Introduction
The hardware team in Boeblingen develops the most powerful server systems in the world - in an international work environment with our partner labs in the USA, Israel and India. We are using modern verification methods and are continuously optimizing our development processes.

Your Role and Responsibilities
To ensure performance targets are met before the design data of the next generation of IBM z microprocessors is sent to the fab, a growing set of performance tests are performed pre-silicon in system-level simulations. However, as of now, the results of these tests are manually analyzed by the team of performance verification engineers.

The goal of this master thesis is to develop an automation solution for the analysis of the pre-silicon system-level performance regression results. It must assist the team of performance verification engineers in finding performance issues of next-generation IBM microprocessors the most efficient way.

1. The first step would be to thoroughly analyze the existing data set and performance metrics and to apply the previously mentioned ideas.
2. The solution then needs to be optimized to the pre-silicon performance regression use-case, e.g. by applying further data science methods and/or developing new scores.
3. Eventually, AI and/or machine learning techniques can be applied to make the solution adaptive to changes throughout the project, or over the course of several project, respectively.

• Study of computer science, electrical engineering, or a similar direction
• Good knowledge of programming, knowledge of a scripting language like Python
• Knowledge of data science, statistics, and machine learning
• Knowledge of development tools / technologies (e.g. git)
• AI knowledge
• English or German language

• First experience in developing hardware, and performance analysis.