Multisource Software on Multicore Automotive ECUs—Combining Runnable Sequencing With Task Scheduling

Monot, Aurelien; Navet, Nicolas; Bavoux, Bernard; Simonot-Lion, Françoise

doi:10.1109/tie.2012.2185913

Cited by 89 publications

(68 citation statements)

References 14 publications

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“…Round Robin) are used in realtime systems, due to their predictability. But dynamic schedulers, where the execution order is defined on-line are under research currently [13]. Important task parameters for hard real-time systems, such as control systems, are the start time and deadline of a task as well as the worst case execution time.…”

Section: Processing Structure and Essentialsmentioning

confidence: 99%

“…Thus, the higher the level of automation, the more computational power is required by the control function implemented on an Electronic Control Unit (ECU). A conservative implementation approach is the one function per ECU, which leads to a decentralized architecture and a high number of ECUs [13] especially when a fail-operational behavior is required. Consequently, the vehicle's power consumption will significantly increase.…”

Section: Introductionmentioning

confidence: 99%

“…Consequently, the vehicle's power consumption will significantly increase. To solve this problem, multi-core ECUs are considered to replace single-core platforms in automotive domains [13]. The deployment of multi-core ECUs will improve the computing performance by parallel computation of different driving functions [11].…”

Section: Introductionmentioning

confidence: 99%

“…To further increase the computing performance, a distribution of the computing workload of one control function on a number of processor cores can be implemented. This idea is inspired by software development, where one task is parti-316 heft 4-5.2018 [9] tioned into smaller sub-tasks and allocated to different computing resources [1,13].…”

Section: Introductionmentioning

confidence: 99%

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Concepts for improved availability and computational power in automated driving

Grubmüller

Stettinger

Nešić

et al. 2018

Elektrotech. Inftech.

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Automated vehicles are required to operate on highways and in complex urban scenarios. To safely handle these complex environmental influences, sophisticated automated driving functions demand a high availability of all involved components in combination with increased computational power. Particular multi-core platforms are deployed to cope with these demands. To achieve higher system availability for SAE level 3 and higher, fail operational concepts from system level down to Microcontroller Unit (MCU) level are needed. These concepts include hardware as well as software requirements and are discussed in this paper. For an increased computing performance, the idea and further the model of a parallel computation method for driving functions and their control algorithms is introduced. For that a stabilizing controller is implemented on different cores of the multi-core processor. Finally, this resulting closed-loop system is modeled as a hybrid system which will serve as an input for further stability analysis.Keywords: fail-operational; parallel computation; waveform relaxation; multi-core processor Konzepte für höhere Verfügbarkeit und Rechenleistung im Bereich autonomes Fahren. Autonome Fahrzeuge sollen in Zukunft auf

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Section: Processing Structure and Essentialsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Concepts for improved availability and computational power in automated driving

Grubmüller

Stettinger

Nešić

et al. 2018

Elektrotech. Inftech.

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“…determined during design time) into cores since it is less complex and more predictable than dynamic resource allocation [8]. The runnables in automotive systems are usually confined with hard realtime constraints.…”

Section: Introductionmentioning

confidence: 99%

Energy-Aware Resource Allocation in Multi-mode Automotive Applications with Hard Real-Time Constraints

Dziurzański

Indrusiak

2016

2016 IEEE 19th International Symposium on Real-Time Distributed Computing (ISORC)

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ReuseUnless indicated otherwise, fulltext items are protected by copyright with all rights reserved. The copyright exception in section 29 of the Copyright, Designs and Patents Act 1988 allows the making of a single copy solely for the purpose of non-commercial research or private study within the limits of fair dealing. The publisher or other rights-holder may allow further reproduction and re-use of this version -refer to the White Rose Research Online record for this item. Where records identify the publisher as the copyright holder, users can verify any specific terms of use on the publisher's website. TakedownIf you consider content in White Rose Research Online to be in breach of UK law, please notify us by emailing eprints@whiterose.ac.uk including the URL of the record and the reason for the withdrawal request. Energy-aware Resource Allocation in Multi-mode Automotive Applications with Hard Real-Time ConstraintsPiotr Dziurzanski, Amit Kumar Singh and Leandro Soares Indrusiak Department of Computer Science, University of York, Deramore Lane, Heslington, York, YO10 5GH, UK.{Piotr.Dziurzanski, Amit.Singh, Leandro.Indrusiak}@york.ac.ukAbstract-This paper presents an energy aware resource allocation approach that benefits from modal nature of hardreal time systems under consideration. The modal nature of the considered applications made it possible to decrease the number of active cores consuming high power in certain modes or to switch into core states with lower power consumption, which lead to considerable energy savings while still not violating any of the timing constraints. For the considered automotive use case, the number of required cores has been decreased by up to 75% in a particular mode and relatively low amount of data is to be migrated during the mode change. The trade-off between the amount of data to be migrated and energy dissipation in the subsequent state is also analysed.

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Parallelizing highly complex engine management systems

Kienberger

Schmidhuber²,

Saad

et al. 2017

Concurrency and Computation

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Summary The automotive industry seeks to include more and more features in its vehicles. For this purpose, the necessary policy shift towards multi‐core technology is in full swing. To eventually exploit the extra processing power, there is much additional effort needed for coping with the tremendously increased complexity. This is largely due to the elaborate parallelization process that spans a vast search space. Consequently, there is a strong need for innovative methods and appropriate tools for the migration of legacy single‐core software. We use the results of a data dependency analysis performed on AUTOSAR system descriptions to determine advantageous partitions as well as initial task‐to‐core mappings. Afterwards, the extracted information serves as input for the simulation within a multi‐core timing tool suite. Here, the initial solution is evaluated with respect to proper scheduling and metrics like cross‐core communication rates, communication latencies, or core load distribution. A subsequent optimization process improves the initial solution and enables a comparative assessment. To demonstrate the benefit, we substantially expand a previous case study by applying our approach to two complex engine management systems and by showing the advantages compared to a parallelization process without preceding dependency analysis and initial partition/mapping suggestions.

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Multisource Software on Multicore Automotive ECUs—Combining Runnable Sequencing With Task Scheduling

Cited by 89 publications

References 14 publications

Concepts for improved availability and computational power in automated driving

Concepts for improved availability and computational power in automated driving

Energy-Aware Resource Allocation in Multi-mode Automotive Applications with Hard Real-Time Constraints

Parallelizing highly complex engine management systems

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