4 papers
On the Effectiveness of Proposed Techniques to Reduce Energy Consumption in RAG Systems: A Controlled Experiment
Zhinuan Guo, Chushu Gao, Justus Bogner
The rising energy demands of machine learning (ML), e.g., implemented in popular variants like retrieval-augmented generation (RAG) systems, have raised significant concerns about…
Green LLM Techniques in Action: How Effective Are Existing Techniques for Improving the Energy Efficiency of LLM-Based Applications in Industry?
Pelin Rabia Kuran, Rumbidzai Chitakunye, Vincenzo Stoico +2
The rapid adoption of large language models (LLMs) has raised concerns about their substantial energy consumption, especially when deployed at industry scale. While several techniq…
How Does Microservice Granularity Impact Energy Consumption and Performance? A Controlled Experiment
Yiming Zhao, Tiziano De Matteis, Justus Bogner
Context: Microservice architectures are a widely used software deployment approach, with benefits regarding flexibility and scalability. However, their impact on energy consumption…
On the Effectiveness of Microservices Tactics and Patterns to Reduce Energy Consumption: An Experimental Study on Trade-Offs
Xingwen Xiao, Chushu Gao, Justus Bogner
Context: Microservice-based systems have established themselves in the software industry. However, sustainability-related legislation and the growing costs of energy-hungry softwar…