Towards Budget-Driven Hardware Optimization for Deep Convolutional Neural Networks using Stochastic Computing

Recently, Deep Convolutional Neural Network (DCNN) has achieved tremendous success in many machine learning applications. Nevertheless, the deep structure has brought significant increases in computation complexity. Largescale deep learning systems mainly operate in high-performance server clusters,...

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Veröffentlicht in:	arXiv.org 2018-05
Hauptverfasser:	Li, Zhe, Li, Ji, Ao Ren, Ding, Caiwen, Draper, Jeffrey, Qiu, Qinru, Yuan, Bo, Wang, Yanzhi
Format:	Artikel
Sprache:	eng
Schlagworte:	Acceleration Algorithms Artificial neural networks Budgeting Budgets Computation Design optimization Design parameters Electronic devices Hardware Machine learning Neural networks
Online-Zugang:	Volltext
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