Nowadays, Graphical Processing Units (GPUs) have become increasingly popular due to their high computational power and low prices. This makes them particularly suitable for high-performance computing applications, like data elaboration and financial computation. In these fields, high efficient test methodologies are mandatory. One of the most effective ways to detect and localize hardware faults in GPUs is a Software-Based-Self-Test methodology (SBST). In this paper a fully comprehensive SBST and fault localization methodology for GPUs is presented. This novel approach exploits different custom test strategies for each component inside the GPU architecture. Such strategies guarantee both permanent fault detection and accurate fault localization.

A software-based self test of CUDA Fermi GPUs / DI CARLO, Stefano; Gambardella, G.; Indaco, M.; Martella, I.; Prinetto, Paolo Ernesto; Rolfo, D.; Trotta, P.. - STAMPA. - (2013), pp. 1-6. (Intervento presentato al convegno IEEE 18th European Test Symposium (ETS) tenutosi a Avignon (F) nel 27-30 May 2013) [10.1109/ETS.2013.6569353].

A software-based self test of CUDA Fermi GPUs

DI CARLO, STEFANO;PRINETTO, Paolo Ernesto;
2013

Abstract

Nowadays, Graphical Processing Units (GPUs) have become increasingly popular due to their high computational power and low prices. This makes them particularly suitable for high-performance computing applications, like data elaboration and financial computation. In these fields, high efficient test methodologies are mandatory. One of the most effective ways to detect and localize hardware faults in GPUs is a Software-Based-Self-Test methodology (SBST). In this paper a fully comprehensive SBST and fault localization methodology for GPUs is presented. This novel approach exploits different custom test strategies for each component inside the GPU architecture. Such strategies guarantee both permanent fault detection and accurate fault localization.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11583/2513497
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