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New HiDVFS scheduler optimizes real-time embedded system performance

By PulseAugur Editorial · [1 sources] ·

Researchers have developed HiDVFS, a novel hierarchical multi-agent DVFS scheduler designed for real-time OpenMP DAG workloads on multicore embedded systems. This system addresses the challenge of leakage power by incorporating per-core, temperature-aware control and prioritizing deadlines alongside thermal limits. HiDVFS utilizes distinct agents for profiling, thermal management, and task prioritization, trained with a makespan-focused reward and a calibrated conformal shield for predicted response times. Benchmarks on various platforms demonstrate significant improvements in makespan, energy reduction, and deadline adherence compared to existing methods. AI

IMPACT This research introduces advanced scheduling techniques that could improve the efficiency and reliability of AI workloads running on embedded systems.

RANK_REASON Academic paper detailing a new scheduling algorithm. [lever_c_demoted from research: ic=1 ai=0.7]

Read on arXiv cs.AI →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

New HiDVFS scheduler optimizes real-time embedded system performance

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Academic paper detailing a new scheduling algorithm. [lever_c_demoted from research: ic=1 ai=0.7]
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COVERAGE [1]

  1. arXiv cs.AI TIER_1 English(EN) · Mohammad Pivezhandi, Abusayeed Saifullah, Ali Jannesari ·

    HiDVFS: Hierarchical Multi-Agent DVFS for Real-Time OpenMP DAG Workloads

    arXiv:2601.06425v2 Announce Type: replace-cross Abstract: Leakage power in multicore embedded systems now rivals dynamic power, so DVFS schedulers must respect deadlines and thermal limits, not just average makespan. Existing heuristics lack per-core, temperature-aware control an…

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