Related papers: Database Engines: Evolution of Greenness
Buildings consume 60% of global electricity. However, current building management systems (BMSs) are highly expensive and difficult to justify for small to medium-sized buildings. As such, the Internet of Things (IoT), which can monitor and…
Energy efficiency has a significant influence on user experience of battery-driven devices such as smartphones and tablets. The goal of an energy model for source code is to lay a foundation for the application of energy-saving techniques…
Climate change has become a major problem for humanity in the last two decades. One of the reasons that caused it, is our daily energy waste. People consume electricity in order to use home/work appliances and devices and also reach certain…
Energy consumption of Cloud data centers has been a major concern of many researchers, and one of the reasons for huge energy consumption of Clouds lies in the inefficient utilization of computing resources. Besides energy consumption,…
In today world, organizations like Google, Yahoo, Amazon, Facebook etc. are facing drastic increase in data. This leads to the problem of capturing, storing, managing and analyzing terabytes or petabytes of data, stored in multiple formats,…
The ICT sector, responsible for 2% of global carbon emissions, is under scrutiny calling for methodologies and tools to design and develop software in an environmentally sustainable-by-design manner. However, the software engineering…
The rapid digitization and the increasing use of emerging technologies such as AI models have significantly contributed to the emissions of computing infrastructure. Efforts to mitigate this impact typically focus on the infrastructure…
By providing unprecedented access to computational resources, cloud computing has enabled rapid growth in technologies such as machine learning, the computational demands of which incur a high energy cost and a commensurate carbon…
The demand in computing power has never stopped growing over the years. Today, the performance of the most powerful systems exceeds the exascale and the number of petascale systems continues to grow. Unfortunately, this growth also goes…
As demand for computing resources continues to rise, the increasing cost of electricity and anticipated regulations on carbon emissions are prompting changes in data center power systems. Many providers are now operating compute nodes in…
While the environmental impact of digitalization is becoming more and more evident, the climate crisis has become a major issue for society. For instance, data centers alone account for 2.7% of Europe's energy consumption today. A…
As sustainability takes center stage across businesses, green and energy-efficient choices are more crucial than ever. While it is becoming increasingly evident that software and the software industry are substantial and rapidly evolving…
The growth of machine learning (ML) models and associated datasets triggers a consequent dramatic increase in energy costs for the use and training of these models. In the current context of environmental awareness and global sustainability…
The energy consumption of deep learning models is increasing at a breathtaking rate, which raises concerns due to potential negative effects on carbon neutrality in the context of global warming and climate change. With the progress of…
Context: Large Language Models (LLMs) are increasingly used in modern software development, aiding in code generation, code completion, and refactoring through AI-powered assistants. While they accelerate development workflows, they often…
Modern RDBMSs support the ability to compress data using methods such as null suppression and dictionary encoding. Data compression offers the promise of significantly reducing storage requirements and improving I/O performance for decision…
Deep Learning has enabled many advances in machine learning applications in the last few years. However, since current Deep Learning algorithms require much energy for computations, there are growing concerns about the associated…
Scientific research in many fields routinely requires the analysis of large datasets, and scientists often employ workflow systems to leverage clusters of computers for their data analysis. However, due to their size and scale, these…
Monitoring energy behaviors in AI data centers is crucial, both to reduce their energy consumption and to raise awareness among their users which are key actors in the AI field. This paper shows a proof of concept of easy and lightweight…
Leadership computing facilities around the world support cutting-edge scientific research across a broad spectrum of disciplines including understanding climate change, combating opioid addiction, or simulating the decay of a neutron. While…