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Call String Sensitivity for Hardware-Based Hybrid WCET Analysis

Dreyer, Boris ; Hochberger, Christian ; Wegener, Simon (2021)
Call String Sensitivity for Hardware-Based Hybrid WCET Analysis.
In: IEEE Embedded Systems Letters, 14 (2)
doi: 10.1109/LES.2021.3134489
Article, Bibliographie

Abstract

Many embedded systems operate under real-time conditions. For them, the worst case execution time (WCET) is a crucial information to check whether the software implementation meets the requirements. In modern microcontrollers, this WCET can often no longer be evaluated statically since these processors include too many unpredictable components (cache, bus arbitration, … ,). Here, hybrid WCET estimation comes into play, where measured traces are used to empirically compute bounds for the WCET. For meaningful estimations, it is required to put each measured segment into a corresponding execution context. In this contribution, we present a method that allows to gather such context-sensitive statistics online in hardware. This enables arbitrary long measurement intervals with a precision that compares to state-of-the-art offline tools.

Item Type: Article
Erschienen: 2021
Creators: Dreyer, Boris ; Hochberger, Christian ; Wegener, Simon
Type of entry: Bibliographie
Title: Call String Sensitivity for Hardware-Based Hybrid WCET Analysis
Language: English
Date: 10 December 2021
Publisher: IEEE
Journal or Publication Title: IEEE Embedded Systems Letters
Volume of the journal: 14
Issue Number: 2
DOI: 10.1109/LES.2021.3134489
Abstract:

Many embedded systems operate under real-time conditions. For them, the worst case execution time (WCET) is a crucial information to check whether the software implementation meets the requirements. In modern microcontrollers, this WCET can often no longer be evaluated statically since these processors include too many unpredictable components (cache, bus arbitration, … ,). Here, hybrid WCET estimation comes into play, where measured traces are used to empirically compute bounds for the WCET. For meaningful estimations, it is required to put each measured segment into a corresponding execution context. In this contribution, we present a method that allows to gather such context-sensitive statistics online in hardware. This enables arbitrary long measurement intervals with a precision that compares to state-of-the-art offline tools.

Uncontrolled Keywords: Hardware, Tools, Context, Software, Real-time systems, Program processors, Microcontrollers, Code profiling, computer architecture, computer and information processing, embedded software, field programmable gate array, integrated circuits, real-time systems, reconfigurable architectures, software, worst-case execution time
Divisions: 18 Department of Electrical Engineering and Information Technology
18 Department of Electrical Engineering and Information Technology > Institute of Computer Engineering
18 Department of Electrical Engineering and Information Technology > Institute of Computer Engineering > Computer Systems Group
Date Deposited: 12 Apr 2024 10:10
Last Modified: 12 Apr 2024 10:10
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