International audienceA classic problem in parallel computing is to take a high-level parallel program written, for example, in nested-parallel style with fork-join constructs and run it efficiently on a real machine. The problem could be considered solved in theory, but not in practice, because the overheads of creating and managing parallel threads can overwhelm their benefits. Developing efficient parallel codes therefore usually requires extensive tuning and optimizations to reduce parallelism just to a point where the overheads become acceptable.In this paper, we present a scheduling technique that delivers provably efficient results for arbitrary nested-parallel programs, without the tuning needed for controlling parallelism overheads...
This paper presents a complete framework for the parallelization of nested loops by applying tiling ...
this document are those of the author and should not be interpreted as representing the official pol...
Anytime algorithms offer a tradeoff between computation time and the quality of the result returned....
International audienceA classic problem in parallel computing is to take a high-level parallel progr...
Many of today's high level parallel languages support dynamic, fine-grained parallelism. These ...
Scheduling problems are essential for decision making in many academic disciplines, including operat...
Many of today's high level parallel languages support dynamic, fine-grained parallelism. These ...
Automatic partitioning, scheduling and code generation are of major importance in the development of...
We study the problem of executing parallel programs, in particular Cilk programs, on a collection of...
International audienceOver the past decade, many programming languages and systems for parallel-comp...
1. INTRODUCTION In this paper we study the problem of executing parallel programs, in particular Cil...
The running time and memory requirement of a parallel program with dynamic, lightweight threads depe...
Abstract The goal of high-level parallel programming models or languages is to facilitate the writin...
Nested parallelism is a well-known parallelization strategy to exploit irregular parallelism in HPC ...
We propose an algorithm for scheduling and allocation of parallel programs to message-passing archit...
This paper presents a complete framework for the parallelization of nested loops by applying tiling ...
this document are those of the author and should not be interpreted as representing the official pol...
Anytime algorithms offer a tradeoff between computation time and the quality of the result returned....
International audienceA classic problem in parallel computing is to take a high-level parallel progr...
Many of today's high level parallel languages support dynamic, fine-grained parallelism. These ...
Scheduling problems are essential for decision making in many academic disciplines, including operat...
Many of today's high level parallel languages support dynamic, fine-grained parallelism. These ...
Automatic partitioning, scheduling and code generation are of major importance in the development of...
We study the problem of executing parallel programs, in particular Cilk programs, on a collection of...
International audienceOver the past decade, many programming languages and systems for parallel-comp...
1. INTRODUCTION In this paper we study the problem of executing parallel programs, in particular Cil...
The running time and memory requirement of a parallel program with dynamic, lightweight threads depe...
Abstract The goal of high-level parallel programming models or languages is to facilitate the writin...
Nested parallelism is a well-known parallelization strategy to exploit irregular parallelism in HPC ...
We propose an algorithm for scheduling and allocation of parallel programs to message-passing archit...
This paper presents a complete framework for the parallelization of nested loops by applying tiling ...
this document are those of the author and should not be interpreted as representing the official pol...
Anytime algorithms offer a tradeoff between computation time and the quality of the result returned....