Name
Abstract | ||
|---|---|---|
Owing to the inherent fault tolerance of deep neural network (DNN) models used for classification, many structural faults in the processing elements (PEs) of a systolic array-based AI accelerator are functionally benign. Brute-force fault simulation for determining fault criticality is computationally expensive due to many potential fault sites in the accelerator array and the dependence of critic... |
Year | DOI | Venue |
|---|---|---|
2021 | 10.1109/ITC50571.2021.00015 | 2021 IEEE International Test Conference (ITC) |
DocType | ISSN | ISBN |
Conference | 1089-3539 | 978-1-6654-1695-5 |
Citations | PageRank | References |
3 | 0.48 | 0 |
Authors | ||
6 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Arjun Chaudhuri | 1 | 17 | 7.07 |
| Ching-Yuan Chen | 2 | 3 | 1.83 |
| Jonti Talukdar | 3 | 8 | 1.35 |
| Siddarth Madala | 4 | 3 | 0.48 |
| Abhishek Kumar Dubey | 5 | 3 | 0.48 |
| K Chakrabarty | 6 | 8173 | 636.14 |