Using software-defined performance counters to construct a GPU power consumption model

A. N. Gulin, S. M. Staroletov

Altai State Technical University

Abstract: In the modern world, processor performance and energy efficiency play a key role in computer system design. Along with CPUs, GPUs are powerful computing devices used for computer graphics processing, machine learning, and more. Processors are equipped with built-in sensors accessible through specialized tools. The chip of a modern video card can operate in a fairly wide range of frequencies and power limits (PLs). Very often, when solving a computational task or rendering a scene, the video card can operate more optimally, without wasting excess power, which can significantly save energy on labor-intensive tasks. Therefore, it is important for a set of given tasks to find such parameters where the ratio of useful work per watt will be maximum. After conducting a large number of experiments, one can learn to predict the dependence of such a target function on the parameters. This paper examines obtaining current GPU parameter values using various tools. We present results of collecting raw data from NVIDIA GPUs and the subsequent construction of an optimal power consumption model.

Keywords: GPU, NVAPI, power consumption model, GPU sensors

Language: English

DOI: 10.15514/ISPRAS-2025-37(4)-16