ParaRMS algorithm: A parallel implementation of rate monotonic scheduling algorithm using OpenMP

Dashora, Rajnish; Bajaj, Harsh P.; Dube, Akshat; M, Narayanamoorthy

doi:10.1109/icaee.2014.6838557

Cited by 2 publications

(3 citation statements)

References 5 publications

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“…Also, it can be lower than the actual achievable bound given a specific system, and does not fit our concept. (A1: All processors are allocated to single CPUs based on period, A3: There is no data dependence among processes, A4: The execution time for each process is constant) [39]. To reliably perform schedulability, we verified with the exact schedulability method [40], [41] and determined it as the most accurate and reliable method for rate monotonic verification.…”

Section: Implementation and Analysismentioning

confidence: 99%

The Migration of Engine ECU Software From Single-Core to Multi-Core

Moon

Kim

et al. 2021

IEEE Access

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As multiple functions have been added to single-core-based engine electronic control units (ECUs) in vehicles, automotive researchers and manufacturers have actively studied multi-core architecture for engine ECUs. Multi-core architecture can provide load balancing and parallelism that can meet the requirements of international organization standard (ISO) 26262. However, since real-world engine ECUs have the most complex automotive open system architecture (AUTOSAR)-based control logic and datasets among automotive ECUs, developing multi-core-based engine ECUs is a substantial amount of work. Thus, automotive researchers and manufacturers will need new methodologies for multi-core-based engine ECUs. In this paper, we focus on designing a multi-core migration methodology and applying it to a real-world AUTOSAR-based engine ECU from HYUNDAI. We verify its practicability and enhanced performance. In conclusion, through connection with other automotive domain ECUs, it is demonstrated that a multi-core engine ECU using our migration technology can be applied in real-world automotive vehicles, leading to a significant improvement in performance.INDEX TERMS Multi-core-based engine system, shared data inconsistency, core load balancing, memory and offset optimization technology.

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Section: Implementation and Analysismentioning

confidence: 99%

The Migration of Engine ECU Software From Single-Core to Multi-Core

Moon

Kim

et al. 2021

IEEE Access

View full text Add to dashboard Cite

show abstract

“…Open MP [10][11][12][13][14][15][16][17] sample, sample, sample, sample ----if number of cores is 4.…”

Section: Overview Of Open Mpmentioning

confidence: 99%

“…Measure the various performance parameters (Like Total Execution time or Run time, Cache memory size, hit ratio, CPU utilization, etc) Step5: Identify the concurrency in the above application code (Independent sub tasks) Step6: Write the parallel code using parallel programming languages (Open MP) Step7: Run the above code using multicore machines Step8: Measure the various performance parameters (Like Total Execution time or Run time, Cache memory size, hit ratio, CPU utilization, etc) Step9: Rerun the above code using various thread size or processors cores (2,4,8,16, 32, n) and make a comparative analysis table.…”

Section: Overview Of Open Mpmentioning

confidence: 99%