Embedded Devices for Neuromorphic Time-Series Assessment
Technical University of Denmark · Jülich Aachen Research Alliance · +3 more institutions
Abstract
Modern computation based on the von Neumann architecture is today a mature cutting-edge science. In the Von Neumann architecture, processing and memory units are implemented as separate blocks interchanging data intensively and continuously. This data transfer is responsible for a large part of the power consumption. The next generation computer technology is expected to solve problems at the exascale with 1018 calculations each second. Even though these future computers will be incredibly powerful, if they are based on von Neumann type architectures, they will consume between 20 and 30 megawatts of power and will not have intrinsic physically built-in capabilities to learn or deal with complex data as our…
Citation impact
- FWCI
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- Percentile
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- References
- 524
Authors
3Topics & keywords
- Neuromorphic engineering
- Computer science
- Computer architecture
- Artificial intelligence
- Artificial neural network
- Affordable and clean energy
Funding
- NSNational Science FoundationAward: E2CDA #1507826
- VFVillum FondenAward: 00027993
- HHelmholtz-GemeinschaftAward: SO-092
- DFDeutsche ForschungsgemeinschaftAward: SFB 91
- SNSchweizerischer Nationalfonds zur Förderung der Wissenschaftlichen ForschungAward: HEAR-EAR, 200021172553
- NNNational Natural Science Foundation of ChinaAward: 62034004
- NENew Energy and Industrial Technology Development OrganizationAward: 18102285-0
- BFBundesministerium für Bildung und ForschungAward: 16ES1134
- CNCentre National de la Recherche Scientifique
- DFDanmarks Frie ForskningsfondAward: 48293
- EZETH Zürich Foundation
- FSFreistaat Sachsen
- CICollaborative Innovation Center of Advanced Microstructures
- DADefense Advanced Research Projects Agency
- H2Horizon 2020 Framework ProgrammeAward: EMPIR 20FUN06 MEMQuD
- EAEngineering and Physical Sciences Research CouncilAward: EP/M015173/1
- JSJapan Society for the Promotion of ScienceAward: 20K11882
- NINational Institute on Deafness and Other Communication DisordersAward: R01 DC014701
- HFH2020 Future and Emerging TechnologiesAward: 945539
- FIFP7 Information and Communication TechnologiesAward: 604102