An Effective Method to Identify Microarchitectural Vulnerabilities in GPUs - Inria - Institut national de recherche en sciences et technologies du numérique Access content directly
Journal Articles IEEE Transactions on Device and Materials Reliability Year : 2022

An Effective Method to Identify Microarchitectural Vulnerabilities in GPUs


Graphics Processing Units (GPUs) are increasingly adopted in several domains where reliability is fundamental, such as self-driving cars and autonomous systems. Unfortunately, GPU devices have been shown to have a high error rate, while the constraints imposed by real-time safety-critical applications make traditional (and costly) replication-based hardening solutions inadequate. This work proposes an effective methodology to identify the architectural vulnerable sites in GPUs modules, i.e. the locations that, if corrupted, most affect the correct instructions execution. We first identify, through an innovative method based on Register-Transfer Level (RTL) fault injection experiments, the architectural vulnerabilities of a GPU model. Then, we mitigate the fault impact via selective hardening applied to the flip-flops that have been identified as critical. We evaluate three hardening strategies: Triple Modular Redundancy (TMR), Triple Modular Redundancy against SETs (∆TMR), and Dual Interlocked Storage Cells (Dice flip-flops). The results gathered on a publicly available GPU Model (FlexGripPlus) considering functional units, pipeline registers, and warp scheduler controller show that our method can tolerate from 85% to 99% of faults in the pipeline registers, from 50% to 100% of faults in the functional units and up to 10% of faults in the warp scheduler, with a reduced hardware overhead (in the range of 58 % to 94% when compared with traditional TMR). Finally, we adapt the methodology to perform a complementary evaluation targeting permanent faults and identify critical sites prone to propagate fault effects across the GPU. We found that a considerable percentage (65% to 98%) of flip-flops that are critical for transient faults are also critical for permanent faults.
Fichier principal
Vignette du fichier
Transactions_on_device_and_materials_reliability.pdf (1.11 Mo) Télécharger le fichier
Origin : Files produced by the author(s)

Dates and versions

hal-03669439 , version 1 (16-05-2022)



Josie Rodriguez Condia, Paolo Rech, Fernando Fernandes dos Santos, Luigi Carro, Matteo Sonza Reorda. An Effective Method to Identify Microarchitectural Vulnerabilities in GPUs. IEEE Transactions on Device and Materials Reliability, 2022, pp.1-14. ⟨10.1109/TDMR.2022.3166260⟩. ⟨hal-03669439⟩
53 View
89 Download



Gmail Facebook Twitter LinkedIn More