Bounding Shared-Stack Usage in Systems with Offsets and Precedences

Bohlin, Markus; Hänninen, Kaj; Mäki-Turja, Jukka; Carlson, Jan; Nolin, Mikael

doi:10.1109/ecrts.2008.29

Cited by 13 publications

(22 citation statements)

References 15 publications

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“…The authors demonstrate that the algorithm in [13] for the assignment of the highest possible preemption thresholds after priorities are assigned to tasks is also optimal with respect to stack usage (again, with the assumption of a given priority assignment). When scheduling offsets are known, they can be exploited to further improve the analysis and the definition of the threshold levels, as discussed in [9] [4]. Also, [5] provides an analysis of the use of non-preemptive regions for the purpose of improving schedulability (considering scheduling overheads).…”

Section: State Of the Artmentioning

confidence: 98%

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Optimizing stack memory requirements for real-time embedded applications

Zeng

Natale

Zhu

2012

Proceedings of 2012 IEEE 17th International Conference on Emerging Technologies &Amp; Factory Automation (ETFA 2012)

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In the development of some real-time embedded applications, especially systems-on-chip, an efficient use of RAM memory is as important as the effective scheduling of the computation resources. The design problem is to find a schedulable solution that fits within the memory budget. In a real-time concurrent system, preemption plays an important role in the exploration of these tradeoffs. Several schemes, including preemption thresholds and non-preemption groups, have been developed to improve schedulability and saving stack memory space by selectively disabling preemption. However, the design synthesis problem for such systems and protocols is still an open problem. We target at the efficient assignment of the scheduling parameters for systems scheduled according to these policies in several cases of practical interest, including those that are compliant with automotive standards.

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Section: State Of the Artmentioning

confidence: 98%

“…In [15], the blocking time limit is computed using Equation (4), which operates at the task level with the conservative assumption that the task is fully preemptive. In this case, the order of the runnables inside a task is irrelevant.…”

Section: Optimal Preemption Threshold and Execution Order Assignmentsmentioning

confidence: 99%

Optimizing stack memory requirements for real-time embedded applications

Zeng

Natale

Zhu

2012

Proceedings of 2012 IEEE 17th International Conference on Emerging Technologies &Amp; Factory Automation (ETFA 2012)

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show abstract

“…Hänninen et al [19] presented an approximate stack analysis method to derive a safe upper bound on the shared stack usage, in offset-based hybrid (interrupt-and time-driven) fixed priority preemptive systems. Finally, Bohlin et al [12] introduced some techniques to exploit precedence and offset relations between tasks, thus limiting preemption patterns and bounding the amount of shared-stack usage.…”

Section: Related Workmentioning

confidence: 99%

“…Indeed, now blocking may occur for two reasons: i) the real local resources and ii) the pseudo-resources. In the first case, Equation (12) still holds and the feasibility can be verified using the methods introduced in [7]. In the second case, the blocking can be calculated in a similar way, and the ceiling for each pseudo-resource is computed in such a way that the system feasibility is always guaranteed.…”

Section: Integrating With Stack Resource Policy (Srp)mentioning

confidence: 99%

Reducing stack with intra-task threshold priorities in real-time systems

Yao

Buttazzo

2010

Proceedings of the Tenth ACM International Conference on Embedded Software

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In the design of hard real-time systems, the feasibility of the task set is one of the primary concerns. However, in embedded systems with scarce resources, optimizing resource usage is equally important. In particular, the RAM is highly expensive in terms of chip space, and it heavily impacts the cost of the final product.In this paper, we address the problem of reducing the stack usage of a set of sporadic tasks with timing and resource constraints, running on a uni-processor system. With respect to other approaches available in the literature, this work considers each task consisting of a set of functions (or subjobs), each characterized by a maximum stack requirement. This makes it possible to prohibit arbitrary preemptions through a dynamic priority protocol that reduces the overall system stack usage. Resource synchronization is also considered and, an extension of the Stack Resource Policy is presented to arbitrate the access to mutually exclusive resources while reducing the overall stack space. Simulations are performed on randomly generated task sets to evaluate the efficiency of the proposed method with respect to existing approaches.

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“…The authors demonstrate that the algorithm in [15] for the assignment of the maximum preemption thresholds is also optimal with respect to stack usage. When scheduling offsets are known, they can be exploited to further improve the analysis and the definition of the threshold levels, as discussed in [12] [5].…”

Section: Introductionmentioning

confidence: 99%

Minimizing stack memory for hard real-time applications on multicore platforms

Dong

Zeng

2014

Design, Automation &Amp; Test in Europe Conference &Amp; Exhibition (DATE), 2014

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Multicore platforms are increasingly used in realtime embedded applications. In the development of such applications, an efficient use of RAM memory is as important as the effective scheduling of software tasks. Preemption Threshold Scheduling is a well-known technique for controlling the degree of preemption, possibly improving system schedulability, and allowing savings in stack space. In this paper, we target at the optimal mapping of tasks to cores and the assignment of the scheduling parameters for systems scheduled with preemption thresholds. We formulate the optimization problems using Mixed Integer Linear Programming framework, and propose an efficient heuristic as an alternative. We demonstrate the efficiency and quality of both approaches with extensive experiments using random systems as well as two industrial case studies.978-3-9815370-2-4/DATE14/ c 2014 EDAA

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Bounding Shared-Stack Usage in Systems with Offsets and Precedences

Cited by 13 publications

References 15 publications

Optimizing stack memory requirements for real-time embedded applications

Optimizing stack memory requirements for real-time embedded applications

Reducing stack with intra-task threshold priorities in real-time systems

Minimizing stack memory for hard real-time applications on multicore platforms

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