David Couturier et Michel Dagenais
Article de revue (2015)
Document en libre accès dans PolyPublie et chez l'éditeur officiel |
|
Libre accès au plein texte de ce document Version officielle de l'éditeur Conditions d'utilisation: Creative Commons: Attribution (CC BY) Télécharger (1MB) |
Abstract
As computation schemes evolve and many new tools become available to programmers to enhance the performance of their applications, many programmers started to look towards highly parallel platforms such as Graphical Processing Unit (GPU). Offloading computations that can take advantage of the architecture of the GPU is a technique that has proven fruitful in recent years. This technology enhances the speed and responsiveness of applications. Also, as a side effect, it reduces the power requirements for those applications and therefore extends portable devices battery life and helps computing clusters to run more power efficiently. Many performance analysis tools such as LTTng, strace and SystemTap already allow Central Processing Unit (CPU) tracing and help programmers to use CPU resources more efficiently. On the GPU side, different tools such as Nvidia's Nsight, AMD's CodeXL, and third party TAU and VampirTrace allow tracing Application Programming Interface (API) calls and OpenCL kernel execution. These tools are useful but are completely separate, and none of them allow a unified CPU-GPU tracing experience. We propose an extension to the existing scalable and highly efficient LTTng tracing platform to allow unified tracing of GPU along with CPU's full tracing capabilities.
Sujet(s): |
2700 Technologie de l'information > 2700 Technologie de l'information 2700 Technologie de l'information > 2706 Génie logiciel 2700 Technologie de l'information > 2715 Optimisation |
---|---|
Département: | Département de génie informatique et génie logiciel |
Organismes subventionnaires: | CRSNG/NSERC, Ericsson, EfficiOS |
URL de PolyPublie: | https://publications.polymtl.ca/4834/ |
Titre de la revue: | Advances in Software Engineering (vol. 2015) |
Maison d'édition: | Hindawi |
DOI: | 10.1155/2015/940628 |
URL officielle: | https://doi.org/10.1155/2015/940628 |
Date du dépôt: | 16 août 2021 13:22 |
Dernière modification: | 11 avr. 2024 03:04 |
Citer en APA 7: | Couturier, D., & Dagenais, M. (2015). LTTng CLUST: A system-wide unified CPU and GPU tracing tool for OpenCL applications. Advances in Software Engineering, 2015, 1-14. https://doi.org/10.1155/2015/940628 |
---|---|
Statistiques
Total des téléchargements à partir de PolyPublie
Téléchargements par année
Provenance des téléchargements
Dimensions