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https://doi.org/10.1109/date.2...
Article . 2010 . Peer-reviewed
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Accurate timed RTOS model for transaction level modeling

Authors: Yonghyun Hwang; Gunar Schirner; Samar Abdi; Daniel D. Gajski;

Accurate timed RTOS model for transaction level modeling

Abstract

In this paper, we present an accurate timed RTOS model within transaction level models (TLMs). Our RTOS model, implemented on top of system level design language (SLDL), incorporates two key features: RTOS behavior model and RTOS overhead model. The RTOS behavior model provides dynamic scheduling, inter-process communication (IPC), and external communication for timing annotated user applications. While the RTOS behavior model is running, all RTOS events, such as context switch and interrupt handling, are passed to RTOS over- head model to adopt the overhead during system execution. Our RTOS overhead model has processor- and RTOS-specific pre-characterized overhead information to provide cycle approximate estimation. We demonstrate the applicability of our model using a multi-core platform executing a JPEG encoder. Experimental results show that the proposed RTOS model provides the high accuracy, 7% off compared to on-board measurements while simulating at speeds close to the reference C code.

Country
Croatia
Keywords

scheduling; transaction processing; JPEG encoder; RTOS behavior model; RTOS speciflc precharacterized overhead information; accurate timed RTOS model; cycle approximate estimation; dynamic scheduling; interprocess communication; multicore platform; system level design language; transaction level modeling; Application software; Context modeling; Delay estimation; Dynamic scheduling; Performance analysis; Scalability; Software performance; Switches; System-level design; Timing

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
Green