MMAE Seminar by Dr. Lorena Barba—Algorithms versus Hardware and Productivity versus Performance: A Journey in Computational Biophysics

Armour College of Engineering’s Department of Mechanical, Materials, and Aerospace Engineering will welcome Dr. Lorena Barba, a professor of mechanical and aerospace engineering at the George Washington University in Washington, DC, to present a lecture, “Algorithms versus Hardware and Productivity versus Performance: A Journey in Computational Biophysics.”

The seminar will take place on Tuesday, February 8, 2022, from 12:45-1:45 p.m. in RE-104.

Contact Elena Magnus at for the seminar details.

Early in my research, I was motivated by the idea that new algorithms are as much or more important than improvements in computer hardware. In fact, the faster the computer, the more important the speed of algorithms. An algorithm that features prominently in our work is the fast multipole method, invented more than 30 years ago, and cited as one of the Top 10 Algorithms of the 20th Century. It was introduced in astrophysics, to simulate the interaction of many bodies under a gravitational potential. Via the integral formulation of partial differential equations, it finds application in acoustics, electromagnetics, fluid dynamics, and biophysics. We have been developing capability to model protein electrostatics using boundary integral formulations and fast multipole methods, adding hardware acceleration with GPUs. Extending the model, we studied physical settings with applications to biosensors, like interaction of proteins with charged surfaces, and resonance of localized electron-cloud vibrations known as plasmons. The software development involved in this research is a story in itself, with an excursion into methodological questions of verification and validation, and reproducibility. In our latest work, we are able to compute the electrostatic solvation energy of a full-scale virus, while emphasizing a high-productivity and high-performance computational workflow. The idea is to integrate an easy-to-use Python interface with well-optimized computational kernels written in compiled languages. Researchers can run simulations interactively via Jupyter notebooks, enabling faster prototyping and analysis, at problem scales that are competitive with high-performance computing scenarios. Modern research software efforts today aim for the union of high performance and high researcher productivity, which our work exemplifies in the context of computational biophysics.

Lorena A. Barba is a professor of mechanical and aerospace engineering at the George Washington University in Washington, DC. She holds a PhD in aeronautics from the California Institute of Technology and BSc/PEng degrees in mechanical engineering from Universidad Técnica Federico Santa Marí¬a, Chile. Her research interests include computational fluid dynamics, high-performance computing, computational biophysics, and animal flight. In 2012, she received the NSF CAREER award, and was named CUDA Fellow by NVIDIA. An international leader in computational science and engineering, she is also a long-standing advocate of open source software for science and education. Dr. Barba was a member (2014–2021) of the Board of Directors for NumFOCUS, a 501(c)3 public charity in the United States that supports and promotes world-class, innovative, open-source scientific software. She is also an expert in research reproducibility, and was a member of the National Academies study committee on Reproducibility and Replicability in Science, which released its report in 2019. She served as Reproducibility Chair for the SC19 conference, is Editor-in-Chief and track editor for Reproducible Research in IEEE Computing in Science Engineering, was founder and Associate Editor-in-Chief for the Journal of Open Source Software, and is Editor-in-Chief of The Journal of Open Source Education. She is also well known for her open educational resources and courses, and was a recipient of the 2016 Leamer-Rosenthal Award for Open Social Sciences under the Leaders in Education category. In 2017 she was nominated and received an honorable mention in the Open Education Awards for Excellence of the Open Education Consortium. She was General Chair of the global JupyterCon and was named Jupyter Distinguished Contributor in 2020.