Toward compiler optimization of distributed real-time processes

Younis, Mohamed; Marlowe, Thomas J.; Tsai, Grace; Stoyenko, Alexander D.

doi:10.1109/iceccs.1996.558328

Cited by 4 publications

(2 citation statements)

References 16 publications

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“…It is also possible that the task set remains schedulable after the optimization, but the original analysis does not hold. Past research effort has focused on ensuring that compiler optimizations are safe (e.g., (Marlowe 15-18 Jun 1992;Younis et al 21-25 Oct 1996)), and techniques for reducing code size without affecting the real-time constraints (e.g., ) In contrast, we take the view that if the task parameters turn out to be worse off, then the analysis should be robust enough to tolerate some deterioration. Obviously, no analysis can permit an arbitrary deterioration of parameters and consideration of higher deterioration leads to more pessimistic results in the analysis.…”

Section: Introductionmentioning

confidence: 99%

Robust and sustainable schedulability analysis of embedded software

AnandMadhukar

LeeInsup

2008

SIGPLAN Not.

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For real-time systems, most of the analysis involves efficient or exact schedulability checking. While this is important, analysis is often based on the assumption that the task parameters such as execution requirements and inter-arrival times between jobs are known exactly. In most cases, however, only a worst-case estimate of these quantities is available at the time of analysis. It is therefore imperative that schedulability analysis hold for better parameter values (Sustainable Analysis). On the other hand, if the task or system parameters turn out to be worse off, then the analysis should tolerate some deterioration (Robust Analysis). Robust analysis is especially important, because the implication of task schedulability is often weakened in the presence of optimizations that are performed on its code, or dynamic system parameters.In this work, we define and address sustainability and robustness questions for analysis of embedded real-time software that is modeled by conditional real-time tasks. Specifically, we show that, while the analysis is sustainable for changes in the task such as lower job execution times and increased relative deadlines, it is not the case for code changes such as job splitting and reordering. We discuss the impact of these results in the context of common compiler optimizations, and then develop robust schedulability techniques for operations where the original analysis is not sustainable. AbstractFor real-time systems, most of the analysis involves efficient or exact schedulability checking. While this is important, analysis is often based on the assumption that the task parameters such as execution requirements and inter-arrival times between jobs are known exactly. In most cases, however, only a worst-case estimate of these quantities is available at the time of analysis. It is therefore imperative that schedulability analysis hold for better parameter values (Sustainable Analysis). On the other hand, if the task or system parameters turn out to be worse off, then the analysis should tolerate some deterioration (Robust Analysis). Robust analysis is especially important, because the implication of task schedulability is often weakened in the presence of optimizations that are performed on its code, or dynamic system parameters.In this work, we define and address sustainability and robustness questions for analysis of embedded real-time software that is modeled by conditional real-time tasks. Specifically, we show that, while the analysis is sustainable for changes in the task such as lower job execution times and increased relative deadlines, it is not the case for code changes such as job splitting and reordering. We discuss the impact of these results in the context of common compiler optimizations, and then develop robust schedulability techniques for operations where the original analysis is not sustainable.

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Section: Introductionmentioning

confidence: 99%

Robust and sustainable schedulability analysis of embedded software

AnandMadhukar

LeeInsup

2008

SIGPLAN Not.

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“…Such transformations change the structure of the program significantly and require non-trivial adaptions of flow information. Marlowe et al reported on a case in which the application of several code transformations for reducing the average execution time had serious impacts on code timing and caused deadline misses (Marlowe and Masticola 1992;Younis et al 1996).…”

Section: Introductionmentioning

confidence: 99%

Transforming flow information during code optimization for timing analysis

2010

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The steadily growing embedded-systems market comprises many application domains in which real-time constraints must be satisfied. To guarantee that these constraints are met, the analysis of the worst-case execution time (WCET) of software components is mandatory. In general WCET analysis needs additional control-flow information, which may be provided manually by the user or calculated automatically by program analysis. For flexibility and simplicity reasons it is desirable to specify the flow information at the same level at which the program is developed, i.e., at the source level. In contrast, to obtain precise WCET bounds the WCET analysis has to be performed at machine-code level. Mapping and transforming the flow information from the source-level down to the machine code, where flow information is used in the WCET analysis, is challenging, even more so if the compiler generates highly optimized code.In this article we present a method for transforming flow information from source code to machine code. To obtain a mapping that is safe and accurate, flow information is transformed in parallel to code transformations performed by an optimizing compiler. This mapping is not only useful for transforming manual code annotations but also if platform-independent flow information is automatically calculated at the source level. We show that our method can be applied to every type of semantics-preserving code transformation. The precision of this flow-information transformation allows its users to calculate tight WCET bounds.

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