Experimental Demonstration and Tolerancing of a Large-Scale Neural Network (165 000 Synapses) Using Phase-Change Memory as the Synaptic Weight Element

IEEE Transactions on Electron Devices

Volumn 62, Issue 11, 2015, Pages 3498-3507

  Burr, Geoffrey W ^a   Shelby, Robert M ^a   Sidler, Severin ^a   Di Nolfo, Carmelo ^a   Jang, Junwoo ^b   Boybat, Irem ^c   Shenoy, Rohit S ^d   Narayanan, Pritish ^a   Virwani, Kumar ^a   Giacometti, Emanuele U ^a   Kurdi, Bulent N ^a   Hwang, Hyunsang ^b  

^a IBM ALMADEN RESEARCH CENTER   (United States)

^b Pohang University of Science and Technology (POSTECH)   (South Korea)

^c EPFL   (Switzerland)

^d INTEL CORPORATION   (United States)

Author keywords

Artificial neural networks; Machine learning; Multilayer perceptrons; Nonvolatile memory; Phase change memory

Indexed keywords

NETWORK LAYERS; SCALES (WEIGHING INSTRUMENTS);

CLASSIFICATION ACCURACY; EXPERIMENTAL DEMONSTRATIONS; HANDWRITTEN DIGIT; HIGH DYNAMIC RANGE; NEURAL NETWORK SIMULATORS; NON-VOLATILE MEMORY; SYNAPTIC WEIGHT; THREE-LAYER PERCEPTRON;

PHASE CHANGE MEMORY;

EID: 84946495902     PISSN: 00189383     EISSN: None     Source Type: Journal    
DOI: 10.1109/TED.2015.2439635     Document Type: Article

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