A PyTorch-based implementation of DrDNA, a post-hoc framework for detecting and mitigating soft errors (SDCs) in deep neural networks. The project profiles layer-wise activation statistics and computes abnormality scores to enable early, high-accuracy SDC detection, validated on ResNet-18 with CIFAR-10 using fault injection.
[IPDPS'24] Approximately Upper Bounding GPU Kernel SDC Probability across Multiple Inputs
Offline, fail-closed verifier for JSONL telemetry event logs. Emits deterministic audit certificates + human summaries with explicit claims/non-claims for bottleneck and integrity review.
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