|
Bio
Matt Larsen graduated with a Ph.D. in Computer and Information Science from the University of Oregon
in December of 2016.
Prior to graduation, Matt accepted a full-time
staff computer scientist position at Lawrence Livermore National Laboratory, and he
continued in this position after graduation.
Matt started the Ph.D. program in September 2013, and began
his concurrent role at LLNL in January 2016.
His research interests include computer graphics, GPU computing, portable performance, and scientific visualization.
Matt worked on two different research grants during his time at UO.
His first project was to contribute to the NSF SI2 GraviT project,
a ray tracing library for distributed-memory parallel environments.
Through this work, he developed a portably-performant ray tracer that
was competitive with industry standard ray tracers.
This work led Matt to his second project, funded by the Department of
Energy XVis grant.
With this project, Matt explored the boundaries of portable performance.
During his time at LLNL, Matt investigated questions on in situ rendering,
which played an important role in his thesis.
Matt's research experience was enhanced by two internships:
In 2014, he worked
on renderers in the EAVL library
at Oak Ridge Laboratory with Jeremy Meredith.
Then, in 2015, he worked
on lightweight in situ visualization systems
at Lawrence Livermore Lab with Eric Brugger.
Honors and Awards
- Nov. 2019: Awarded ISAV19 Best Paper
- Nov. 2018: Awarded ISAV18 Best Paper
- June 2016: Submission to SC16 selected as Best Paper Finalist
- Jan. 2016: Passed UO Oral Candidacy Exam with Distinction
- June 2015: Awarded UO's J. Donald Hubbard Scholarship
- Dec. 2014: Passed UO Directed Research Project Exam with Distinction
- June 2013: Graduated magna cum laude from California State University at Sacramento with a B.S. in Computer Science
First-Author Publications
Trigger Happy: Assessing the Viability of Trigger-Based In Situ Analysis
Matthew Larsen,
Cyrus Harrison, Terece L. Turton,
Sudhanshu Sane,
Stephanie Brink,
and Hank Childs
IEEE Symposium on Large Data Analysis and Visualization (LDAV), New Orleans, LA, October 2021
[PDF] [BIB]
|
A Flexible System For In Situ Triggers
Matt Larsen,
Amy Woods, Nicole Marsaglia, Ayan Biswas, Soumya Dutta, Cyrus Harrison, and
Hank Childs
ISAV 2018: In Situ Infrastructures for Enabling Extreme-scale Analysis and Visualization, Dallas, TX, November 2018
Best Paper
[PDF] [BIB]
|
The ALPINE In Situ Infrastructure: Ascending from the Ashes of Strawman
Matt Larsen,
James Ahrens, Utkarsh Ayachit, Eric Brugger,
Hank Childs,
Berk Geveci, and Cyrus Harrison
ISAV 2017: In Situ Infrastructures for Enabling Extreme-scale Analysis and Visualization, Denver, CO, November 2017
[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]
|
Optimizing Multi-Image Sort-Last Parallel Rendering
Matthew Larsen,
Ken Moreland, Chris Johnson, and
Hank Childs
IEEE Symposium on Large Data Analysis and Visualization (LDAV), Baltimore, MD, October 2016
[PDF] [BIB]
|
Strawman - A Batch In Situ Visualization and Analysis Infrastructure for Multi-Physics Simulation Codes
Matthew Larsen,
Eric Brugger,
Hank Childs,
Jim Eliot,
Kevin Griffin,
and Cyrus Harrison
SC15 Workshop on In Situ Infrastructures for Enabling Extreme-scale Analysis and Visualization (ISAV-15), Austin, TX, November 2015
[PDF] [BIB]
|
Volume Rendering Via Data-Parallel Primitives
Matthew Larsen,
Stephanie Labasan,
Paul Navratil, Jeremy Meredith,
and
Hank Childs
EuroGraphics Symposium on Parallel Graphics and Visualization (EGPGV), Cagliari, Italy, May 2015
[PDF] [BIB]
|
Ray-Tracing Within a Data Parallel Framework
Matthew Larsen,
Jeremy Meredith, Paul Navratil, and
Hank Childs
IEEE Pacific Visualization, Hangzhou, China, April 2015
[PDF] [BIB]
|
Additional Publications
Minimizing Development Costs for Efficient Many-Core Visualization Using MCD3
Kenneth Moreland, Robert Maynard, David Pugmire,
Abhishek Yenpure,
Allison Vacanti,
Matthew Larsen, and
Hank Childs
Parallel Computing, December 2021
[PDF] [BIB]
|
Evaluating Adaptive and Predictive Power Management Strategies for Optimizing Visualization Performance on Supercomputers
Stephanie Brink,
Matthew Larsen,
Hank Childs,
and Barry Rountree
Parallel Computing, July 2021
[PDF] [BIB]
|
Scalable In Situ Computation of Lagrangian Representations via Local Flow Maps
Sudhanshu Sane,
Abhishek Yenpure,
Roxana Bujack,
Matt Larsen,
Ken Moreland,
Christoph Garth,
Christopher R. Johnson,
and Hank Childs
Eurographics Symposium on Parallel Graphics and Visualization (EGPGV), Zurich, Switzerland, June 2021
Best Paper
[PDF] [BIB]
|
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]
|
Benchmarking In Situ Triggers Via Reconstruction Error
Yuya Kawakami,
Nicole Marsaglia,
Matt Larsen,
and
Hank Childs
ISAV 2020: In Situ Infrastructures for Enabling Extreme-scale Analysis and Visualization, Atlanta GA, November 2020
[PDF] [BIB]
|
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]
|
When Parallel Performance Measurement and Analysis Meets In Situ Analytics and Visualization
Allen Malony,
Matthew Larsen,
Kevin Huck, Chad Wood,
Sudhanshu Sane,
and
Hank Childs
International Conference on Parallel Computing (ParCo2019), Prague, Czech Republic, September 2019
[PDF] [BIB]
|
A Scalable Hybrid Scheme for Ray-Casting of Unstructured Volume Data
Roba Binyahib, Tom Peterka,
Matthew Larsen,
Kwan-Liu Ma,
and Hank Childs
IEEE Transactions on Visualization and Computer Graphics, July 2019
[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]
|
Dynamic I/O Budget Reallocation For In Situ Wavelet Compression
Nicole Marsaglia,
Shaomeng Li,
Kristi Belcher,
Matt Larsen, and
Hank Childs,
Eurographics Symposium on Parallel Graphics and Visualization (EGPGV), Porto, Portugal, June 2019
[PDF] [BIB]
|
Power and Performance Tradeoffs for Visualization Algorithms
Stephanie Labasan,
Matt Larsen,
Hank Childs,
and Barry Rountree
IEEE International Parallel and Distributed Processing Symposium (IPDPS), Rio de Janeiro, Brazil, May 2019
[PDF] [BIB]
|
Performance Impacts of In Situ Wavelet Compression on Scientific Simulations
Samuel Li,
Matt Larsen,
John Clyne,
and Hank Childs
ISAV 2017: In Situ Infrastructures for Enabling Extreme-Scale Analysis and Visualization, Denver, CO, November 2017
[PDF] [BIB]
|
Techniques for Data-Parallel Searching for Duplicate Elements
Brent Lessley,
Kenneth Moreland,
Matt Larsen,
and Hank Childs
IEEE Symposium on Large Data Analysis and Visualization (LDAV), Phoenix, AZ, October 2017
[PDF] [BIB]
|
PaViz: A Power-Adaptive Framework for Optimizing Visualization Performance
Stephanie Labasan,
Matt Larsen,
Hank Childs,
and Barry Rountree
Eurographics Symposium on Parallel Graphics and Visualization (EGPGV), Barcelona, Spain, June 2017
[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 for Exascale: Portable Performance is Critical
Ken Moreland,
Matt Larsen, and Hank Childs
Supercomputing Frontiers and Innovations, December 2015
[LINK] [BIB]
|
Exploring Tradeoffs Between Power and Performance for a Scientific Visualization Algorithm
Stephanie Labasan,
Matthew Larsen,
and Hank Childs
IEEE Symposium on Large Data Analysis and Visualization (LDAV), Chicago, IL, October 2015
[PDF] [BIB]
|
|
