Fully Parallel Stochastic Computing Hardware Implementation of Convolutional Neural Networks for Edge Computing Applications
العنوان: | Fully Parallel Stochastic Computing Hardware Implementation of Convolutional Neural Networks for Edge Computing Applications |
---|---|
المؤلفون: | Christiam F. Frasser, Pablo Linares-Serrano, Ivan Diez de los Rios, Alejandro Moran, Erik S. Skibinsky-Gitlin, Joan Font-Rossello, Vincent Canals, Miquel Roca, Teresa Serrano-Gotarredona, Josep L. Rossello |
المصدر: | IEEE Transactions on Neural Networks and Learning Systems. :1-11 |
بيانات النشر: | Institute of Electrical and Electronics Engineers (IEEE), 2022. |
سنة النشر: | 2022 |
مصطلحات موضوعية: | Artificial Intelligence, Computer Networks and Communications, Software, Computer Science Applications |
الوصف: | Edge artificial intelligence (AI) is receiving a tremendous amount of interest from the machine learning community due to the ever-increasing popularization of the Internet of Things (IoT). Unfortunately, the incorporation of AI characteristics to edge computing devices presents the drawbacks of being power and area hungry for typical deep learning techniques such as convolutional neural networks (CNNs). In this work, we propose a power-and-area efficient architecture based on the exploitation of the correlation phenomenon in stochastic computing (SC) systems. The proposed architecture solves the challenges that a CNN implementation with SC (SC-CNN) may present, such as the high resources used in binary-to-stochastic conversion, the inaccuracy produced by undesired correlation between signals, and the complexity of the stochastic maximum function implementation. To prove that our architecture meets the requirements of edge intelligence realization, we embed a fully parallel CNN in a single field-programmable gate array (FPGA) chip. The results obtained showed a better performance than traditional binary logic and other SC implementations. In addition, we performed a full VLSI synthesis of the proposed design, showing that it presents better overall characteristics than other recently published VLSI architectures. |
تدمد: | 2162-2388 2162-237X |
URL الوصول: | https://explore.openaire.eu/search/publication?articleId=doi_dedup___::e89cda35dc70cd49af61c831facf0c0c https://doi.org/10.1109/tnnls.2022.3166799 |
حقوق: | CLOSED |
رقم الأكسشن: | edsair.doi.dedup.....e89cda35dc70cd49af61c831facf0c0c |
قاعدة البيانات: | OpenAIRE |
تدمد: | 21622388 2162237X |
---|