Phoeni6: A systematic approach for evaluating the energy consumption of neural networks

IF 5.7 3区计算机科学 Q1 COMPUTER SCIENCE, HARDWARE & ARCHITECTURE

Sustainable Computing-Informatics & Systems Pub Date : 2025-08-06 DOI:10.1016/j.suscom.2025.101172

Antônio Oliveira-Filho , Wellington Silva-de-Souza , Carlos Alberto Valderrama Sakuyama , Samuel Xavier-de-Souza

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引用次数: 0

Abstract

This paper presents Phoeni6, a systematic approach for assessing the energy consumption of neural networks while upholding the principles of fair comparison and reproducibility. Phoeni6 offers a comprehensive solution for managing energy-related data and configurations, ensuring portability, transparency, and coordination during evaluations. The methodology automates energy evaluations through containerized tools, robust database management, and versatile data models. In the first case study, the energy consumption of AlexNet and MobileNet was compared using raw and resized images. Results showed that MobileNet is up to 6.25% more energy-efficient for raw images and 2.32% for resized datasets, while maintaining competitive accuracy levels. In the second study, the impact of image file formats on energy consumption was evaluated. BMP images reduced energy usage by up to 30% compared to PNG, highlighting the influence of file formats on energy efficiency. These findings emphasize the importance of Phoeni6 in optimizing energy consumption for diverse neural network applications and establishing sustainable artificial intelligence practices.

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Phoeni6：一种评估神经网络能耗的系统方法

本文介绍了Phoeni6，这是一种在坚持公平比较和可重复性原则的情况下评估神经网络能耗的系统方法。Phoeni6为管理能源相关数据和配置提供了全面的解决方案，确保了评估过程中的可移植性、透明度和协调性。该方法通过容器化工具、健壮的数据库管理和通用的数据模型自动化能源评估。在第一个案例研究中，AlexNet和MobileNet的能耗使用原始和调整大小的图像进行比较。结果表明，MobileNet在保持具有竞争力的精度水平的同时，对原始图像的能效提高了6.25%，对调整大小的数据集的能效提高了2.32%。在第二项研究中，评估了图像文件格式对能耗的影响。与PNG相比，BMP图像减少了高达30%的能源使用，突出了文件格式对能源效率的影响。这些发现强调了Phoeni6在优化各种神经网络应用的能耗和建立可持续的人工智能实践方面的重要性。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Sustainable Computing-Informatics & Systems COMPUTER SCIENCE, HARDWARE & ARCHITECTUREC-COMPUTER SCIENCE, INFORMATION SYSTEMS

CiteScore

10.70

自引率

4.40%

发文量

142

期刊介绍： Sustainable computing is a rapidly expanding research area spanning the fields of computer science and engineering, electrical engineering as well as other engineering disciplines. The aim of Sustainable Computing: Informatics and Systems (SUSCOM) is to publish the myriad research findings related to energy-aware and thermal-aware management of computing resource. Equally important is a spectrum of related research issues such as applications of computing that can have ecological and societal impacts. SUSCOM publishes original and timely research papers and survey articles in current areas of power, energy, temperature, and environment related research areas of current importance to readers. SUSCOM has an editorial board comprising prominent researchers from around the world and selects competitively evaluated peer-reviewed papers.