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Taming extreme heterogeneity via machine learning based des..:

, In: Proceedings of the International Conference on Hardware/Software Codesign and System Synthesis Companion,

Bogdan, Paul ; Chen, Fan ; Deshwal, Aryan... - p. 1-10 , 2019

Link: https://dl.acm.org/doi/10.1145/3349567.3357376

RT 
T1 <cTitle>Proceedings of the International Conference on Hardware/Software Codesign and System Synthesis Companion</cTitle>: T1 <Title>Taming extreme heterogeneity via machine learning based design of autonomous manycore systems</Title>

UL https://suche.suub.uni-bremen.de/peid=acm-3357376&Exemplar=1&LAN=DE
				
A1 Bogdan, Paul
A1 Chen, Fan
A1 Deshwal, Aryan
A1 Doppa, Janardhan Rao
A1 Joardar, Biresh Kumar
A1 Li, Hai (Helen)
A1 Nazarian, Shahin
A1 Song, Linghao
A1 Xiao, Yao
PB ACM
YR 2019
K1 ReRAM
K1 autonomous design optimization
K1 machine learning
K1 manycore systems
K1 model of computation
K1 processing-in-memory
K1 self-programming computing architectures
K1 Computer systems organization
K1 Embedded and cyber-physical systems
K1 Embedded systems
K1 Networks
K1 Network properties
K1 Network reliability
K1 Robotics
K1 Dependable and fault-tolerant systems and networks
K1 Redundancy
SP 1
OP 10
LK http://dx.doi.org/https://dl.acm.org/doi/10.1145/3349567.3357376
DO https://dl.acm.org/doi/10.1145/3349567.3357376
SF ELIB - SuUB Bremen

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