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AI-enabled features built on LLMs and agentic workflows are difficult to test, debug, and reproduce, especially for product-focused software engineers without a machine learning background. We present the AI Toolkit plugin for JetBrains…
Artificial Intelligence (AI) is used to create more sustainable production methods and model climate change, making it a valuable tool in the fight against environmental degradation. This paper describes the paradox of an energy-consuming…
The Internet of Things adoption in the manufacturing industry allows enterprises to monitor their electrical power consumption in real time and at machine level. In this paper, we follow up on such emerging opportunities for data…
Energy consumption reserves a large portion of the budget for school buildings. At the same time, the students that use such facilities are the adults of the years to come and thus, should they embrace energy-aware behaviors, then…
Energy transparency is a concept that makes a program's energy consumption visible, from hardware up to software, through the different system layers. Such transparency can enable energy optimizations at each layer and between layers, and…
The ever increasing demand for ML-driven intelligence in a wide spectrum of domains has led to ubiquity of GPUs. At the same time, GPUs are notorious for their power consumption needs and often dominate power allocation in a typical ML…
Power consumption is a major concern in data centers and HPC applications, with GPUs typically accounting for more than half of system power usage. While accurate power measurement tools are crucial for optimizing the energy efficiency of…
The static estimation of the energy consumed by program executions is an important challenge, which has applications in program optimization and verification, and is instrumental in energy-aware software development. Our objective is to…
The rapid adoption of artificial intelligence (AI) and machine learning (ML) has generated growing interest in understanding their environmental impact and the challenges associated with designing environmentally friendly ML-enabled…
The concern about global warming increased the interest in the energy efficiency of computer applications. Assuming power is constant, the general trend is that faster programs consume less energy, thus optimizing a program for speed would…
Score-P is a measurement infrastructure originally designed for the analysis and optimization of the performance of HPC codes. Recent extensions of Score-P and its associated tools now also allow the investigation of energy-related…
Energy consumption is a growing concern in several fields, from mobile devices to large data centers. Developers need detailed data on the energy consumption of their software to mitigate consumption issues. Previous approaches have a…
Advances in technologies like artificial intelligence and metaverse have led to a proliferation of software systems in business and everyday life. With this widespread penetration, the carbon emissions of software are rapidly growing as…
In particular, large-scale deep learning and artificial intelligence model training uses a lot of computational power and energy, so it poses serious sustainability issues. The fast rise in model complexity has resulted in exponential…
Energy consumption analysis of IT-controlled systems can play a major role in minimising the overall energy consumption of such IT systems, during the development phase, or for optimisation in the field. Recently, a precise energy analysis…
Power awareness is fast becoming immensely important in computing, ranging from the traditional High Performance Computing applications, to the new generation of data centric workloads. In this work we describe our efforts towards a power…
Hybrid intelligence aims to enhance decision-making, problem-solving, and overall system performance by combining the strengths of both, human cognitive abilities and artificial intelligence. With the rise of Large Language Models (LLM),…
The integration of renewable energy sources increases the complexity in mantaining the power grid. In particular, the highly dynamic nature of generation and consumption demands for a better utilization of energy resources, which seen the…
High-performance computing (HPC) and supercomputing are critical in Artificial Intelligence (AI) research, development, and deployment. The extensive use of supercomputers for training complex AI models, which can take from days to months,…
In recent years,Large Language Models (LLMs) have significantly improved in generating high-quality code, enabling their integration into developers' Integrated Development Environments (IDEs) as code assistants. These assistants, such as…