Memory allocation for low-power real-time embedded microcontroller: a case study

Zhishen Zhang, Yuwen Shen, Binqi Sun, Tomasz Kloda, Marco Caccamo

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

Abstract

Memory allocation of instructions and data can affect the program execution speed. This paper tests various memory-intensive benchmarks under different memory allocations on a Cortex-M4-based microcontroller and solves the allocation problem using integer linear programming.

Original languageEnglish
Title of host publication2022 IEEE 27th International Conference on Emerging Technologies and Factory Automation, ETFA 2022
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781665499965
DOIs
StatePublished - 2022
Event27th IEEE International Conference on Emerging Technologies and Factory Automation, ETFA 2022 - Stuttgart, Germany
Duration: 6 Sep 20229 Sep 2022

Publication series

NameIEEE International Conference on Emerging Technologies and Factory Automation, ETFA
Volume2022-September
ISSN (Print)1946-0740
ISSN (Electronic)1946-0759

Conference

Conference27th IEEE International Conference on Emerging Technologies and Factory Automation, ETFA 2022
Country/TerritoryGermany
CityStuttgart
Period6/09/229/09/22

Keywords

  • Cortex-M
  • core-coupled memory
  • real-time

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