Runtime Fault Diagnostics for GPU Tensor Cores
Saurabh Hukerikar, N.R. Saxena · 2022
Tensor cores in NVIDIA GPUs are important computational engines that accelerate diverse AI deep neural networks and algorithms for perception, mapping, localization and path planning in autonomous drive systems. The occurrence of random hardware faults, particularly permanent faults in these computational units have potentially catastrophic consequences. This paper describes software-based runtime diagnostics for tensor cores that leverage universal test patterns (UTP) to achieve high diagnostic fault coverage with very low latency enabling GPU-based systems to meet the ASIL B functional safety targets outlined in the ISO 26262 standard.