Author

Oana Balmau

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#machine learning Preprint Sep 2026

A principled approach for energy-efficient training via phase-aware GPU frequency tuning

PAFT, a phase-aware, dynamically adaptable GPU frequency tuning system that reduces energy consumption of training workloads with minimal performance overhead, achieving energy savings of up to 46% with an average overhead of 4%.

Miguel Braga, Júlio Pinto, Rahma Nouaji et al. · 0 citations

Jul 2026

DeltaServe: Host-Agnostic Co-Serving of Inference and Fine-Tuning for LLMs

DeltaServe is presented, a host-agnostic co-serving design that converts this idle inference capacity into LoRA fine-tuning throughput while preserving inference service-level objectives (SLOs).

Jiaxuan Chen, Jianshu She, Ye Yuan et al. · arXiv.org · 1 citation