5 papers
SEALing the Gap: A Reference Framework for LLM Inference Carbon Estimation via Multi-Benchmark Driven Embodiment
Priyavanshi Pathania, Rohit Mehra, Vibhu Saujanya Sharma +4
Large Language Models are rapidly gaining traction in software engineering, yet their growing carbon footprint raises pressing sustainability concerns. While training emissions are…
Calculating Software's Energy Use and Carbon Emissions: A Survey of the State of Art, Challenges, and the Way Ahead
Priyavanshi Pathania, Nikhil Bamby, Rohit Mehra +5
The proliferation of software and AI comes with a hidden risk: its growing energy and carbon footprint. As concerns regarding environmental sustainability come to the forefront, un…
Assessing the Impact of Refactoring Energy-Inefficient Code Patterns on Software Sustainability: An Industry Case Study
Rohit Mehra, Priyavanshi Pathania, Vibhu Saujanya Sharma +3
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,…
Towards a Knowledge Base of Common Sustainability Weaknesses in Green Software Development
Priyavanshi Pathania, Rohit Mehra, Vibhu Saujanya Sharma +3
With the climate crisis looming, engineering sustainable software systems become crucial to optimize resource utilization, minimize environmental impact, and foster a greener, more…
Breaking the ICE: Exploring promises and challenges of benchmarks for Inference Carbon & Energy estimation for LLMs
Samarth Sikand, Rohit Mehra, Priyavanshi Pathania +5
While Generative AI stands to be one of the fastest adopted technologies ever, studies have made evident that the usage of Large Language Models (LLMs) puts significant burden on e…