Abstract—The paper presents X-KAAPI, a compact runtime for multicore architectures that brings multi parallel paradigms (parallel independent loops, fork-join tasks and dataflow tasks) in a unified framework without performance penalty. Comparisons on independent loops with OpenMP and on dense linear algebra with QUARK/PLASMA confirm our design decisions. Applied to EUROPLEXUS, an industrial simulation code for fast transient dynamics, we show that X-KAAPI achieves high speedups on mul-ticore architectures by efficiently parallelizing both independent loops and dataflow tasks. I
International audienceThe shared memory architecture of multicore CPUs provides HEP developers with ...
Data parallel operations are widely used in game, multimedia, physics and data-intensive and scienti...
Making the best use of modern computational resources for distributed appli-cations requires expert ...
International audienceThe paper presents X-Kaapi, a compact runtime for multicore architec- tures th...
International audienceMost recent HPC platforms have heterogeneous nodes composed of multi-core CPUs...
International audienceTo efficiently exploit high performance computing platforms, applications curr...
The alpaka library defines and implements an abstract hierarchical redundant parallelism model. This...
International audienceIn this paper, we focus on a distributed and parallel programming paradigm for...
The shared memory architecture of multicore CPUs provides HENP developers with the opportunity to re...
eScience applications need to use distributed Grid environments where each component is an individua...
With the appearance of the heterogeneous platform OpenPower,many-core accelerator devices have been ...
Abstract—This paper presents preliminary performance com-parisons of parallel applications developed...
In this thesis, we propose to study the issues of task parallelism with data dependencies on multico...
SkePU (Skeleton Programming Framework for Multi-core CPU and Multi-GPU Systems) is a parallel comput...
In the last few years, the traditional ways to keep the increase of hardware performance at the rate...
International audienceThe shared memory architecture of multicore CPUs provides HEP developers with ...
Data parallel operations are widely used in game, multimedia, physics and data-intensive and scienti...
Making the best use of modern computational resources for distributed appli-cations requires expert ...
International audienceThe paper presents X-Kaapi, a compact runtime for multicore architec- tures th...
International audienceMost recent HPC platforms have heterogeneous nodes composed of multi-core CPUs...
International audienceTo efficiently exploit high performance computing platforms, applications curr...
The alpaka library defines and implements an abstract hierarchical redundant parallelism model. This...
International audienceIn this paper, we focus on a distributed and parallel programming paradigm for...
The shared memory architecture of multicore CPUs provides HENP developers with the opportunity to re...
eScience applications need to use distributed Grid environments where each component is an individua...
With the appearance of the heterogeneous platform OpenPower,many-core accelerator devices have been ...
Abstract—This paper presents preliminary performance com-parisons of parallel applications developed...
In this thesis, we propose to study the issues of task parallelism with data dependencies on multico...
SkePU (Skeleton Programming Framework for Multi-core CPU and Multi-GPU Systems) is a parallel comput...
In the last few years, the traditional ways to keep the increase of hardware performance at the rate...
International audienceThe shared memory architecture of multicore CPUs provides HEP developers with ...
Data parallel operations are widely used in game, multimedia, physics and data-intensive and scienti...
Making the best use of modern computational resources for distributed appli-cations requires expert ...