Riccardo Faggiano
An extended RT-level model foran NVIDIA GPU for safety-critical applications = An extended RT-level model for an NVIDIA GPU for safety-critical applications.
Rel. Matteo Sonza Reorda, Josie Esteban Rodriguez Condia, Luca Sterpone. Politecnico di Torino, Corso di laurea magistrale in Ingegneria Elettronica (Electronic Engineering), 2022
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Abstract
General Purpose Graphics Processing Unit (GPGPU) is a Graphic Processing Unit (GPU) that is programmed for purposes beyond graphics processing, such as performing computations typically conducted by a Central Processing Unit (CPU). Incorporating GPUs for general purposes enhances CPU architecture by accelerating portions of an application while the rest continues to run on the CPU, ultimately creating a faster, high performance application. They have been massively used in the last years in many fields, such as DSP, bioinformatics, machine learning, etc. They are becoming popular also in safety critical applications as, for example, autonomous and semi-autonomous vehicles. Even if they allows performances to be improved, these devices suffer from transient faults (those produced by radiation effects) which can cause misbehaviors not acceptable in critical application.
The university of Massachusetts has developed a model for soft integer GPGPU optimized for a FPGA implementation which is called FlexGrip
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