A heterogeneous multi-core system-on-chip for energy efficient brain inspired vision

Proceedings - IEEE International Symposium on Circuits and Systems

Volumn 2016-July, Issue , 2016, Pages 2910-

  Pullini, Antonio ^a   Conti, Francesco ^a,b   Rossi, Davide ^b   Loi, Igor ^b   Gautschi, Michael ^a   Benini, Luca ^a,b  

^a ETH ZURICH   (Switzerland)

^b UNIVERSITY OF BOLOGNA   (Italy)

Author keywords

[No Author keywords available]

Indexed keywords

APPLICATION SPECIFIC INTEGRATED CIRCUITS; CLASSIFICATION (OF INFORMATION); COMPUTER VISION; CONVOLUTION; NEURAL NETWORKS; PROGRAMMABLE LOGIC CONTROLLERS; RECONFIGURABLE HARDWARE; SENSOR NODES; SYSTEM-ON-CHIP;

CLASSIFICATION ACCURACY; COMPUTATIONAL REQUIREMENTS; CONVOLUTIONAL NEURAL NETWORK; EMBEDDED PLATFORMS; GENERALIZATION CAPABILITY; HARDWARE ACCELERATORS; HETEROGENEOUS MULTI-CORE SYSTEMS; INFORMATION DENSITY;

ENERGY EFFICIENCY;

EID: 84983396876     PISSN: 02714310     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ISCAS.2016.7539213     Document Type: Conference Paper

References (2)

1. F. Conti et al, "Ultra-Low-Energy Convolution Engine for Fast Brain-Inspired Vision in Multicore Clusters", DATE, 2015.
2. D. Rossi et al, "A 60 GOPS/W,-1. 8V to 0. 9V Body Bias ULP Cluster in 28nm UTBB FD-SOI technology", JSSE, 2015.