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Jan, 2019
基于深度神经网络进行定制硬件逼近: 过去和未来
Deep Neural Network Approximation for Custom Hardware: Where We've Been, Where We're Going
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Erwei Wang, James J. Davis, Ruizhe Zhao, Ho-Cheung Ng, Xinyu Niu...
TL;DR
该论文提供了有关高性能网络推断的近似方法的全面评估,并深入讨论了这些方法在自定义硬件实现中的有效性,旨在启发该领域的新发展。
Abstract
deep neural networks
have proven to be particularly effective in visual and audio recognition tasks. Existing models tend to be computationally expensive and memory intensive, however, and so methods for
hardware-orient
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