Neuromemristive Systems: Boosting Efficiency through Brain-Inspired Computing

Computer

Volumn 49, Issue 10, 2016, Pages 56-64

  Merkel, Cory ^a   Hasan, Raqibul ^b   Soures, Nicholas ^c   Kudithipudi, Dhireesha ^c   Taha, Tarek ^d   Agarwal, Sapan ^e   Marinella, Matthew ^e  

^a AIR FORCE RESEARCH LABORATORY   (United States)

^b LABORATORY FOR PHYSICAL SCIENCES   (United States)

^c ROCHESTER INSTITUTE OF TECHNOLOGY   (United States)

^d UNIVERSITY OF DAYTON   (United States)

^e SANDIA NATIONAL LABORATORIES   (United States)

Author keywords

brain inspired computing; energy efficient computing; energy efficient systems; high performance computing; low power design; memristors; neural network architecture; neural networks; neuromemristive systems; neuromorphic systems; power management

Indexed keywords

BRAIN; ELECTRIC POWER SUPPLIES TO APPARATUS; LEARNING SYSTEMS; LOW POWER ELECTRONICS; MEMRISTORS; NETWORK ARCHITECTURE; NEURAL NETWORKS; POWER MANAGEMENT; REDUCED INSTRUCTION SET COMPUTING;

BRAIN-INSPIRED COMPUTING; ENERGY EFFICIENT COMPUTING; ENERGY EFFICIENT SYSTEMS; HIGH PERFORMANCE COMPUTING; LOW-POWER DESIGN; NEUROMORPHIC SYSTEMS;

ENERGY EFFICIENCY;

EID: 84992695572     PISSN: 00189162     EISSN: None     Source Type: Trade Journal    
DOI: 10.1109/MC.2016.312     Document Type: Article

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