Author

Jurn-Gyu Park

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Preprint Aug 2026

Energy- and Memory-Efficient PEFT Methods for Personalized On-Device SLMs on Consumer GPUs

Results show that compact SLMs paired with PEFT provide a practical, energy-aware path to personalized on-device deployment, with the optimal method set by the dominant constraint: LoRA+ for energy and QLoRA for memory.

Kuanysh Akhmetzhanov, Jurn-Gyu Park · 0 citations

Jul 2026

Energy-Efficient GPU DVFS for Fine-Tuning of SLMs on Resource-constrained Embedded Devices

This work characterize the fine-tuning behavior of representative encoder-only SLMs of BERT variants, and autoregressive decoder-only SLMs of Pythia variants on GLUE benchmarks, and proposes a simple yet effective ML-based model selection that selects energy-optimal GPU DVFS settings on resource-constrained embedded platforms.

Jurn-Gyu Park, S. Zholdybayev, Aidar Amangeldi et al. · arXiv.org · 0 citations