Energy and Emissions of Machine Learning on Smartphones vs. the Cloud

IF 3.5 2区生物学 Q2 BIOCHEMISTRY & MOLECULAR BIOLOGY

ACS Chemical Biology Pub Date : 2024-01-25 DOI:10.1145/3624719

David Patterson, Jeffrey M. Gilbert, Marco Gruteser, Efren Robles, Krishna Sekar, Yong Wei, Tenghui Zhu

引用次数: 0

Abstract

A Google case study finds ML training in the cloud can reduce CO 2 e emissions up to 100×.

查看原文本刊更多论文

智能手机与云计算机器学习的能耗与排放对比

谷歌的一项案例研究发现，云计算中的 ML 培训可将二氧化碳排放量减少 100 倍。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

求助全文

约1分钟内获得全文求助全文

来源期刊

ACS Chemical Biology 生物-生化与分子生物学

CiteScore

7.50

自引率

5.00%

发文量

353

审稿时长

3.3 months

期刊介绍： ACS Chemical Biology provides an international forum for the rapid communication of research that broadly embraces the interface between chemistry and biology. The journal also serves as a forum to facilitate the communication between biologists and chemists that will translate into new research opportunities and discoveries. Results will be published in which molecular reasoning has been used to probe questions through in vitro investigations, cell biological methods, or organismic studies. We welcome mechanistic studies on proteins, nucleic acids, sugars, lipids, and nonbiological polymers. The journal serves a large scientific community, exploring cellular function from both chemical and biological perspectives. It is understood that submitted work is based upon original results and has not been published previously.