Art

J-GLOBAL ID：202002242486908318   Reference number：20A0318605

CNNアクセラレータSNACCの実チップ評価

Author (5)： TOMURA RYOHEI (慶応大) ,  KOJIMA TAKUYA (慶応大) ,  AMANO HIDEHARU (慶応大) ,  SAKAMOTO RYUICHI (東大) ,  KONDO MASAAKI (東大)
Material： 電子情報通信学会技術研究報告  (IEICE Technical Report (Institute of Electronics, Information and Communication Engineers))
Volume： 119  Issue： 286(CPSY2019 41-51)(Web)  Page： 65-70 (WEB ONLY)  Publication year： Nov. 06, 2019 
JST Material Number： S0532B  ISSN： 0913-5685  Document type： Proceedings
Article type： 原著論文  Country of issue： Japan (JPN)  Language： JAPANESE (JA)

Thesaurus term： *neural network (biomodel) ,  data processing system ,  SIMD ,  complementary metal oxide semiconductor ,  Machine Learning ,  Electronics ,  *hardware design ,  performance evaluation ,  accelerator ,  deep neural network ,  convolutional neuralnetwork ,  deep learning
Semi thesaurus term： convolutional neural network ,  TCI【チップ間接続技術】 ,  three dimension laminated technology

JST classification (1)： Digital computer systems in general  (JC02010O)

Reference (12)：

• Y.-H. Chen, T. Krishna, Joel S.Emer, and V. Sze, “Eyeriss: An energy-efficient reconfigurable accelerator for deep convolutional neural networks,” IEEE Journal of Solid-State Circuits, vol.52, no.1, pp.127-138, 2017.
• Y. Chen and et.al, “Dadiannao: A machine-learning supercomputer,” 2014 47th Annual IEEE/ACM International Symposium on Microarchitecture, pp.609-622, 2014.
• S.Han, X.Liu, H.Mao, J.Pu, and A.Pedram, “Eie: Efficient inference engine on compressed deep neural network,”43rd Intenernational Symposium on Computer Architecture, pp.243-254, 2016.
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• A. Krizhevsky, I. Sutskever, and G.E. Hinton, “Imagenet classification with deep convolutional neural networks,” Advances in Neural Information Processing Systems 25, pp.1097-1105, 2012.

Terms in the title (3)： CNN ,  アクセラレータ ,  評価