Dr. Shaomeng (Samuel) Li

Ph.D. Graduate, November 2017
CIS Department
University of Oregon

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

Bio

Samuel Li is an alumnus of the CDUX group, receiving his Ph.D. in November 2017. He accepted a full-time staff position at National Center for Atmospheric Research (NCAR) in September 2016, and continued in this position after graduation. His research interests include high-performance computing, portable performance, scientific data reduction for exascale computing, and scientific visualization.

Sam's dissertation question focused on the viability of wavelet compression as a reduction operator on exascale computers. This question required assessing viability from multiple perspectives. His first research thrust was on evaluating the integrity of scientific data sets after undergoing a wavelet transformation (LDAV15). In this work, Sam also demonstrated the benefit of bringing in modern wavelet approaches (CDF kernels and prioritized coefficients) for scientific data. Sam's second research thrust was on how to carry out wavelet transforms on exascale computers. Sam had two works on this front, one showing how to write portably performant code (EGPGV17) and another showing how to achieve better accuracy by leveraging deep memory hierarchies (CLUSTER17). Sam's final research thrust was on whether wavelet transformations could be accomplished within simulation codes' time budget, and evaluating their savings at scale. Sam studied this topic with his final dissertation work (ISAV17), which included runs of up to 1000 MPI ranks on NCAR's Cheyenne supercomputer. These works combined to answer his dissertation question: yes, wavelet compression is a viable reduction operator for exascale computing. Finally, Sam's Area Exam paper surveying data reduction operators was published at the Computer Graphics Forum journal.

Prior to joining UO, Samuel completed an M.S. degree from Tufts University, working with Remco Chang. His M.S. thesis was published as a research paper, Exploring Visualization Designs Using Phylogenetic Trees, at the SPIE Visualization and Data Analysis conference in 2015, and won a Best Paper award. During his time at UO, Samuel collaborated with John Clyne of NCAR, first as a summer student in 2015, and later through NCAR's Advanced Study Program (ASP) Award in Winter of 2016. Finally, Samuel did an internship at Los Alamos National Laboratory in the Summer of 2016, working with Chris Sewell, Ollie Lo, and Jon Woodring.

First-Author Publications


Data Reduction Techniques for Simulation, Visualization, and Data Analysis
Samuel Li, Nicole Marsaglia, Christoph Garth, Jon Woodring, John Clyne, and Hank Childs
Computer Graphics Forum, September 2018

[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]

Spatiotemporal Wavelet Compression for Visualization of Scientific Simulation Data
Samuel Li, Sudhanshu Sane, Leigh Orf, Pablo Mininni, John Clyne, and Hank Childs
IEEE Cluster Conference, Honolulu, HI, September 2017

[PDF]     [BIB]

Achieving Portable Performance For Wavelet Compression Using Data Parallel Primitives
Samuel Li, Nicole Marsaglia, Vincent Chen, Christopher Sewell, John Clyne, and and Hank Childs
Eurographics Symposium on Parallel Graphics and Visualization (EGPGV), Barcelona, Spain, June 2017

[PDF]     [BIB]

Evaluating the Efficacy of Wavelet Configurations on Turbulent-Flow Data
Samuel Li, Kenny Gruchalla, Kristi Potter, John Clyne, and Hank Childs
IEEE Symposium on Large Data Analysis and Visualization (LDAV), Chicago, IL, October 2015

[PDF]     [BIB]

Exploring Hierarchical Visualization Designs Using Phylogenetic Trees
Samuel Li, Jordan Crouser, Garth Griffin, Connor Gramazio, Hans-Jörg Schulz, Hank Childs, and Remco Chang
SPIE Visualization and Data Analysis (VDA), San Francisco, CA, February 2015
Best Paper

[PDF]     [BIB]
Additional Publications


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]

Enabling Explorative Visualization With Full Temporal Resolution Via In Situ Calculation Of Temporal Intervals
Nicole Marsaglia, Shaomeng Li, and Hank Childs
ISC High Performance 2018 International Workshops (Lecture Notes in Computer Science), Frankfurt, Germany, June 2018

[PDF]     [BIB]

Toward a Multi-method Approach: Lossy Data Compression for Climate Simulation Data
Allison Baker, Haiying Xu, Dorit Hammerling, Samuel Li, and John Clyne
The 1st International Workshop on Data Reduction for Big Scientific Data (DRBSD-1), Frankfurt, Germany, June 2017

[PDF]     [BIB]