Heike Jagode is a Research Associate Professor and Lead of the ICL Performance Group at the Innovative Computing Laboratory, University of Tennessee, with over a decade focused on high-performance computing and advanced architecture optimization. She develops tools and methodologies for performance analysis, tuning, and energy-efficient execution of parallel scientific applications, translating research into practical improvements for large-scale workflows. Her PhD work under Jack Dongarra introduced dataflow programming paradigms to convert NWChem Coupled Cluster methods into task-based executions, demonstrating superior scalability and resource utilization versus coarse-grain approaches. Heike’s background spans European and U.S. HPC centers, from EPCC at Edinburgh to Dresden’s ZIH, giving her a rare blend of domain science and systems-level expertise. She is notable for bridging computational chemistry algorithms with next-generation runtime systems like StarPU and PaRSEC, making legacy codes more adaptable to modern task schedulers. Based in Knoxville, she continues to lead performance-focused research that directly impacts how scientific codes exploit heterogeneous, energy-constrained supercomputing systems.
9 years of coding experience
21 years of employment as a software developer
Master of Science - MS, High-Performance Computing, Master of Science - MS, High-Performance Computing at The University of Edinburgh
Master of Science - MS, Applied Mathematics, Master of Science - MS, Applied Mathematics at Hochschule Mittweida - University of Applied Science
Doctor of Philosophy - PhD, Computer Science, Doctor of Philosophy - PhD, Computer Science at University of Tennessee, Knoxville
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