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eBrainII :
eBrainII : a 3 kW Realtime Custom 3D DRAM Integrated ASIC Implementation of a Biologically Plausible Model of a Human Scale Cortex
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- Stathis, Dimitrios (author)
- KTH,Elektronik och inbyggda system
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- Sudarshan, Chirag (author)
- University of Kaiserslautern, Kaiserslautern, Germany
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- Yang, Yu (author)
- KTH,Elektronik och inbyggda system
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- Jung, Mathias (author)
- Fraunhofer IESE, Kaiserslautern, Germany
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- Weis, Christian (author)
- University of Kaiserslautern, Kaiserslautern, Germany
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- Hemani, Ahmed, 1961- (author)
- KTH,Elektronik och inbyggda system
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- Lansner, Anders, Professor (author)
- Stockholms universitet,KTH,Beräkningsvetenskap och beräkningsteknik (CST),Matematiska institutionen,KTH Royal Institute of Technology, Sweden
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- Wehn, Norbert (author)
- University of Kaiserslautern, Kaiserslautern, Germany
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(creator_code:org_t)
- 2020-07-07
- 2020
- English.
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In: Journal of Signal Processing Systems. - : Springer. - 1939-8018 .- 1939-8115. ; 92:11, s. 1323-1343
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Abstract
Subject headings
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- The Artificial Neural Networks (ANNs), like CNN/DNN and LSTM, are not biologically plausible. Despite their initial success, they cannot attain the cognitive capabilities enabled by the dynamic hierarchical associative memory systems of biological brains. The biologically plausible spiking brain models, e.g., cortex, basal ganglia, and amygdala, have a greater potential to achieve biological brain like cognitive capabilities. Bayesian Confidence Propagation Neural Network (BCPNN) is a biologically plausible spiking model of the cortex. A human-scale model of BCPNN in real-time requires 162 TFlop/s, 50 TBs of synaptic weight storage to be accessed with a bandwidth of 200 TBs. The spiking bandwidth is relatively modest at 250 GBs/s. A hand-optimized implementation of rodent scale BCPNN has been done on Tesla K80 GPUs require 3 kWs, we extrapolate from that a human scale network will require 3 MWs. These power numbers rule out such implementations for field deployment as cognition engines in embedded systems. The key innovation that this paper reports is that it is feasible and affordable to implement real-time BCPNN as a custom tiled application-specific integrated circuit (ASIC) in 28 nm technology with custom 3D DRAM - eBrainII - that consumes 3 kW for human scale and 12 watts for rodent scale. Such implementations eminently fulfill the demands for field deployment.
Subject headings
- TEKNIK OCH TEKNOLOGIER -- Elektroteknik och elektronik -- Datorsystem (hsv//swe)
- ENGINEERING AND TECHNOLOGY -- Electrical Engineering, Electronic Engineering, Information Engineering -- Computer Systems (hsv//eng)
- NATURVETENSKAP -- Data- och informationsvetenskap -- Datavetenskap (hsv//swe)
- NATURAL SCIENCES -- Computer and Information Sciences -- Computer Sciences (hsv//eng)
- NATURVETENSKAP -- Data- och informationsvetenskap -- Bioinformatik (hsv//swe)
- NATURAL SCIENCES -- Computer and Information Sciences -- Bioinformatics (hsv//eng)
- NATURVETENSKAP -- Data- och informationsvetenskap (hsv//swe)
- NATURAL SCIENCES -- Computer and Information Sciences (hsv//eng)
Keyword
- 3D DRAM
- ASIC
- BCPNN
- Custom 3D DRAM
- Machine learning
- Neural Network
- Neural network architecture
- Neuromorphic computing
- Application specific integrated circuits
- Associative processing
- Backpropagation
- Bandwidth
- Brain models
- Cognitive systems
- Dynamic random access storage
- Embedded systems
- Hierarchical systems
- Program processors
- Scales (weighing instruments)
- Associative memory system
- Cognitive capability
- Field deployment
- Optimized implementation
- Plausible model
- Scale modeling
- Spiking model
- Synaptic weight
- Long short-term memory
Publication and Content Type
- ref (subject category)
- art (subject category)
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Stathis, Dimitri ...
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Sudarshan, Chira ...
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Yang, Yu
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Jung, Mathias
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Weis, Christian
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Hemani, Ahmed, 1 ...
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Lansner, Anders, ...
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Wehn, Norbert
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- About the subject
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- ENGINEERING AND TECHNOLOGY
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ENGINEERING AND ...
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and Electrical Engin ...
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and Computer Systems
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- NATURAL SCIENCES
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NATURAL SCIENCES
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and Computer and Inf ...
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and Computer Science ...
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- NATURAL SCIENCES
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NATURAL SCIENCES
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and Computer and Inf ...
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and Bioinformatics
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- NATURAL SCIENCES
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NATURAL SCIENCES
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and Computer and Inf ...
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Journal of Signa ...
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Royal Institute of Technology
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Stockholm University