SC23 IXPUG BoF
Navigating Complexity: Achieving Performance Portability in the Evolving Landscape of Heterogeneous HPC Systems
Location: In-person at SC23, Denver, Colorado – room number 301-302-303
Date & Time: Wednesday, November 15, 2023 12:15-1:15 p.m. MST
Registration: https://sc23.supercomputing.org/attend/registration/
SC23 Session Page: https://sc23.supercomputing.org/presentation/?id=bof170&sess=sess345
Agenda:
12:15-12:20 p.m. Introductions
12:20-1:00 p.m. Panelist Presentations
12:20-12:30 p.m. Dr. Huda Ibeid, Intel Corporation
12:30-12:40 p.m. Dr. Venkatatram Vishwanath, Argonne National Laboratory
12:40-12:50 p.m. Dr. Zhao Zhang, Rutgers University
12:50-1:00 p.m. Dr. Anna Pietarila Graham, Los Alamos National Laboratory
1:00-1:15 p.m. Open Discussion and Q&A
Panelists:
- Dr. Huda Ibeid, Intel Corporation
- Huda Ibeid is an HPC Performance Architect at Intel, working on enabling Exascale computing. Prior to that, she was a postdoctoral researcher at the University of Illinois at Urbana–Champaign. She holds a Ph.D. in Computer Science from King Abdullah University of Science and Technology (KAUST). Her research interests lie broadly in the field of high-performance computing, with a particular emphasis on two areas: the development of performance models for parallel architectures and applications, as well as the development of scalable numerical algorithms for partial differential equations (PDEs). She is the recipient of the Google Women Techmakers Scholarship (2014) and Rising Stars in EECS (2019).
- Dr. Venkatatram Vishwanath, Argonne National Laboratory
- Venkatram Vishwanath is a computer scientist at Argonne National Laboratory. He is the Data Science Team Lead at the Argonne Leadership Computing Facility (ALCF). His current focus is on algorithms, system software, and workflows to facilitate data-centric applications on supercomputing systems. His interests include scientific applications, supercomputing architectures, parallel algorithms and runtimes, scalable analytics and collaborative workspaces. He has received best papers awards at venues including HPDC and LDAV, and a Gordon Bell finalist. Vishwanath received his Ph.D. in computer science from the University of Illinois at Chicago in 2009.
- Dr. Zhao Zhang, Rutgers University
- Dr. Zhao Zhang is an assistant professor in the Department of Electrical and Computer Engineering at the Rutgers University. Prior to that, Dr. Zhang was a computer scientist and led the machine learning group at Texas Advanced Computing Center (TACC). From 2014 to 2016, Dr. Zhang was a postdoc researcher at AMPLab, UC Berkeley and the data science fellow in Berkeley Institute for Data Science. Dr. Zhang received his Ph.D. from the Department of Computer Science at UChicago in 2014. Dr. Zhang has extensive experience in high performance computing (HPC) and big data systems. His recent research focus is the fusion of HPC and deep learning (DL) with a wide range of topics of optimization algorithm, I/O, architecture, and domain applications.
- Dr. Anna Pietarila Graham, Los Alamos National Laboratory
- Dr. Anna Pietarila Graham is the deputy group leader for HPC-ENV and the LANL Center of Excellence (CoE) Lead for Crossroads and El Capitan at the Los Alamos National Laboratory. Prior to LANL, she worked as a staff scientist in observational and computational solar physics at the Max Planck Institute for Solar System Research in Germany and the National Solar Observatory in Tucson, AZ, and as a research geophysicist focusing on depth imaging at Shearwater GeoServices in Houston, TX. Anna received her MSc in physics from Lund University, Sweden, and her Ph.D. in astrophysics from the University of Oslo, Norway.
Session Leaders:
- Clay Hughes, Sandia National Laboratories
- Nalini Kumar, Intel Corporation
- David Martin, Argonne National Laboratory
- Amit Ruhela, Texas Advanced Computing Center (TACC)
Session Organizers:
- Glenn Brook, Cornelis Networks
- Hatem Ltaief, King Abdullah University of Science & Technology
- Christopher Mauney, Los Alamos National Laboratory
General questions should be sent to This email address is being protected from spambots. You need JavaScript enabled to view it.