OpenACC

Résumé

OpenACC (pour Open Accelerators) est un standard de programmation pour le calcul parallèle développé par Cray, CAPS, Nvidia et . Ce standard est conçu pour permettre du calcul parallèle sur des systèmes hétérogènes CPU/GPU. Tout comme OpenMP, il est possible de rajouter des commandes dans du code source C, C++ et Fortran pour identifier des portions qui pourrait bénéficier d'une accélération, en utilisant des directives au compilateur. Comme en OpenMP 4.0 et suivant, le code peut être exécuté sur CPU et GPU. Les développeurs d'OpenACC ont également travaillé sur le standard d'OpenMP afin de créer une spécification commune permettant d'étendre OpenMP pour supporter de nouveaux types d’accélérateurs dans les prochaines versions d'OpenMP. Ces travaux ont abouti à un rapport technique incluant commentaires et discussions destinés à être débattus durant la conférence annuelle Supercomputing Conference à Salt Lake City en , afin de traiter le support des accélérateurs non-Nvidia par les

Source officielle

https://fr.wikipedia.org/wiki/OpenACC

À propos de ce résultat

Cette page est générée automatiquement et peut contenir des informations qui ne sont pas correctes, complètes, à jour ou pertinentes par rapport à votre recherche. Il en va de même pour toutes les autres pages de ce site. Veillez à vérifier les informations auprès des sources officielles de l'EPFL.

Publications associées (4)

Publications associées

Chargement

Personnes associées

Chargement

Unités associées

Chargement

Concepts associés (7)

Concepts associés

Chargement

Cours associés (4)

Cours associés

Chargement

Séances de cours associées (5)

Séances de cours associées

Chargement

, , , ,

We present a portable platform, called PIC_ENGINE, for accelerating Particle-In-Cell (PIC) codes on heterogeneous many-core architectures such as Graphic Processing Units (GPUs). The aim of this development is efficient simulations on future exascale systems by allowing different parallelization strategies depending on the application problem and the specific architecture. To this end, this platform contains the basic steps of the PIC algorithm and has been designed as a test bed for different algorithmic options and data structures. Among the architectures that this engine can explore, particular attention is given here to systems equipped with GPUs. The study demonstrates that our portable PIC implementation based on the OpenACC programming model can achieve performance closely matching theoretical predictions. Using the Cray XC30 system, Piz Daint, at the Swiss National Supercomputing Centre (CSCS), we show that PIC_ENGINE running on an NVIDIA Kepler K20X GPU can outperform the one on an Intel Sandy bridge 8-core CPU by a factor of 3.4.

Elsevier Science Bv2016

Chargement

On the Efficiency of OpenACC-aided GPU-Based FDTD Approach: Application to Lightning Electromagnetic Fields

Mohammad Azadifar, Hamidreza Karami

An open accelerator (OpenACC)-aided graphics processing unit (GPU)-based finite difference time domain (FDTD) method is presented for the first time for the 3D evaluation of lightning radiated electromagnetic fields along a complex terrain with arbitrary topography. The OpenACC directive-based programming model is used to enhance the computational performance, and the results are compared with those obtained by using a CPU-based model. It is shown that OpenACC GPUs can provide very accurate results, and they are more than 20 times faster than CPUs. The presented results support the use of OpenACC not only in relation to lightning electromagnetics problems, but also to large-scale realistic electromagnetic compatibility (EMC) applications in which computation time efficiency is a critical factor.

MDPI2020

Chargement

Hybrid OpenMP/MPI parallelization of the charge deposition step in the global gyrokinetic Particle-In-Cell code ORB5

Stephan Brunner, Claudio Gheller, Emmanuel Lanti, Noé Thomas Elie Ohana, Aaron Lewis Scheinberg, Laurent Villard

Gyrokinetic simulations are computationally extremely demanding due to the high dimensionality of the physical phase space and the interplay between plasma particles and electromagnetic fields. It is thus essential to make full use of the available numerical resources to be able to simulate more complex physical problems. With the aim of optimizing the gyrokinetic Particle-In-Cell code ORB5 towards exascale computing, a particle sorting method is implemented to increase data locality. Furthermore, different algorithms are used to improve vectorization, and the MPI parallelization is complemented with OpenMP. More specifically, we shall focus on the particle to grid operations involved in the PIC charge deposition step. The latter is critical to parallelize using a shared memory paradigm due to the scatter operations involved. We will present the different algorithms and parallelization schemes implemented in the ORB5 charge deposition step and how they affect the speedup compared to the base MPI case.

2017

Chargement