collaborators

5 papers

cs.DC2026

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

Mohammad Pivezhandi, Abusayeed Saifullah, Ali Jannesari

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 l…

cs.AI2026

ZeroDVFS: Zero-Shot LLM-Guided Core and Frequency Allocation for Embedded Platforms

Mohammad Pivezhandi, Mahdi Banisharif, Abusayeed Saifullah +1

Dynamic voltage and frequency scaling (DVFS) and task-to-core allocation are critical for thermal management and balancing energy and performance in embedded systems. Existing appr…

cs.LG2026

GraphPerf-RT: A Graph-Driven Performance Model for Hardware-Aware Scheduling of OpenMP Codes

Mohammad Pivezhandi, Mahdi Banisharif, Saeed Bakhshan +2

Autonomous AI agents on embedded platforms require real-time, risk-aware scheduling under resource and thermal constraints. Classical heuristics struggle with workload irregularity…

cs.DC2026

Feature-Aware Task-to-Core Allocation in Embedded Multi-core Platforms via Statistical Learning

Mohammad Pivezhandi, Abusayeed Saifullah, Prashant Modekurthy

Optimizing task-to-core allocation can substantially reduce power consumption in multi-core platforms without degrading user experience. However, existing approaches overlook criti…

cs.LG2026

FlowRL: Flow-Augmented Few-Shot Reinforcement Learning for Semi-Structured Sensor Data

Mohammad Pivezhandi, Abusayeed Saifullah

Reinforcement learning (RL) in few-shot scenarios with limited sensor data is challenging due to insufficient training samples, particularly in applications like Dynamic Voltage an…