Erich Strohmaier is a Senior Scientist and Group Lead of the Performance and Algorithms Research group at the Lawrence Berkeley National Laboratory. His main interests are in performance characterization, evaluation, modeling, and prediction for HPC systems and large scale scientific workflows. He is involved in the analysis of advanced-computer architectures and parallel programming paradigms, classification of kernels and programming patterns for scientific computational kernels. His recent work is on the analysis and optimization of data-intensive large scale scientific workflows and the application of machine learning for predicting their behavior and performance. He has a Dr. in Theoretical Physics from the University of Heidelberg, Germany. Strohmaier was awarded the 2008 ACM Gordon Bell Prize for parallel processing research in algorithmic innovation and was named a Fellow of the ISC Conference in 2017. He is a member of ACM, IEEE, and APS.
Performance Analysis and Optimization