Efficient Processing of Deep Neural Networks, Sze Vivienne, Chen Yu-Hsin, Yang Tien-Ju
Автор: Sze Vivienne, Chen Yu-Hsin, Yang Tien-Ju Название: Efficient Processing of Deep Neural Networks ISBN: 168173835X ISBN-13(EAN): 9781681738352 Издательство: Mare Nostrum (Eurospan) Цена: 116110.00 T Наличие на складе: Нет в наличии. Описание:
This book provides a structured treatment of the key principles and techniques for enabling efficient processing of deep neural networks (DNNs). DNNs are currently widely used for many artificial intelligence (AI) applications, including computer vision, speech recognition, and robotics. While DNNs deliver state-of-the-art accuracy on many AI tasks, it comes at the cost of high computational complexity. Therefore, techniques that enable efficient processing of deep neural networks to improve key metrics--such as energy-efficiency, throughput, and latency--without sacrificing accuracy or increasing hardware costs are critical to enabling the wide deployment of DNNs in AI systems.
The book includes background on DNN processing; a description and taxonomy of hardware architectural approaches for designing DNN accelerators; key metrics for evaluating and comparing different designs; features of DNN processing that are amenable to hardware/algorithm co-design to improve energy efficiency and throughput; and opportunities for applying new technologies. Readers will find a structured introduction to the field as well as formalization and organization of key concepts from contemporary work that provide insights that may spark new ideas.
Автор: Thomas Lu, Tien-Hsin Chao Название: Advances in Pattern Recognition Research ISBN: 1536144290 ISBN-13(EAN): 9781536144291 Издательство: Nova Science Рейтинг: Цена: 215410.00 T Наличие на складе: Невозможна поставка. Описание: Artificial Intelligence (AI) has become a popular research topic recently. Pattern recognition (PR) is an important part of an AI system. If the AI is considered as the digital brain, then the PR is the visual and auditory cortex that converts the optical signals from the eyes and the acoustic signals from the ears to meaningful symbolic texts that the brain can digest. Over the past 40+ years, the processing speed of a digital computer has increased from kbits/s to tera floating point operations per second (TFLOPS), a 109 times acceleration. PR research has made significant advancements along the advancement of digital hardware, especially the graphical processing unit (GPU) technology that helps the rapid processing of complex images. In this book, the authors have collected the latest work from leading researchers in the PR fields. The topics are broad, which include optical implementation of various filters, digital implementation of state-of-the-art neural network (NN) training methods, and the latest deep leaning (DL) models. We also included applications of PR in various fields.
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