Modeling the Energy Consumption of the HEVC Software Encoding Process using Processor events

TL;DR

This paper develops a simple model to estimate the energy consumption of HEVC software encoding using processor events, achieving high accuracy and enabling energy distribution analysis among encoding sub-processes.

Contribution

It introduces a novel energy estimation model based on processor events for HEVC encoding, with high accuracy and sub-process energy distribution capability.

Findings

Mean absolute percentage error of 5.36% in energy estimation

Model can estimate energy for complex presets using ultrafast preset data

Provides energy distribution among encoding sub-processes

Abstract

Developing energy-efficient video encoding algorithms is highly important due to the high processing complexities and, consequently, the high energy demand of the encoding process. To accomplish this, the energy consumption of the video encoders must be studied, which is only possible with a complex and dedicated energy measurement setup. This emphasizes the need for simple energy estimation models, which estimate the energy required for the encoding. Our paper investigates the possibility of estimating the energy demand of a HEVC software CPU-encoding process using processor events. First, we perform energy measurements and obtain processor events using dedicated profiling software. Then, by using the measured energy demand of the encoding process and profiling data, we build an encoding energy estimation model that uses the processor events of the ultrafast encoding preset to obtain the energy estimate for complex encoding presets with a mean absolute percentage error of 5.36% when averaged over all the presets. Additionally, we present an energy model that offers the possibility of obtaining energy distribution among various encoding sub-processes.