An ILP approach for mapping AUTOSAR runnables on multi-core architectures

Saidi, Salah Eddine; Cotard, Sylvain; Chaaban, Khaled; Marteil, Kevin

doi:10.1145/2693433.2693439

Cited by 14 publications

(5 citation statements)

References 3 publications

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“…Monot et al [24] proposed an algorithm for sequencing and scheduling runnables for multicore ECUs. Saidi et al [25] studied the runnable-to-core mapping problem using the integer linear programming (ILP) technique. Kehr et al [26] developed a method for migrating a legacy AUTOSAR application to a multicore processor while minimizing energy consumption.…”

Section: Related Workmentioning

confidence: 99%

AUTOSAR Runnable Periods Optimization for DAG-Based Complex Automobile Applications

Daeho¹,

Kim

2020

Applied Sciences

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When developing an automobile control application, its scheduling parameters as well as the control algorithm itself should be carefully optimized to achieve the best control performance from given computing resources. Moreover, since the wide acceptance of the AUTOSAR standard, where finer-granular scheduling entities (called runnables) rather than the traditional real-time tasks are used, the number of scheduling parameters to be optimized is far greater than the traditional task-based control systems. Hence, due to the vast problem space, it is not feasible to reuse existing time-consuming search-based optimization methods. With this motivation, this paper presents an analytical codesign method for deciding runnable periods that minimize given control cost functions. Our solution approach, based on the Lagrange multiplier method, can find optimized runnable periods in polynomial times due to its analytical nature. Moreover, our evaluation results for synthesized applications with varying complexities show that our method performs significantly better (12% to 59% of control cost reductions) than a state-of-the-art evolutionary algorithm. To the best of our knowledge, this study is one of the first attempts to find runnable periods that maximize a given system’s control performance.

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Section: Related Workmentioning

confidence: 99%

AUTOSAR Runnable Periods Optimization for DAG-Based Complex Automobile Applications

Daeho¹,

Kim

2020

Applied Sciences

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“…The following pseudo-code illustrates how the ILP logical assertions are synthesized from the input models. The pseudo-code contains three main parts: i) the first part in Line (2) identifies the different deployment cases of the cause-effect chains over a set of nodes M , ii) the second part in Line (3)(4)(5), checks the schedulability of a deployable cause-effect chain φ against the reaction or age delays [13] and returns its schedulability matrix M Γ , with values true if schedulable and f alse if not schedulable. For a schedulable φ, Line (5) constructs a conjunctive ILP expression that indicates the existence of at least one schedulable φ that satisfies the end-to-end requirement imposed on γ, and iii) the last part in Line (7) asserts the ILP logical OR expressions for each γ. for all φ ∈ Φ do 4: assert(depExp) 8: end for VI.…”

Section: Timing Constraintsmentioning

confidence: 99%

“…It is a type of bin-packing problem, and therefore finding an optimal solution, in the general case, is NP-hard [4]. The methods to solve such problems can be exact [5], which means solutions are guaranteed to be optimal, or heuristic, which deliver near-optimal solutions [6] [7]. Exact methods such as Integer Linear Programming (ILP) [8] have been used widely in several resource optimization problems.…”

Section: Introductionmentioning

confidence: 99%

Power-Aware Allocation of Fault-Tolerant Multirate AUTOSAR Applications

Mahmud

Rodríguez-Navas

Faragardix³

et al. 2018

2018 25th Asia-Pacific Software Engineering Conference (APSEC)

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Software-to-hardware allocation plays an important role in the development of resource-constrained automotive embedded systems that are required to meet timing, reliability and power requirements. This paper proposes an Integer Linear Programming optimization approach for the allocation of faulttolerant embedded software applications that are developed using the AUTOSAR standard. The allocation takes into account the timing and reliability requirements of the multirate software applications and the heterogeneity of their execution platforms. The optimization objective is to minimize the total power consumption of the applications that are distributed over multiple computing units. The proposed approach is evaluated using a range of different software applications from the automotive domain, which are generated using the real-world automotive benchmark. The evaluation results indicate that our proposed allocation approach is effective while meeting the timing, reliability, and power requirements of the considered automotive software applications.

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“…This is apparent in [27], [28], where ILP formulations are proposed for mapping and scheduling runnables on multi-core and distributed automotive architectures, respectively. The approaches are demonstrated for a small automotive applications, although results clearly show that a basic ILP formulation does not scale to complex applications with hundreds or thousands of runnables that are individually mapped and scheduled.…”

Section: Related Workmentioning

confidence: 99%

Contention-Free Execution of Automotive Applications on a Clustered Many-Core Platform

Becker

Dasari

Nicolic

et al. 2016

2016 28th Euromicro Conference on Real-Time Systems (ECRTS)

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Abstract-Next generations of compute-intensive real-time applications in automotive systems will require more powerful computing platforms. One promising power-efficient solution for such applications is to use clustered many-core architectures. However, ensuring that real-time requirements are satisfied in the presence of contention in shared resources, such as memories, remains an open issue.This work presents a novel contention-free execution framework to execute automotive applications on such platforms. Privatization of memory banks together with defined access phases to shared memory resources is the backbone of the framework. An Integer Linear Programming (ILP) formulation is presented to find the optimal time-triggered schedule for the on-core execution as well as for the access to shared memory. Additionally a heuristic solution is presented that generates the schedule in a fraction of the time required by the ILP. Extensive evaluations show that the proposed heuristic performs only 0.5% away from the optimal solution while it outperforms a baseline heuristic by 67%. The applicability of the approach to industrially sized problems is demonstrated in a case study of a software for Engine Management Systems.

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An ILP approach for mapping AUTOSAR runnables on multi-core architectures

Cited by 14 publications

References 3 publications

AUTOSAR Runnable Periods Optimization for DAG-Based Complex Automobile Applications

AUTOSAR Runnable Periods Optimization for DAG-Based Complex Automobile Applications

Power-Aware Allocation of Fault-Tolerant Multirate AUTOSAR Applications

Contention-Free Execution of Automotive Applications on a Clustered Many-Core Platform

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