GPU Devices for Safety-Critical Systems: A Survey

Author:

Perez-Cerrolaza Jon1ORCID,Abella Jaume2ORCID,Kosmidis Leonidas2ORCID,Calderon Alejandro J.3ORCID,Cazorla Francisco4ORCID,Flores Jose Luis1ORCID

Affiliation:

1. Ikerlan Technology Research Centre, Basque Research and Technology Alliance (BRTA), Guipúzcoa, Spain

2. Barcelona Supercomputing Center, Cataluña, Spain

3. Universitat Politècnica de Catalunya and Ikerlan Technology Research Centre, Basque Research and Technology Alliance (BRTA), Guipúzcoa, Spain

4. Barcelona Supercomputing Center and Maspatechnologies S.L., Cataluña, Spain

Abstract

 Graphics Processing Unit (GPU) devices and their associated software programming languages and frameworks can deliver the computing performance required to facilitate the development of next-generation high-performance safety-critical systems such as autonomous driving systems. However, the integration of complex, parallel, and computationally demanding software functions with different safety-criticality levels on GPU devices with shared hardware resources contributes to several safety certification challenges. This survey categorizes and provides an overview of research contributions that address GPU devices’ random hardware failures, systematic failures, and independence of execution.

Funder

European Research Council with Horizon 2020

Spanish Ministry of Science and Innovation SP02

HiPEAC Network of Excellence

Basque Government

Spanish Ministry of Economy and Competitiveness

Juan de la Cierva Incorporación postdoctoral fellowship

Publisher

Association for Computing Machinery (ACM)

Subject

General Computer Science,Theoretical Computer Science

Reference204 articles.

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3. 2018. ISO 26262-11: Road Vehicles - Functional Safety - Part 11: Guideline on application of ISO 26262 to semiconductors.

4. 2020. NVIDIA Xavier Series System-on-Chip - Technical Reference Manual. Report DP-09253-002. NVIDIA.

5. 2020. R-Car H3/M3 - User Manual (Rev.0.10). Report. Renesas.

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