A scalable, heterogeneous hardware platform for accelerated aiot based on microservers

Autor(en): Griessl, R.
Porrmann, F.
Kucza, N.
Mika, K.
Hagemeyer, J.
Kaiser, M.
Porrmann, M. 
Tassemeier, M.
Flottmann, M.
Qararyah, F.
Waqar, M.
Trancoso, P.
Ödman, D.
Gugala, K.
Latosinski, G.
Stichwörter: (far) edge-computing; Accelerator; AIoT; Deep learning; Energy-efficiency; FPGA; IoT; Machine learning; Microserver; Performance classification
Erscheinungsdatum: 2023
Herausgeber: River Publishers
Journal: Shaping the Future of IoT with Edge Intelligence: How Edge Computing Enables the Next Generation of IoT Applications
Startseite: 179 – 196
Zusammenfassung: 
Performance and energy efficiency are key aspects of next-generation AIoT hardware. This chapter presents a scalable, heterogeneous hardware platform for accelerated AIoT based on microserver technology. It integrates several accelerator platforms based on technologies like CPUs, embedded GPUs, FPGAs, or specialized ASICs, supporting the full range of the cloud-edge-IoT continuum. The modular microserver approach enables the integration of different, heterogeneous accelerators into one platform. Benchmarking the various accelerators takes performance, energy efficiency, and accuracy into account. The results provide a solid overview of available accelerator solutions and guide hardware selection for AIoT applications from the far edge to the cloud. © The Editor(s) (if applicable) and The Author(s) 2023. All rights reserved.
Beschreibung: 
Cited by: 0
ISBN: 9788770040266
9788770040273
Externe URL: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85173023396&partnerID=40&md5=801665a7503d8e93263e7f1c77ce52e0

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