Cube, which is used as performance report explorer for Scalasca and Score-P, is a generic tool for displaying a multi-dimensional performance space consisting of following dimensions: performance metric, call path, system resources. Each dimension can be represented as a tree, where the non-leaf nodes can be collapsed or expanded to achieve the desired level of granularity. CUBEGUI is a graphical component, which allows the manual and visual exploring of the performance measurement result, the cube profile. Its plugin-based architecture promotes extensibility, allowing for the seamless integration of additional analysis capabilities through dedicated plugins. This kind of sophisticated data analysis is now being revolutionized by artificial intelligence. AI is increasingly demonstrating its power across a wide range of human activities, often yielding surprising and impressive outcomes. By analyzing vast amounts of text+data, AI models learn to understand the world in a profound way, extending beyond the mere memorization of facts. They begin to grasp the deeper meaning and connections between things, much like humans do, developing a nuanced comprehensive of how the world works. Join us now for this highly interesting topic.

• Development of the method to describe performance data in form as a prompt for the LLW
• Demonstration of the possibility to detect typical performance issues such as load imbalance using LLM
• Developing a a CubeGUI plugin to provide the interface and the automation of the developed approach
• Investigation of possible limitations of the approac