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Minisymposium Presentation
Breaking Limits: Scaling HPC Performance Engineering Horizons to Maximize Potential
Presenter
Dr. Sarah Neuwirth holds the professorship for "High Performance Computing and its Applications" at Johannes Gutenberg University Mainz from October 2023. This position is associated with the direction of the High Performance Computing division in the Center for Data Processing at JGU. Previously, Dr. Neuwirth was deputy head of the research group "Modular Supercomputing and Quantum Computing" at Goethe University Frankfurt. In 2018, she completed her PhD in computer science at Heidelberg University. For her outstanding work in high performance computing, she was awarded the "2023 PRACE Ada Lovelace Award for HPC" and the "ZONTA Science Award 2019". Her research interests include parallel file and memory systems, modular supercomputing, performance engineering, high performance computing and networking, benchmarking, parallel I/O, and communication protocols. Sarah has worked on numerous research collaborations including working with: the Jülich Supercomputing Centre (DEEP Project Series, EUPEX), the Oak Ridge National Laboratory, and the Virginia Polytechnic Institute and State University. Her projects are funded by the European Commission, DOE, ORAU, and ORNL.
Description
In the ever-evolving realm of high-performance computing (HPC), and in an era where data-driven insights and complex simulations are essential, pushing the boundaries of performance is paramount to scientific discovery and technological advancement. This presentation will delve into innovative approaches to scale HPC performance engineering horizons and unlock the full potential of computational capabilities. Strategies for optimizing hardware and software utilization, identifying and mitigating performance bottlenecks, and implementing cutting-edge techniques to maximize scalability, efficiency, and productivity will be explored. Using the example of tracking the data path, this presentation will illustrate how monitoring the movement of data from computation to storage has the potential to break through performance barriers and propel research and development efforts to new heights.