Comparison of GPU computing methodologies for safety-critical systems: an avionics case study
| Autor: | Sergio Carretero, Juan David Garcia, Ken Wenger, Leonidas Kosmidis, Marc Benito, Matina Maria Trompouki |
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| Přispěvatelé: | Barcelona Supercomputing Center, Universitat Politècnica de Catalunya. CAP - Grup de Computació d'Altes Prestacions |
| Jazyk: | angličtina |
| Rok vydání: | 2021 |
| Předmět: |
OpenGL SC 2.0
Computer software -- Development business.industry Computer science OpenGL Informàtica::Enginyeria del software [Àrees temàtiques de la UPC] Certification Computer software -- Reliability Avionics Programari -- Fiabilitat Aviònica CUDA Software Computer architecture Life-critical system Aeronàutica i espai::Aviònica [Àrees temàtiques de la UPC] Brook Auto/BRASIL Safety-critical systems Programari -- Desenvolupament State-of-the art Graphics General-purpose computing on graphics processing units business ComputingMethodologies_COMPUTERGRAPHICS |
| Zdroj: | DATE UPCommons. Portal del coneixement obert de la UPC Universitat Politècnica de Catalunya (UPC) |
| Popis: | Introducing advanced functionalities in safety-critical systems requires using more powerful architectures such as GPUs. However software in safety-critical industries is subject to functional certification, which cannot be achieved using standard GPU programming languages such as CUDA and OpenCL. Fortunately, GPUs are already used in certified critical systems for display tasks, using safety-certified solutions such as OpenGL SC 2.0. In this paper, we compare two state-of-the art graphics-based methodologies, OpenGL SC 2.0 and Brook Auto/BRASIL for the implementation of a prototype avionics case study. We evaluate both methods on a realistic industrial setup, composed by an avionics-grade GPU and a safety-certified GPU driver in terms of development metrics and performance, showing their feasibility. This work was funded by the Airbus TANIA-GPU Project ADS (E/200). It was also partially supported by the Spanish Ministry of Economy and Competitiveness under grants PID2019-107255GB and FJCI-2017-34095 and HiPEAC. |
| Databáze: | OpenAIRE |
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