TIE: Energy-efficient Tensor Train-based Inference Engine for Deep Neural Network

In the era of artificial intelligence (AI), deep neural networks (DNNs) have emerged as the most important and powerful AI technique. However, large DNN models are both storage and computation intensive, posing significant challenges for adopting DNNs in resource- constrained scenarios. Thus, model...

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Veröffentlicht in:	2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA) S. 264 - 277
Hauptverfasser:	Deng, Chunhua, Sun, Fangxuan, Qian, Xuehai, Lin, Jun, Wang, Zhongfeng, Yuan, Bo
Format:	Tagungsbericht
Sprache:	Englisch
Veröffentlicht:	ACM 01.06.2019
Schlagworte:	acceleration Artificial intelligence Artificial neural networks CMOS technology compression Computational modeling Computer architecture Deep learning Energy efficiency Engines Prototypes tensor-train decomposition Tensors Throughput
ISSN:	2575-713X
Online-Zugang:	Volltext
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