Long-Term and Short-Term Transistor Aging in Deep Neural Networks: Impact and Mitigation
Deep neural networks (DNNs) are used in a variety of real-world applications including, for example, image classification and speech recognition. The inference accuracy of DNN implemented on hardware in integrated circuits (ICs) degrades under phenomena such as transistor aging. Aging slows down the switching speed of transistors, resulting in system-level timing violations due to unsustainable clocks. To maintain reliability for the entire projected lifetime, designers add guardbands to prevent timing violations; however, adding large timing guardbands causes losses in performance (speed or throughput). This chapter provides a detailed discussion of the effects of long-term and short-ter...
| Authors | Alireza Sarmadi, Virinchi Roy Surabhi, Prashanth Krishnamurthy et al. |
|---|---|
| Primary category | cs.CR |
| Published | 2 June 2026 |
| Last updated at source | 2 June 2026 |
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