer architectures expose an increasing number of parallel features supported by complex ...
Abstract. We present a framework for parallel programming. It consists of a distributed shared memor...
Tasking in OpenMP 3.0 has been conceived to handle the dynamic generation of unstructured parallelis...
Parallel programming on SMP and multi-core architectures is hard. In this paper we present a program...
The larger flexibility that task parallelism offers with respect to data parallelism comes at the co...
Dependency-aware task-based parallel programming models have proven to be successful for developing ...
Parallel task-based programming models like OpenMP support the declaration of task data dependences....
The emergence of multicore processors has increased the need for simple parallel programming models ...
The shift toward multicore processors has transformed the software and hardware landscape in the las...
This paper presents an automatic parallelization approach for handling complex task systems with hea...
Given the considerate amounts of research on task-based parallel programming models for maximizing p...
Thesis (Ph. D.)--University of Rochester. Dept. of Computer Science, 2012.Speculative parallelizatio...
It has become common knowledge that parallel programming is needed for scientific applications, part...
Parallel computing is notoriously challenging due to the difficulty in developing correct and effici...
The use of SMP architectures to manage tasks with real-time requirements is a matter of a great amou...
Modern computer architectures expose an increasing number of parallel features supported by complex ...
Abstract. We present a framework for parallel programming. It consists of a distributed shared memor...
Tasking in OpenMP 3.0 has been conceived to handle the dynamic generation of unstructured parallelis...
Parallel programming on SMP and multi-core architectures is hard. In this paper we present a program...
The larger flexibility that task parallelism offers with respect to data parallelism comes at the co...
Dependency-aware task-based parallel programming models have proven to be successful for developing ...
Parallel task-based programming models like OpenMP support the declaration of task data dependences....
The emergence of multicore processors has increased the need for simple parallel programming models ...
The shift toward multicore processors has transformed the software and hardware landscape in the las...
This paper presents an automatic parallelization approach for handling complex task systems with hea...
Given the considerate amounts of research on task-based parallel programming models for maximizing p...
Thesis (Ph. D.)--University of Rochester. Dept. of Computer Science, 2012.Speculative parallelizatio...
It has become common knowledge that parallel programming is needed for scientific applications, part...
Parallel computing is notoriously challenging due to the difficulty in developing correct and effici...
The use of SMP architectures to manage tasks with real-time requirements is a matter of a great amou...
Modern computer architectures expose an increasing number of parallel features supported by complex ...
Abstract. We present a framework for parallel programming. It consists of a distributed shared memor...
Tasking in OpenMP 3.0 has been conceived to handle the dynamic generation of unstructured parallelis...