用处理器事件预测HEVC编码能耗，误差仅5.36%。
Modeling the Energy Consumption of the HEVC Software Encoding Process using Processor events
- 通过处理器事件建模编码能耗，无需复杂测量设备。
- 对复杂编码预设的能耗估计平均误差为5.36%。
- 可分解各编码子过程的能耗分布，适合能效优化研究者。
由于视频编码过程计算复杂度高，导致能耗巨大，开发节能编码算法至关重要。为此，必须研究编码器的能耗，但传统测量需复杂专用设备。本文提出一种基于处理器事件的简单能耗估算模型，用于预测HEVC软件编码的能耗。首先通过专业性能分析工具采集编码过程中的能量消耗与处理器事件数据；随后利用这些数据构建能耗估算模型，以超快速编码预设的处理器事件为基础，对其他复杂预设的能耗进行预测，平均绝对百分比误差为5.36%。此外，该模型还能揭示编码各子过程的能量分布情况，为能效优化提供支持。
原文摘要 · Abstract (English)
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.
Thank you to arXiv for use of its open access interoperability. PaperDance 不是 arXiv 官方产品；中文卡片由大模型生成，请以原文为准。