A Case for Sustainability and Environment Friendliness in Software Development and Architecture Decisions by Taking Energy-Efficient Design Decisions
November 03, 2023 Β· Declared Dead Β· π arXiv.org
"No code URL or promise found in abstract"
Evidence collected by the PWNC Scanner
Authors
Kaushik Dutta, Debra Vandermeer
arXiv ID
2311.01680
Category
cs.SE: Software Engineering
Citations
4
Venue
arXiv.org
Last Checked
4 months ago
Abstract
IT power usage is a significant concern. Data center energy consumption is estimated to account for 1% to 1.5% of all energy consumption worldwide. Hardware designers, data center designers, and other members of the IT community have been working to improve energy efficiency across many parts of the IT infrastructure; however, little attention has been paid to the energy efficiency of software components. Indeed, energy efficiency is currently not a common performance criteria for software. In this work, we attempt to quantify the potential for gains in energy efficiency in software, based on a set of examples drawn from common, everyday decisions made by software developers and enterprise architects. Our results show that there is potential for significant energy savings through energy-conscious choices at software development and selection time, making the software and IT artifact sustainable and environment friendly.
Community Contributions
Found the code? Know the venue? Think something is wrong? Let us know!
π Similar Papers
In the same crypt β Software Engineering
R.I.P.
π»
Ghosted
R.I.P.
π»
Ghosted
Microservices: yesterday, today, and tomorrow
π
π
The Cartographer
A Survey of Machine Learning for Big Code and Naturalness
R.I.P.
π»
Ghosted
An Overview on Smart Contracts: Challenges, Advances and Platforms
R.I.P.
π»
Ghosted
Slither: A Static Analysis Framework For Smart Contracts
R.I.P.
π»
Ghosted
ContractFuzzer: Fuzzing Smart Contracts for Vulnerability Detection
Died the same way β π» Ghosted
R.I.P.
π»
Ghosted
Federated Learning: Strategies for Improving Communication Efficiency
R.I.P.
π»
Ghosted
In-Datacenter Performance Analysis of a Tensor Processing Unit
R.I.P.
π»
Ghosted
Deep Convolutional Neural Networks for Computer-Aided Detection: CNN Architectures, Dataset Characteristics and Transfer Learning
R.I.P.
π»
Ghosted