Generalized Execution Time Estimation

Andreas Rechberger; Eugen Brenner

doi:10.1109/SIES.2018.8442107

Generalized Execution Time Estimation

Andreas Rechberger, Eugen Brenner

Institute of Technical Informatics (4480)

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Abstract

While developing embedded devices a significant challenge is to choose the appropriate computing architecture. Especially during early design stages providing measurable metric on the performance demands to implement a specified algorithm is required. Usually this includes a large amount of target dependency, like the chosen micro-controller platform. This work aims on providing a generalized method to estimate the processing time of a dedicated algorithm, when being run on a variety of hardware choices. The focus is on a fast exploration of the hardware design space in order to provide guidance for selecting a suitable processing platform.

Original language	English
Title of host publication	2018 IEEE 13th International Symposium on Industrial Embedded Systems, SIES 2018 - Proceedings
Publisher	Institute of Electrical and Electronics Engineers
ISBN (Print)	9781538641552
DOIs	https://doi.org/10.1109/SIES.2018.8442107
Publication status	Published - 20 Aug 2018
Event	13th IEEE International Symposium on Industrial Embedded Systems, SIES 2018 - Graz, Austria Duration: 6 Jun 2018 → 8 Jun 2018

Conference

Conference	13th IEEE International Symposium on Industrial Embedded Systems, SIES 2018
Country	Austria
City	Graz
Period	6/06/18 → 8/06/18

Keywords

algorithm
compiler
data flow
performance estimation

ASJC Scopus subject areas

Computer Science Applications
Hardware and Architecture
Industrial and Manufacturing Engineering

Access to Document

10.1109/SIES.2018.8442107

Link to publication in Scopus

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Rechberger, A & Brenner, E 2018, Generalized Execution Time Estimation. in 2018 IEEE 13th International Symposium on Industrial Embedded Systems, SIES 2018 - Proceedings., 8442107, Institute of Electrical and Electronics Engineers, 13th IEEE International Symposium on Industrial Embedded Systems, SIES 2018, Graz, Austria, 6/06/18. https://doi.org/10.1109/SIES.2018.8442107

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