6 citations · 23 across the 17 of their papers we have counts for
4 papers · 1 filter
LCFI: A Fault Injection Tool for Studying Lossy Compression Error Propagation in HPC Programs
Baodi Shan, Aabid Shamji, Jiannan Tian +2
Error-bounded lossy compression is becoming more and more important to today's extreme-scale HPC applications because of the ever-increasing volume of data generated because it has…
A Novel Memory-Efficient Deep Learning Training Framework via Error-Bounded Lossy Compression
Sian Jin, Guanpeng Li, Shuaiwen Leon Song +1
Deep neural networks (DNNs) are becoming increasingly deeper, wider, and non-linear due to the growing demands on prediction accuracy and analysis quality. When training a DNN mode…
TensorFI: A Flexible Fault Injection Framework for TensorFlow Applications
Zitao Chen, Niranjhana Narayanan, Bo Fang +3
As machine learning (ML) has seen increasing adoption in safety-critical domains (e.g., autonomous vehicles), the reliability of ML systems has also grown in importance. While prio…
A Low-cost Fault Corrector for Deep Neural Networks through Range Restriction
Zitao Chen, Guanpeng Li, Karthik Pattabiraman
The adoption of deep neural networks (DNNs) in safety-critical domains has engendered serious reliability concerns. A prominent example is hardware transient faults that are growin…