<  Back to the Polytechnique Montréal portal

LTTng CLUST: A system-wide unified CPU and GPU tracing tool for OpenCL applications

David Couturier and Michel Dagenais

Article (2015)

Open Acess document in PolyPublie and at official publisher
Open Access to the full text of this document
Published Version
Terms of Use: Creative Commons Attribution
Download (1MB)
Show abstract
Hide 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.

Subjects: 2700 Information technology > 2700 Information technology
2700 Information technology > 2706 Software engineering
2700 Information technology > 2715 Optimization
Department: Department of Computer Engineering and Software Engineering
Funders: CRSNG/NSERC, Ericsson, EfficiOS
PolyPublie URL: https://publications.polymtl.ca/4834/
Journal Title: Advances in Software Engineering (vol. 2015)
Publisher: Hindawi
DOI: 10.1155/2015/940628
Official URL: https://doi.org/10.1155/2015/940628
Date Deposited: 16 Aug 2021 13:22
Last Modified: 01 Oct 2023 06:10
Cite in 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


Total downloads

Downloads per month in the last year

Origin of downloads


Repository Staff Only

View Item View Item