In recent years, the growth of interest in adopting deep neural network techniques across various domains led to new architectures for supporting the required computational effort. Tensor Processing Units (TPUs), which are based on a systolic array matrix multiplication unit (MMU), became widely popular thanks to their specific structure suitable for Artificial Intelligence. This work investigates Single Event Transient (SET) effects on TPU’s MMU. The analysis demonstrates the impact of SETs on the functionality of MMU when executing digital image processing filtering. The experimental results identify the static and dynamic SET sensitivity of TPU and depict meaningful information on the data dependency of the filters’ kernel values.
A Comprehensive Analysis of Transient Errors on Systolic Arrays / Vacca, Eleonora; Azimi, Sarah; Sterpone, Luca. - ELETTRONICO. - (In corso di stampa). (Intervento presentato al convegno 26th International Symposium on Design and Diagnostics of Electronic Circuits and Systems tenutosi a Tallin, Estonia nel 3-5 May 2023).
A Comprehensive Analysis of Transient Errors on Systolic Arrays
Vacca, Eleonora;Azimi, Sarah;Sterpone, Luca
In corso di stampa
Abstract
In recent years, the growth of interest in adopting deep neural network techniques across various domains led to new architectures for supporting the required computational effort. Tensor Processing Units (TPUs), which are based on a systolic array matrix multiplication unit (MMU), became widely popular thanks to their specific structure suitable for Artificial Intelligence. This work investigates Single Event Transient (SET) effects on TPU’s MMU. The analysis demonstrates the impact of SETs on the functionality of MMU when executing digital image processing filtering. The experimental results identify the static and dynamic SET sensitivity of TPU and depict meaningful information on the data dependency of the filters’ kernel values.File | Dimensione | Formato | |
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https://hdl.handle.net/11583/2977969