1. Ankur Agrawal et al. 2019. Dlfloat: A 16-b floating point format designed for deep learning training and inference . In 26th IEEE Symposium on Computer Arithmetic, ARITH 2019 , Kyoto, Japan, June 10--12 , 2019 , 92--95. Ankur Agrawal et al. 2019. Dlfloat: A 16-b floating point format designed for deep learning training and inference. In 26th IEEE Symposium on Computer Arithmetic, ARITH 2019, Kyoto, Japan, June 10--12, 2019, 92--95.
2. NPU Thermal Management
3. Giorgos Armeniakos , Georgios Zervakis , Dimitrios Soudris , and Jörg Henkel . 2022 . Hardware approximate techniques for deep neural network accelerators: a survey . ACM Comput. Surv., (Mar. 2022). Giorgos Armeniakos, Georgios Zervakis, Dimitrios Soudris, and Jörg Henkel. 2022. Hardware approximate techniques for deep neural network accelerators: a survey. ACM Comput. Surv., (Mar. 2022).
4. Giorgos Armeniakos , Georgios Zervakis , Dimitrios Soudris , Mehdi B. Tahoori , and Jörg Henkel . 2022 . Cross-layer approximation for printed machine learning circuits. In Design , Automation Test in Europe Conference Exhibition, 190--195 . Giorgos Armeniakos, Georgios Zervakis, Dimitrios Soudris, Mehdi B. Tahoori, and Jörg Henkel. 2022. Cross-layer approximation for printed machine learning circuits. In Design, Automation Test in Europe Conference Exhibition, 190--195.
5. Approximate Decision Trees For Machine Learning Classification on Tiny Printed Circuits