Michael Gerndt

Prof. Dr. Michael Gerndt is a Full Professor at the Chair of Computer Architecture and Parallel Systems, School of Informatics, Technische Universität München (TUM). His research focuses on cloud and IoT systems, high-performance computing (HPC), and performance analysis tools for parallel/distributed systems.

• Current projects: SEANERGYS, PlasmaPEPS, OpenCUBE, and MUNIQC-ATOMS
• Past projects: AutoTune, READEX, InvasIC, and CrossGrid

Research Highlights:

• Developed the Periscope Tuning Framework and iOMP (OpenMP extension for invasive computing)
• Pioneering work in performance analysis, energy efficiency, and resource management in HPC and cloud systems
• Focus on AI-driven cloud operations, quantum-HPC integration, and hardware accelerators for machine learning

Scientific Awards:

• Outstanding Paper Award, IEEE SC2 Symposium (2017)

Teaching Contributions:

• Lectures: Parallel Programming Systems, Advanced Computer Architecture, Cloud Computing
• Lab courses: Efficient Programming of Multicore Processors, IoT Sensor Nodes
• Seminars: Hardware Accelerators for AI, Quantum Computing Integration

Education & Career: PhD in Computer Science (1989, University of Bonn), postdoc at University of Vienna (1990-1991), habilitation at TUM (1998), Professor at TUM since 2000.