Work in Progress: Increasing Schedulability via on-GPU Scheduling

GPUs are increasingly needed to run a variety of tasks in embedded systems, from object recognition to conver-sational chat. Some of these tasks are safety-critical, real-time tasks, where completing each by its deadline is essential for system safety. To meet the practical constraints of real-world...

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Bibliographic Details
Published inProceedings / IEEE Real-Time and Embedded Technology and Applications Symposium pp. 422 - 425
Main Authors Bakita, Joshua, Anderson, James H.
Format Conference Proceeding
LanguageEnglish
Published IEEE 06.05.2025
Subjects
Contracts
Costs
Embedded systems
Graphics processing units
Object recognition
Parallel processing
Real-time systems
Safety
Schedules
Scheduling
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Summary:GPUs are increasingly needed to run a variety of tasks in embedded systems, from object recognition to conver-sational chat. Some of these tasks are safety-critical, real-time tasks, where completing each by its deadline is essential for system safety. To meet the practical constraints of real-world systems, these tasks much also be run efficiently. Unfortunately, current techniques to schedule GPU-using tasks onto a single GPU while respecting deadlines impart high overheads, leading to inefficiency and substantial capacity loss during formal analysis. We address this problem by moving GPU scheduling from the CPU to the GPU. Our approach limits overheads, increasing the proportion of CPU tasks which can meet their deadlines by as much as 12.1% while increasing available GPU capacity.
ISSN:2642-7346
DOI:10.1109/RTAS65571.2025.00016