Dr. James Kress

Ph.D. Graduate, March 2020
CIS Department
University of Oregon

Area Exam: [PDF]
Dissertation: [PDF]
Google Scholar page

Bio

James completed a Ph.D. in Computer Science at the University of Oregon in March 2020. His dissertation focused on tradeoffs between two types forms of in situ processing, called in-line and in-transit. He considered many tradeoffs, with special foci on efficiency and execution time. With respect to efficiency, James' dissertation showed a counterintuitive result: adding more resources (i.e., in transit) can lead to cost savings, because it enables visualization algorithms to sidestep scalability issues. Prior to graduation, James began a concurrent role as a staff computer scientist at Oak Ridge National Laboratory, and he continued in this role post-graduation.

James received his Masters in 2017 from the University of Oregon in Computer Science. He received his BS in 2013 from Boise State University in Computer Science, with a minor in Political Science. James received the Outstanding Graduating Senior award from the Boise State Department of Computer Science in recognition of his dedication and scholastic achievement. His past service has paper review for various conferences, a position on the Graduate Student Advisory Board at the University of Oregon, a student member on the University of Oregon Tuition and Fee Advisory Board, founding member then Vice President and then President of the Graduate Student Association, University of Oregon's first campus wide Graduate Student Association.

First-Author Publications


Comparing Time-to-Solution for In Situ Visualization Paradigms at Scale
James Kress, Matt Larsen, Jong Choi, Mark Kim, Matthew Wolf, Norbert Podhorszki, Scott Klasky, Hank Childs, and David Pugmire
IEEE Symposium on Large Data Analysis and Visualization (LDAV), Salt Lake City, Utah, October 2020

[PDF]     [BIB]

Opportunities for Cost Savings with In Transit Visualization
James Kress, Matt Larsen, Jong Choi, Mark Kim, Matthew Wolf, Norbert Podhorszki, Scott Klasky, Hank Childs, and David Pugmire
ISC High Performance Conference, Frankfurt, Germany, June 2020

[PDF]     [BIB]

Comparing the Efficiency of In Situ Visualization Paradigms at Scale
James Kress, Matthew Larsen, Jong Choi, Mark Kim, Matthew Wolf, Norbert Podhorszki, Scott Klasky, Hank Childs, and David Pugmire
ISC High Performance Conference, Frankfurt, Germany, June 2019

[PDF]     [BIB]

Binning Based Data Reduction for Vector Field Data of a Particle-In-Cell Fusion Simulation
James Kress, Jong Choi, Scott Klasky, Michael Churchill, Hank Childs, and David Pugmire
ISC High Performance 2018 International Workshops (Lecture Notes in Computer Science), Frankfurt, Germany, June 2018

[PDF]     [BIB]

Preparing for In Situ Processing on Upcoming Leading-edge Supercomputers
James Kress, Randy Michael Churchill, Scott Klasky, Mark Kim, Hank Childs, and Dave Pugmire
Supercomputing Frontiers and Innovations, December 2016

[LINK]     [BIB]

Visualization and Analysis Requirements for In Situ Processing for a Large-Scale Fusion Simulation Code
James Kress, Dave Pugmire, Scott Klasky, and Hank Childs
SC16 Workshop on In Situ Infrastructures for Enabling Extreme-scale Analysis and Visualization (ISAV-16), Salt Lake City, UT, November 2016

[PDF]     [BIB]

Loosely Coupled In Situ Visualization: A Perspective on Why it's Here to Stay
James Kress, Scott Klasky, Norbert Podhorszki, Jong Choi, Hank Childs, and Dave Pugmire
SC15 Workshop on In Situ Infrastructures for Enabling Extreme-scale Analysis and Visualization (ISAV-15), Austin, TX, November 2015

[PDF]     [BIB]

A Visualization Pipeline for Large-Scale Tractography Data
James Kress, Erik Anderson, and Hank Childs
IEEE Symposium on Large Data Analysis and Visualization (LDAV), Chicago, IL, October 2015

[PDF]     [BIB]

A Novel Graphical User Interface for High-Efficacy Modeling of Human Perceptual Similarity Opinions
James Kress, Songhua Xu, Georgia Tourassi
SPIE Medical Imaging, Orlando, FL, March 2013

[PDF]     [BIB]
Additional Publications


A Terminology for In Situ Visualization and Analysis Systems
Community paper with 57 authors, including Hank Childs (lead author), James Kress, Matt Larsen, and Sudhanshu Sane
International Journal of High Performance Computing Applications (IJHPCA), November 2020

[PDF]     [BIB]

Visualization as a Service for Scientific Data
Community paper led by David Pugmire with 20 authors, including CDUX members James Kress, Nicole Marsaglia, and Hank Childs
Smoky Mountains Computational Sciences and Engineering Conference, Kingsport, TN, August 2020

[PDF]     [BIB]

Performance-Portable Particle Advection with VTK-m
David Pugmire, Abhishek Yenpure, Mark Kim, James Kress, Robert Maynard, Hank Childs, and Bernd Hentschel
Eurographics Symposium on Parallel Graphics and Visualization (EGPGV), Brno, Czech Republic, June 2018

[PDF]     [BIB]

Performance Modeling of In Situ Rendering
Matthew Larsen, Cyrus Harrison, James Kress, David Pugmire, Jeremy S. Meredith, and Hank Childs
The International Conference for High Performance Computing, Networking, Storage, and Analysis (SC16), Salt Lake City, UT, November 2016
Best Paper Finalist

[PDF]     [BIB]

VTK-m: Accelerating the Visualization Toolkit for Massively Threaded Architectures
Ken Moreland, Chris Sewell, William Usher, Li-ta Lo, Jeremy Meredith, Dave Pugmire, James Kress, Hendrik Schroots, Kwan-Liu Ma, Matt Larsen, Hank Childs, Chun-Ming Chen, Robert Maynard, and Berk Geveci
Computer Graphics and Applications, May/June 2016

[LINK]     [BIB]

Visualization and Analysis for Near-Real-Time Decision Making in Distributed Workflows
David Pugmire, James Kress, Jong Choi, Scott Klasky, Tahsin Kurc, Randy Churchill, Matthew Wolf, Greg Eisenhauer, Hank Childs, Kesheng Wu, Alex Sim, Junmin Gu, and Jonathan Low
IPDPS Workshop on High Performance Data Analysis and Visualization (HPDAV), Chicago, IL, May 2016

[PDF]     [BIB]

Towards Scalable Visualization Plugins for Data Staging Workflows
David Pugmire, James Kress, Jeremy Meredith, Norbert Podhorszki, Jong Choi, and Scott Klasky
SC14 Workshop on Big Data Analytics: Challenges, and Opportunities (BDAC-14), New Orleans, LA, November 2014

[PDF]     [BIB]