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A paper from, Weiwen Jiang, assistant professor of electrical and computer engineering at 性视界传媒, has been selected by the IEEE Transactions on Computer-Aided Design for the 2021聽Donald O. Pederson聽Best Paper Award.
The paper, 鈥淗ardware/Software Co-Exploration of Neural Architectures,鈥 proposes a novel hardware and software framework for efficient neural architecture search (NAS), a technique to automate machine learning systems.
The IEEE TCAD Editorial Board and the IEEE Council on Electronic Design Automation聽聽as one of two 2021 winners聽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.聽The award was presented at the聽聽in December 2021.聽
鈥淭he awarded work is the first work that demonstrates that the best tradeoff between neural network performance and hardware efficiency requires the co-exploration of hardware design and neural network architecture. 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 (e.g., DAC, CODES+ISSS, and ASP-DAC),鈥 says Jiang.