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ECE professor’s paper selected for IEEE best paper award

January 10, 2022 - by Kim Delker

photo: Lei Yang
Lei Yang

Lei Yang, assistant professor of electrical and computer engineering at The University of New Mexico, has been awarded the 2021 Donald O. Pederson Best Paper Award by the IEEE Transactions on Computer-Aided Design.

The paper, “Hardware/Software Co-Exploration of Neural Architectures,” proposes a novel hardware and software framework for efficient neural architecture search (NAS), a technique to automate machine learning systems.

The IEEE Transactions on Computer-Aided Design Editorial Board and the IEEE Council on Electronic Design Automation selected the paper as one of two 2021 winners from over 800 papers published by the journal in the last two years based on the overall quality, originality, level of contribution, subject matter and timeliness of the research. The award was presented at the Design Automation Conference in December 2021.

“This is the first work for the co-exploration of hardware design space and neural network architecture search space,” Lei said. “Compared with the existing hardware-aware NAS, in this work, our proposed co-exploration framework has demonstrated the best tradeoff between the performance of neural network architectures and the requires from hardware platforms. It provides fundaments of a series of my co-design neural network system works, among which several works have been nominated for best paper at top EDA conferences.”

In addition, Lei said she and her research team have implemented the proposed co-exploration framework onto real-edge devices, the implantable cardioverter defibrillator (ICD), for achieving the higher accuracy of heartrate detection. This research was awarded the 31st ACM SIGDA University Demonstration at Design Automation Conference in December 2021.

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