Featured Speakers: Damian Rouson, Dan Gunter, Hannah Klion
Date: July 15, 2025
Time: 11 a.m. – 12 p.m.
Where: 59-4102. Virtual: Zoom Available
Three Short Talks:
The Problem Is Not Fortran
Presented by Damian Rouson (Group Lead, Computer Languages and Systems Software Group, AMCR)
We always did feel the same, We just saw it from a different point of view: Computer Science in Support of Team Science
Presented by Dan Gunter (Group Lead, Usable Data Systems Group, SciData)
For over two decades, the groups currently named Usable Data Systems, Sustainable Software Engineering, and Integrated Data Systems have worked as unit to meet a broad variety of challenges in cutting-edge science and engineering, such as creating highly used data pipelines and portals, building production engineering modeling software across multiple labs and universities, and pioneering the use of user experience practices in science. This talk will provide a sampling of the projects that the groups are currently working on and describe some of the lessons learned along the way.
Zooming in on multi-scale ocean dynamics with GPUs
Presented by Hannah Klion (Center for Computational Science and Engineering, AMCR)
In many geophysical systems, small-scale processes drive global dynamics. The naive approach to simulating these systems – resolving small-scale processes in the entire large domain – can be computationally infeasible. I will discuss my work toward high-accuracy, multi-scale simulations of Earth’s oceans. Small-scale (<1km) processes are expected to be important to global oceanic flows, but cannot be captured in global ocean simulations. I lead development of REMORA, a new performance-portable regional ocean model that can run on any computer, from a laptop to a GPU-accelerated supercomputer. REMORA will couple to global ocean simulations in order to add refinement in regions of particular interest. It is also able to run standalone, realistic simulations of coastal and open-ocean regions. Its additional capabilities, such as mesh refinement and tracer particles make it a particularly flexible tool in both standalone and coupled applications. I will discuss progress toward these goals as well as future directions.
Read more about our presenters below.
Date: July 16, 2025
Time: 2 p.m. – 3 p.m.
Where: In person at Shyh Wang Hall (Bldg 59, meet at the 3rd floor lobby)
RSVP in advance is required for this event. Only 50 spaces available per tour.
Date: July 18, 2025
Time: 10 a.m. – 11 a.m.
Where: In person at Shyh Wang Hall (Bldg 59, meet at the 3rd floor lobby)
RSVP in advance is required for this event. Only 50 spaces available per tour.
Senior Scientist and the Group Lead for the Computer Languages and Systems Software (CLaSS) Group at Berkeley Lab. He also holds an Adjunct Faculty position at San Diego State University. He researches parallel programming and deep learning, teaches tutorials in parallel Fortran and UPC++, and leads the development of the Caffeine parallel runtime library, the Fiats deep learning library, and several other open-source software projects. He has prior research experience in simulating turbulent flows in multiphase, quantum, and magnetohydrodynamic media.
Dan Gunter leads the Usable Data Systems (UDS) group in the Scientific Data Division (SciData). Dan's interests include usability for scientific interfaces and workflows, data management and data processing pipelines in heterogeneous environments, software engineering for distributed multidisciplinary scientific teams, and building usable interfaces to enable scientific exploration. He has led software efforts in projects for multiple domains, collaborating with science divisions at LBNL as well as other research institutions in the DOE and academia. Dan enjoys riding bicycles, roasting coffee beans and drinking the results, and watching sumo.
Hannah Klion is a computational research scientist in the Center for Computational Science and Engineering. Her research focuses on developing high-performance, multi-scale simulations of oceanic and astrophysical systems. She earned her BS in Physics from Caltech (2015) and her PhD in Physics from UC Berkeley in 2021. At UC Berkeley, she was a Department of Energy Computational Science Graduate Fellow and a UC Berkeley Physics Theory Fellow.
