GPU devices for safety-critical systems: a survey
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 integrat...
| Autores: | , , , , , |
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| Tipo de recurso: | artículo |
| Fecha de publicación: | 2023 |
| País: | España |
| Institución: | Universitat Politècnica de Catalunya (UPC) |
| Repositorio: | UPCommons. Portal del coneixement obert de la UPC |
| Idioma: | inglés |
| OAI Identifier: | oai:upcommons.upc.edu:2117/386460 |
| Acceso en línea: | https://hdl.handle.net/2117/386460 https://dx.doi.org/10.1145/3549526 |
| Access Level: | acceso abierto |
| Palabra clave: | Graphics processing units Computer security Diagnostic coverage Time independence Spatial independence Unitats de processament gràfic Seguretat informàtica Àrees temàtiques de la UPC::Informàtica::Arquitectura de computadors |
| Sumario: | 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. |
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