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Sökning: onr:"swepub:oai:DiVA.org:kth-337433" > A GPU-based computa...

A GPU-based computational framework that bridges neuron simulation and artificial intelligence

Zhang, Yichen (författare)
National Key Laboratory for Multimedia Information Processing, School of Computer Science, Peking University, Beijing, 100871, China
He, Gan (författare)
National Key Laboratory for Multimedia Information Processing, School of Computer Science, Peking University, Beijing, 100871, China
Ma, Lei (författare)
National Key Laboratory for Multimedia Information Processing, School of Computer Science, Peking University, Beijing, 100871, China; Beijing Academy of Artificial Intelligence (BAAI), Beijing, 100084, China
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Liu, Xiaofei (författare)
National Key Laboratory for Multimedia Information Processing, School of Computer Science, Peking University, Beijing, 100871, China; School of Information Science and Engineering, Yunnan University, Kunming, 650500, China
Hjorth, J. J. Johannes (författare)
KTH,Science for Life Laboratory, SciLifeLab,Beräkningsvetenskap och beräkningsteknik (CST)
Kozlov, Alexander (författare)
KTH,Science for Life Laboratory, SciLifeLab,Beräkningsvetenskap och beräkningsteknik (CST),Department of Neuroscience, Karolinska Institute, Stockholm, SE-17165, Sweden
He, Yutao (författare)
National Key Laboratory for Multimedia Information Processing, School of Computer Science, Peking University, Beijing, 100871, China
Zhang, Shenjian (författare)
National Key Laboratory for Multimedia Information Processing, School of Computer Science, Peking University, Beijing, 100871, China
Hellgren Kotaleski, Jeanette (författare)
KTH,Beräkningsvetenskap och beräkningsteknik (CST),Science for Life Laboratory, SciLifeLab,Department of Neuroscience, Karolinska Institute, Stockholm, SE-17165, Sweden
Tian, Yonghong (författare)
National Key Laboratory for Multimedia Information Processing, School of Computer Science, Peking University, Beijing, 100871, China; School of Electrical and Computer Engineering, Shenzhen Graduate School, Peking University, Shenzhen, 518055, China
Grillner, Sten (författare)
Department of Neuroscience, Karolinska Institute, Stockholm, SE-17165, Sweden
Du, Kai (författare)
Institute for Artificial Intelligence, Peking University, Beijing, 100871, China
Huang, Tiejun (författare)
National Key Laboratory for Multimedia Information Processing, School of Computer Science, Peking University, Beijing, 100871, China; Beijing Academy of Artificial Intelligence (BAAI), Beijing, 100084, China; Institute for Artificial Intelligence, Peking University, Beijing, 100871, China
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 (creator_code:org_t)
Springer Nature, 2023
2023
Engelska.
Ingår i: Nature Communications. - : Springer Nature. - 2041-1723. ; 14:1
Relaterad länk:
https://doi.org/10.1...
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https://urn.kb.se/re...
https://doi.org/10.1...
http://kipublication...
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  • Tidskriftsartikel (refereegranskat)
Abstract Ämnesord
Stäng  
  • Biophysically detailed multi-compartment models are powerful tools to explore computational principles of the brain and also serve as a theoretical framework to generate algorithms for artificial intelligence (AI) systems. However, the expensive computational cost severely limits the applications in both the neuroscience and AI fields. The major bottleneck during simulating detailed compartment models is the ability of a simulator to solve large systems of linear equations. Here, we present a novel Dendritic Hierarchical Scheduling (DHS) method to markedly accelerate such a process. We theoretically prove that the DHS implementation is computationally optimal and accurate. This GPU-based method performs with 2-3 orders of magnitude higher speed than that of the classic serial Hines method in the conventional CPU platform. We build a DeepDendrite framework, which integrates the DHS method and the GPU computing engine of the NEURON simulator and demonstrate applications of DeepDendrite in neuroscience tasks. We investigate how spatial patterns of spine inputs affect neuronal excitability in a detailed human pyramidal neuron model with 25,000 spines. Furthermore, we provide a brief discussion on the potential of DeepDendrite for AI, specifically highlighting its ability to enable the efficient training of biophysically detailed models in typical image classification tasks.

Ämnesord

MEDICIN OCH HÄLSOVETENSKAP  -- Medicinska och farmaceutiska grundvetenskaper -- Neurovetenskaper (hsv//swe)
MEDICAL AND HEALTH SCIENCES  -- Basic Medicine -- Neurosciences (hsv//eng)

Nyckelord

Algorithms
Artificial Intelligence
Brain
Humans
Neurons
Pyramidal Cells

Publikations- och innehållstyp

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