SEC-Learn: Sensor Edge Cloud for Federated Learning Invited Paper

被引：0

作者：

Aichroth, Patrick ^{[3
]}

Antes, Christoph ^{[4
]}

Gembatzka, Pierre ^{[8
]}

Graf, Holger ^{[5
]}

Johnson, David S. ^{[3
]}

Jung, Matthias ^{[4
]}

Kaempfe, Thomas ^{[9
]}

Kleinberger, Thomas ^{[4
]}

Koellmer, Thomas ^{[3
]}

Kuhn, Thomas ^{[4
]}

Kutter, Christoph ^{[1
]}

Krueger, Jens ^{[10
]}

Loroch, Dominik M. ^{[10
]}

Lukashevich, Hanna ^{[3
]}

Laleni, Nellie ^{[9
]}

Zhang, Lei ^{[1
]}

Leugering, Johannes ^{[6
]}

Fernandez, Rodrigo Martin ^{[6
]}

Mateu, Loreto ^{[6
]}

Mojumder, Shaown ^{[9
]}

Prautsch, Benjamin ^{[6
]}

Pscheidl, Ferdinand ^{[1
]}

Roscher, Karsten ^{[7
]}

Schneickert, Soeren ^{[4
]}

Vanselow, Frank ^{[1
]}

Wallbott, Paul ^{[2
]}

Walter, Oliver ^{[2
]}

Weber, Nico ^{[10
]}

机构：

[1] EMFT, Fraunhofer Res Inst Microsyst & Solid State Techn, Munich, Germany

[2] Fraunhofer Inst Intelligent Anal & Informat Syst, St Augustin, Germany

[3] Fraunhofer Inst Digital Media Technol IDMT, Ilmenau, Germany

[4] Fraunhofer Inst Expt Software Engn IESE, Kaiserslautern, Germany

[5] Fraunhofer Inst Comp Graph Res IGD, Darmstadt, Germany

[6] Fraunhofer Inst Integrated Circuits IIS, Erlangen, Germany

[7] Fraunhofer Inst Cognit Syst IKS, Munich, Germany

[8] Fraunhofer Inst Microelect Circuits & Syst IMS, Duisburg, Germany

[9] Fraunhofer Inst Photon Microsyst IPMS, Dresden, Germany

[10] Fraunhofer Inst Ind Math ITWM, Kaiserslautern, Germany

来源：

EMBEDDED COMPUTER SYSTEMS: ARCHITECTURES, MODELING, AND SIMULATION, SAMOS 2021 | 2022年 / 13227卷

关键词：

SNN; Federated learning; Edge cloud; Neuromorphic hardware; Next generation computing; Virtual prototyping; NVM; DEEP NEURAL-NETWORKS;

D O I：

10.1007/978-3-031-04580-6_29

中图分类号：

TP3 [计算技术、计算机技术];

学科分类号：

0812 ;

摘要：

Due to the slow-down of Moore's Law and Dennard Scaling, new disruptive computer architectures are mandatory. One such new approach is Neuromorphic Computing, which is inspired by the functionality of the human brain. In this position paper, we present the projected SEC-Learn ecosystem, which combines neuromorphic embedded architectures with Federated Learning in the cloud, and performance with data protection and energy efficiency.

引用

页码：432 / 448

页数：17

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