Synchrotron light sources are advanced scientific facilities that enable imaging of materials with extremely high spatial and temporal resolutions, helping tens of thousands of researchers to carry out their groundbreaking research every year. Depending on the experimental setup, X-ray experiments at synchrotrons can generate massive amounts of scientific datasets. Iterative reconstruction algorithms are often the preferred method for recovering high-quality 2D/3D images from these datasets, however, their use has been limited to small/medium datasets due to their computational requirements.

In this talk, I will present high-performance optimization methods that we developed for tomographic and ptychographic iterative reconstruction techniques. These will include compute- and memory-centric parallelization techniques with a special focus on communication and data access pattern optimizations on many-core and heterogeneous architectures. I will also present our workflow system that provides an end-to-end X-ray image analysis pipeline between APS and ALCF. I will show the evaluation of our optimizations and workflow system with real-world medium/large scale experimental datasets.

Bio: Tekin Bicer

Tekin Bicer is a computer scientist at Data Science and Learning Division at Argonne National Laboratory. He also holds joint appointments in X-ray Science Division at Advanced Photon Source and Consortium for Advanced Science and Engineering at the University of Chicago. His research focuses on parallel and distributed systems, high-performance computing, programming models, and data science. He is currently working on large-scale runtime systems and machine-learning techniques that deal with data-intensive synchrotron radiation imaging problems. He has received several awards, including the Best Paper Award at SC'20, Top Recognition at SCinet Technology Challenge at SC'19, and the best paper nomination at CCGrid'14. He received both his Ph.D. and M.Sc. degrees from the Computer Science and Engineering Department at Ohio State University. He is a senior member of IEEE and ACM.

See upcoming and previous presentations at CS Seminar Series