Reference Implementations for Machine Learning Application Benchmark

Andreas Koch, Gabriel Dax, Michael Petry, Harvey Gomez, Amir Raoofy, Urvij Saroliya, Max Ghiglione, Gianluca Furano, Martin Werner, Carsten Trinitis, Martin Langer

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

This paper presents reference implementations for a multitude of space applications from the Machine Learning Application Benchmark. Reference implementations include the respective model, its on-board hardware implementation, test scripts and final benchmarking results. In publishing these reference implementations, we make a significant contribution to the benchmark and provide more insight into the viability of on-board machine learning applications.

Original languageEnglish
Title of host publicationProceedings of the 2023 European Data Handling and Data Processing Conference for Space, EDHPC 2023
EditorsMaris Tali, Max Ghiglione
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9789090379241
DOIs
StatePublished - 2023
Event2023 European Data Handling and Data Processing Conference for Space, EDHPC 2023 - Juan-Les-Pins, France
Duration: 2 Oct 20236 Oct 2023

Publication series

NameProceedings of the 2023 European Data Handling and Data Processing Conference for Space, EDHPC 2023

Conference

Conference2023 European Data Handling and Data Processing Conference for Space, EDHPC 2023
Country/TerritoryFrance
CityJuan-Les-Pins
Period2/10/236/10/23

Keywords

  • FPGA
  • Machine learning
  • benchmark
  • datasets
  • neural networks
  • power consumption

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