2026-10-06T11:33:53Z https://api.figshare.com/v2/oai

oai:figshare.com:article/33968398 2026-09-22T17:56:50Z category_28987 item_type_3 month_year_09_2026

Research Data for LLM-Based GPU Power, Performance, and Thermal Footprint Prediction Experiments Ravi Kumar (25091359) High performance computing GPU power management energy-efficient deep learning power capping thermal-aware computing hardware characterization sustainable computing. <p dir="ltr">This dataset supports a study of <b>GPU power management, energy efficiency, and hardware-aware power prediction for deep-learning workloads</b>. The research characterizes five deep-learning architectures across NVIDIA Tesla T4 and Quadro GV100 GPUs, evaluates large-language-model-based GPU power predictions, and investigates the effects of hardware power capping on power consumption, throughput, thermal behavior, and energy per completed training step. The study also includes controlled T4 power-cap experiments and cross-hardware validation on NVIDIA L4 GPUs. The data are intended to support the reproducibility and verification of the experimental results reported in the associated research article.</p> 2026-09-22T17:56:50Z Dataset Dataset 10.6084/m9.figshare.33968398.v1 https://figshare.com/articles/dataset/Research_Data_for_LLM-Based_GPU_Power_Performance_and_Thermal_Footprint_Prediction_Experiments/33968398 CC BY 4.0