Accelerating multiscale materials modeling with machine learning

A cube with balls represents atoms configured on a grid.

Multiscale materials modeling fundamental insight into microscopic mechanisms that determine materials properties in nuclear stockpile applications that leverage radiation harden semiconductors, advanced manufacturing, shock compression, and energetic materials. This LDRD team including three postdoctoral researchers developed a new ML surrogate model for density functional theory using deep neural networks to accurately predict total energies of 100,000 atom systems when trained on only 256 atoms.

When compared with direct numerical simulation of 2048 aluminum atoms, the error provides in electron density of the new surrogate model is under 1%, but computation is three orders of magnitude faster. Promising methodologies such as optimal experimental design techniques and novel Graph Neural Networks were explored in training smaller data sets and will be researched further in the future to continue accelerating first-principal data generation and increase the fidelity and robustness of predictive atomistic materials simulations. An ML model designed for aluminum has already been successfully leveraged in Sandia’s Electronics Parts Program milestone.


CAD model (left) with multiple fasteners (right), rapidly reduced to simulation-ready state using new ML methods.

Sandia researchers linked to work


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Associated Publications

Asmeret Naugle, Daniel Krofcheck, Christina Warrender, Kiran Lakkaraju, Laura Swiler, Stephen Verzi, Ben Emery, Jaimie Murdock, Michael Bernard, Vicente Romero, (2023). What can simulation test beds teach us about social science? Results of the ground truth program Computational and Mathematical Organization Theory https://doi.org/10.1007/s10588-021-09349-6 Publication ID: 80604

Asmeret Naugle, Stephen Verzi, Kiran Lakkaraju, Laura Swiler, Christina Warrender, Michael Bernard, Vicente Romero, (2023). Feedback density and causal complexity of simulation model structure Journal of Simulation https://doi.org/10.1080/17477778.2021.1982653 Publication ID: 75723

Lenz Fiedler, Normand Modine, Steve Schmerler, Dayton Vogel, Gabriel Popoola, Aidan Thompson, Sivasankaran Rajamanickam, Attila Cangi, (2022). Predicting the Electronic Structure of Matter on Ultra-Large Scales https://doi.org/10.2172/1895024 Publication ID: 80390

Alina Kononov, Cheng-Wei Lee, Tatiane Pereira dos Santos, Brian Robinson, Yifan Yao, Yi Yao, Xavier Andrade, Andrew Baczewski, Emil Constantinescu, Alfredo Correa, Yosuke Kanai, Normand Modine, Andre Schleife, (2022). Electron dynamics in extended systems within real-time time-dependent density-functional theory MRS communications https://doi.org/10.1557/s43579-022-00273-7 Publication ID: 80304

Brian Kelley, Sivasankaran Rajamanickam, (2022). Unified Language Frontend for Physic-Informed AI/ML https://doi.org/10.2172/1888879 Publication ID: 80261

Paul Mariner, Bert Debusschere, David Fukuyama, Jacob Harvey, Tara LaForce, Rosemary Leone, Frank Perry, Laura Swiler, ANNA TACONI, (2022). GDSA Framework Development and Process Model Integration FY2022 https://doi.org/10.2172/1893995 Publication ID: 80378

Dusty Brooks, Laura Swiler, Emily Stein, Paul Mariner, Eduardo Basurto, Teresa Portone, Aubrey Eckert, Rosemary Leone, (2022). Sensitivity analysis of generic deep geologic repository with focus on spatial heterogeneity induced by stochastic fracture network generation Advances in Water Resources https://doi.org/10.1016/j.advwatres.2022.104310 Publication ID: 80187

Normand Modine, John Stephens, Laura Swiler, Aidan Thompson, Dayton Vogel, Attila Cangi, Lenz Feilder, Sivasankaran Rajamanickam, (2022). Accelerating Multiscale Materials Modeling with Machine Learning https://doi.org/10.2172/1889336 Publication ID: 80251

Laura Swiler, Eduardo Basurto, Dusty Brooks, Aubrey Eckert, Rosemary Leone, Paul Mariner, Teresa Portone, Mariah Smith, (2022). Uncertainty and Sensitivity Analysis Methods and Applications in the GDSA Framework (FY2022) https://doi.org/10.2172/1884909 Publication ID: 80086

Asmeret Naugle, Laura Swiler, Kiran Lakkaraju, Stephen Verzi, Christina Warrender, Vicente Romero, (2022). Graph-Based Similarity Metrics for Comparing Simulation Model Causal Structures https://doi.org/10.2172/1884926 Publication ID: 80095

James Goff, Charles Sievers, Mitchell Wood, Aidan Thompson, (2022). Permutation-adapted complete and independent basis for atomic cluster expansion descriptors https://doi.org/10.2172/1879613 Publication ID: 80036

Jeremy Myers, Daniel Dunlavy, (2022). A Hybrid Method for Tensor Decompositions that Leverages Stochastic and Deterministic Optimization https://doi.org/10.2172/1865529 Publication ID: 80700

Asmeret Naugle, Adam Russell, Kiran Lakkaraju, Laura Swiler, Stephen Verzi, Vicente Romero, (2022). The Ground Truth Program: Simulations as Test Beds for Social Science Research Methods. Computational and Mathematical Organization Theory https://doi.org/10.1007/s10588-021-09346-9 Publication ID: 80622

Christian Trott, Damien Lebrun-Grandie, Daniel Arndt, Jan Ciesko, Vinh Dang, Nathan Ellingwood, Rahulkumar Gayatri, Evan Harvey, Daisy Hollman, Dan Ibanez, Nevin Liber, Jonathan Madsen, Jeff Miles, David Poliakoff, Amy Powell, Sivasankaran Rajamanickam, Mikael Simberg, Dan Sunderland, Bruno Turcksin, Jeremiah Wilke, (2022). Kokkos 3: Programming Model Extensions for the Exascale Era IEEE Transactions on Parallel and Distributed Systems https://doi.org/10.1109/TPDS.2021.3097283 Publication ID: 79057

Gordon Moon, Hyoukjun Kwon, Geonhwa Jeong, Prasanth Chatarasi, Sivasankaran Rajamanickam, Tushar Krishna, (2022). Evaluating Spatial Accelerator Architectures with Tiled Matrix-Matrix Multiplication IEEE Transactions on Parallel and Distributed Systems https://doi.org/10.1109/TPDS.2021.3104240 Publication ID: 79857

Lenz Fiedler, Nils Hoffmann, Parvez Mohammed, Gabriel Popoola, Tamar Yovell, Vladyslav Oles, Austin Ellis, Sivasankaran Rajamanickam, Attila Cangi, (2022). Finding Electronic Structure Machine Learning Surrogates without Training https://doi.org/10.2172/1891948 Publication ID: 80361

Aidan Thompson, H. Aktulga, Richard Berger, Dan Bolintineanu, W. Brown, Paul Crozier, Pieter in ‘t Veld, Axel Kohlmeyer, Stan Moore, Trung Nguyen, Ray Shan, Mark Stevens, Julien Tranchida, Christian Trott, Steven Plimpton, (2022). LAMMPS – a flexible simulation tool for particle-based materials modeling at the atomic, meso, and continuum scales Computer Physics Communications https://doi.org/10.1016/j.cpc.2021.108171 Publication ID: 80783

Abdurrahman Yasar, Sivasankaran Rajamanickam, Jonathan Berry, Umit Catalyurek, (2022). A Block-Based Triangle Counting Algorithm on Heterogeneous Environments IEEE Transactions on Parallel and Distributed Systems https://doi.org/10.1109/tpds.2021.3093240 Publication ID: 79132

Oscar Lopez, Richard Lehoucq, Daniel Dunlavy, (2022). Zero-Truncated Poisson Tensor Decomposition for Sparse Count Data https://doi.org/10.2172/1841834 Publication ID: 79989

Alexander Heinlein, Mauro Perego, Sivasankaran Rajamanickam, (2022). FROSch PRECONDITIONERS FOR LAND ICE SIMULATIONS OF GREENLAND AND ANTARCTICA SIAM Journal on Scientific Computing https://doi.org/10.1137/21m1395260 Publication ID: 79975

Laura Swiler, (2021). Uncertainty Quantification (UQ) and Sensitivity Analysis (SA) in GDSA https://www.osti.gov/servlets/purl/1901835 Publication ID: 77036

Yury Lysogorskiy, Cas Oord, Anton Bochkarev, Sarath Menon, Matteo Rinaldi, Thomas Hammerschmidt, Matous Mrovec, Aidan Thompson, Gábor Csányi, Christoph Ortner, Ralf Drautz, (2021). Performant implementation of the atomic cluster expansion (PACE) and application to copper and silicon npj Computational Materials https://doi.org/10.1038/s41524-021-00559-9 Publication ID: 76410

Svetoslav Nikolov, Mitchell Wood, Attila Cangi, Jean Maillet, Mihai Marinica, Aidan Thompson, Michael Desjarlais, Julien Tranchida, (2021). Data-driven magneto-elastic predictions with scalable classical spin-lattice dynamics npj Computational Materials https://www.osti.gov/servlets/purl/1870099 Publication ID: 78587

Daniel Dunlavy, Peter Chew, (2021). Document Retrieval and Ranking using Similarity Graph Mean Hitting Times https://doi.org/10.2172/1835671 Publication ID: 77129

Sivasankaran Rajamanickam, Luc Berger-Vergiat, Erik Boman, Ichitaro Yamazaki, (2021). Sake December 2021 ECP ST Project Review https://www.osti.gov/servlets/purl/1902027 Publication ID: 77055

Sivasankaran Rajamanickam, (2021). Can Scientific Software Development Use the Outsourcing Model Successfully? https://doi.org/10.2172/1908776 Publication ID: 77136

Laura Swiler, (2021). Verification and Validation for Cyber Emulation https://doi.org/10.2172/1897016 Publication ID: 76651

Brian Adams, William Bohnhoff, Keith Dalbey, Mohamed Ebeida, John Eddy, Michael Eldred, Russell Hooper, Patricia Hough, Kenneth Hu, John Jakeman, Mohammad Khalil, Kathryn Maupin, Jason Monschke, Elliott Ridgway, Ahmad Rushdi, Daniel Seidl, John Stephens, Laura Swiler, Anh Tran, Justin Winokur, (2021). Dakota, A Multilevel Parallel Object-Oriented Framework for Design Optimization, Parameter Estimation, Uncertainty Quantification, and Sensitivity Analysis (V.6.16 User’s Manual) https://doi.org/10.2172/1868142 Publication ID: 80729

Mary Cusentino, Mitchell Wood, Aidan Thompson, (2021). Development of SNASP Machine Learned Interatomic Potentials for Materials in Extreme Environments https://doi.org/10.2172/1899237 Publication ID: 76870

Sivasankaran Rajamanickam, (2021). Portability in Trilinos https://www.osti.gov/servlets/purl/1895552 Publication ID: 76522

Clayton Hughes, Rizwan Ashraf, Roberto Gioiosa, Cynthia Phillips, Jonathan Berry, William Hart, Carl Laird, Sivasankaran Rajamanickam, (2021). ARIAA Update — SST https://www.osti.gov/servlets/purl/1897599 Publication ID: 76739

Sivasankaran Rajamanickam, Sivasankaran Rajamanickam, (2021). Can Scientific Software Development Use the Outsourcing Model Successfully https://www.osti.gov/servlets/purl/1899526 Publication ID: 76879

Jennifer Loe, Sivasankaran Rajamanickam, (2021). Mixed Precision in Trilinos https://doi.org/10.2172/1900352 Publication ID: 76971

Sivasankaran Rajamanickam, Alexander Heinlein, Heidi Thornquist, Ichitaro Yamazaki, (2021). Trilinos User Group MeetingSolvers Update https://doi.org/10.2172/1900353 Publication ID: 76972

Alexander Heinlein, Mauro Perego, Sivasankaran Rajamanickam, Ichitaro Yamazaki, (2021). FROSch Preconditioners for Land Ice Simulations of Greenland and Antarctica https://doi.org/10.2172/1900354 Publication ID: 76982

Aidan Thompson, (2021). FusMatML End-of-Year Review Summary https://www.osti.gov/servlets/purl/1897015 Publication ID: 76411

Brian Kelley, Sivasankaran Rajamanickam, (2021). Parallel, Portable Algorithms for Distance-2 Maximal Independent Set and Graph Coarsening https://doi.org/10.1109/IPDPS53621.2022.00035 Publication ID: 76347

Sivasankaran Rajamanickam, (2021). Enabling Science Simulations with Scalable Computational Frameworks for Scientific Computing https://www.osti.gov/servlets/purl/1894020 Publication ID: 76394

David Littlewood, Mitchell Wood, David Montes de Oca Zapiain, Sivasankaran Rajamanickam, Nathaniel Trask, (2021). Sandia / IBM Discussion on Machine Learning for Materials Applications [Slides] https://doi.org/10.2172/1828106 Publication ID: 76348

Stan Moore, Aidan Thompson, (2021). Large-Scale Atomistic Simulations [Slides] https://doi.org/10.2172/1820306 Publication ID: 75672

Paul Mariner, Timothy Berg, Bert Debusschere, Aubrey Eckert, Jacob Harvey, Tara LaForce, Rosemary Leone, Melissa Mills, Michael Nole, Heeho Park, Perry, Daniel Seidl, Laura Swiler, Kyung Chang, (2021). GDSA Framework Development and Process Model Integration FY2021 https://doi.org/10.2172/1825056 Publication ID: 76168

Laura Swiler, Dirk-Alexander Becker, Dusty Brooks, Joan Govaerts, Lasse Koskinen, Elmar Plischke, Klaus-Jürgen Röhlig, Elena Saveleva, Sabine Spiessl, Emily Stein, Valentina Svitelman, (2021). Sensitivity Analysis Comparisons on Geologic Case Studies: An International Collaboration https://doi.org/10.2172/1822591 Publication ID: 75545

Ali Pinar, Thomas Tarman, Laura Swiler, Jared Gearhart, Derek Hart, Eric Vugrin, Gerardo Cruz, Bryan Arguello, Gianluca Geraci, Bert Debusschere, Seth Hanson, Alexander Outkin, Jamie Thorpe, William Hart, Meghan Sahakian, Kasimir Gabert, Casey Glatter, Emma Johnson, She?ifa Punla-Green, (2021). Science & Engineering of Cyber Security by Uncertainty Quantification and Rigorous Experimentation (SECURE) HANDBOOK https://doi.org/10.2172/1820527 Publication ID: 75697

Laura Swiler, Dusty Brooks, (2021). Joint Sensitivity Analysis (JOSA) Exercise Meeting Sept. 21, 2021 https://www.osti.gov/servlets/purl/1888135 Publication ID: 75754

Laura Swiler, (2021). White paper on Verification and Validation for Cyber Emulation Models https://doi.org/10.2172/1854720 Publication ID: 75981

Benjamin Wagman, Laura Swiler, Kamaljit Chowdhary, Benjamin Hillman, (2021). The Fingerprints of Stratospheric Aerosol Injection in E3SM https://doi.org/10.2172/1821542 Publication ID: 75727

Ali Pinar, Thomas Tarman, Laura Swiler, Jared Gearhart, Derek Hart, Eric Vugrin, Gerardo Cruz, Bryan Arguello, Gianluca Geraci, Bert Debusschere, Seth Hanson, Alexander Outkin, Jamie Thorpe, William Hart, Meghan Sahakian, Kasimir Gabert, Casey Glatter, Emma Johnson, She?ifa Punla-Green, (2021). Science and Engineering of Cybersecurity by Uncertainty quantification and Rigorous Experimentation (SECURE) (Final Report) https://doi.org/10.2172/1821322 Publication ID: 75817

Michael Stickland, Justin Li, Laura Swiler, Thomas Tarman, (2021). Foundations of Rigorous Cyber Experimentation https://doi.org/10.2172/1854751 Publication ID: 76007

Mary Cusentino, N. Bobbitt, Mitchell Wood, Aidan Thompson, (2021). Development of SNAP Interatomic Potentials for Studying Mixed Materials Effects at the Tungsten Divertor https://doi.org/10.2172/1890848 Publication ID: 75965

Stephen Olivier, Nathan Ellingwood, Jonathan Berry, Daniel Dunlavy, (2021). Performance Portability of an SpMV Kernel Across Scientific Computing and Data Science Applications https://doi.org/10.2172/1887725 Publication ID: 75703

Sean Geronimo Anderson, Keita Teranishi, Daniel Dunlavy, Jee Choi, (2021). Performance-Portable Sparse Tensor Decomposition Kernels on Emerging Parallel Architectures https://doi.org/10.2172/1888390 Publication ID: 75757

Jeremy Myers, Daniel Dunlavy, (2021). Using Computation Effectively for Scalable Poisson Tensor Factorization: Comparing Methods Beyond Computational Efficiency https://doi.org/10.2172/1888651 Publication ID: 75760

Geonhwa Jeong, Gokcen Kestor, Prasanth Chatarsi, Angshuman Parashar, Po-An Tsai, Sivasankaran Rajamanickam, Roberto Gioiosa, Tushar Krishna, (2021). Union: A Unified HW-SW Co-Design Ecosystem in MLIR for Evaluating Tensor Operations on Spatial Accelerators https://doi.org/10.2172/1890906 Publication ID: 75669

Raveesh Garg, Eric Qin, Francisco Martinez, Robert Guirado, Akshay Jain, Sergi Abadal, Jose Abellan, Manuel Acacio, Eduard Alarcon, Sivasankaran Rajamanickam, Tushar Krishna, (2021). Understanding the Design Space of Sparse/Dense Multiphase Dataflows for Mapping Graph Neural Networks on Spatial Accelerators https://doi.org/10.2172/1821960 Publication ID: 75867

Seher Acer, Erik Boman, Christian Glusa, Sivasankaran Rajamanickam, (2021). Sphynx: A parallel multi-GPU graph partitioner for distributed-memory systems Parallel Computing https://doi.org/10.2172/1853867 Publication ID: 77409

Ahmad Abdelfattah, Hartwig Anzt, Alan Ayala, Erik Boman, Erin Carson, Sebastien Cayrols, Terry Cojean, Jack Dongarra, Rob Falgout, Mark Gates, Thomas Gr\"{u}tzmacher, Nicholas Higham, Scott Kruger, Sherry Li, Neil Lindquist, Yang Liu, Jennifer Loe, Pratik Nayak, Daniel Osei-Kuffuor, Sri Pranesh, Sivasankaran Rajamanickam, Tobias Ribizel, Bryce Smith, Kasia Swirydowicz, Stephen Thomas, Stanimire Tomov, Yaohung M. Tsai, Ichitaro Yamazaki, Urike Yang, (2021). Advances in Mixed Precision Algorithms: 2021 Edition https://doi.org/10.2172/1814447 Publication ID: 75285

Laura Swiler, Eduardo Basurto, Dusty Brooks, Aubrey Eckert, Rosemary Leone, Paul Mariner, Teresa Portone, Mariah Smith, Emily Stein, (2021). Uncertainty and Sensitivity Analysis Methods and Applications in the GDSA Framework (FY2021) https://doi.org/10.2172/1855018 Publication ID: 79851

Thomas Tarman, Trevor Rollins, Laura Swiler, Gerardo Cruz, Eric Vugrin, Hao Huang, Abhijeet Sahu, Patrick Wlazlo, Ana Goulart, Kate Davis, (2021). Comparing reproduced cyber experimentation studies across different emulation testbeds ACM International Conference Proceeding Series https://doi.org/10.1145/3474718.3474725 Publication ID: 78420

Laura Swiler, Dusty Brooks, Emily Stein, Klaus-Jürgen Röhlig, Elmar Plischke, Dirk-Alexander Becker, Sabine Spiessl, Lasse Koskinen, Joan Govaerts, Valentina Svitelman, Elena Saveleva., (2021). Metamodelling sensitivity approaches versus regression and graphical methods on the basis of Geologic Cases: An International Collaboration https://doi.org/10.2172/1884666 Publication ID: 75431

Thomas Tarman, Laura Swiler, Eric Vugrin, Trevor Rollins, Gerardo Cruz, Hao Huang, Abhijeet Sahu, Patrick Wlazlo, Ana Goulart, Kate Davis, (2021). Comparing reproduced cyber experimentation studies across different emulation testbeds https://doi.org/10.2172/1881645 Publication ID: 79697

Mary Cusentino, Mitchell Wood, Aidan Thompson, (2021). Development of SNAP Potentials for Fusion Reactor Materials https://doi.org/10.2172/1882069 Publication ID: 79641

Mitchell Wood, Aidan Thompson, Mary Cusentino, David Montes de Oca Zapiain, Ivan Oleynik, (2021). Interatomic Potentials for Materials Science and Beyond; Advances in Machine Learned Spectral Neighborhood Analysis Potentials https://doi.org/10.2172/1883516 Publication ID: 79748

Anthony Rice, Mary Crawford, Andrew Armstrong, Andrew Allerman, Normand Modine, (2021). Defect Spectroscopy and Reduced Compensation of UV Illuminated MOCVD n-type GaN https://doi.org/10.2172/1888973 Publication ID: 79658

Sean Geronimo Anderson, Keita Teranishi, Daniel Dunlavy, Jee Choi, (2021). Performance-Portable Sparse Tensor Decomposition Kernels on Emerging Parallel Architectures https://www.osti.gov/servlets/purl/1884665 Publication ID: 75426

Seher Acer, Erik Boman, Christian Glusa, Sivasankaran Rajamanickam, (2021). Sphynx: a parallel multi-GPU graph partitioner https://doi.org/10.2172/1882077 Publication ID: 79650

J. Ellis, L. Fiedler, G. Popoola, Normand Modine, John Stephens, Aidan Thompson, A. Cangi, Sivasankaran Rajamanickam, (2021). Accelerating finite-temperature Kohn-Sham density functional theory with deep neural networks Physical Review B https://doi.org/10.2172/1817970 Publication ID: 79009

Gordon Moon, Hyoukjun Kwon, Geonhwa Jeong, Prasanth Chatarsi, Sivasankaran Rajamanickam, Tushar Krishna, (2021). Evaluating Spatial Accelerator Architectures with Tiled Matrix-Matrix Multiplication https://doi.org/10.2172/1808019 Publication ID: 78992

Thomas Tarman, Laura Swiler, Gerardo Cruz, Eric Vugrin, Trevor Rollins, Hao Huang, Abhijeet Sahu, Patrick Wlazlo, Ana Goulart, Kate Davis, (2021). Comparing reproduced cyber experimentation studies across different emulation testbeds https://doi.org/10.1145/3474718.3474725 Publication ID: 79240

Gianluca Geraci, Laura Swiler, Bert Debusschere, (2021). Multifidelity UQ sampling for Stochastic Simulations https://doi.org/10.2172/1889573 Publication ID: 79490

Jennifer Loe, Christian Glusa, Ichitaro Yamazaki, Erik Boman, Sivasankaran Rajamanickam, (2021). Properties of GMRES with Iterative Refinement on GPUs https://doi.org/10.2172/1884157 Publication ID: 79139

Sivasankaran Rajamanickam, Luc Berger-Vergiat, Vinh Dang, Nathan Ellingwood, Evan Harvey, Brian Kelley, Christian Trott, (2021). Kokkos Kernels 3.4 https://www.osti.gov/servlets/purl/1889057 Publication ID: 79353

Kyle Lennon, Sivasankaran Rajamanickam, (2021). Learning Transferable DFT Neural Network Surrogates https://www.osti.gov/servlets/purl/1884431 Publication ID: 79432

Jennifer Loe, Christian Glusa, Ichitaro Yamazaki, Erik Boman, Sivasankaran Rajamanickam, (2021). Experimental Evaluation of Multiprecision Strategies for GMRES on GPUs 2021 IEEE International Parallel and Distributed Processing Symposium Workshops, IPDPSW 2021 – In conjunction with IEEE IPDPS 2021 https://doi.org/10.1109/IPDPSW52791.2021.00078 Publication ID: 77887

Sharlotte Kramer, Dan Bolintineanu, Kevin Long, Craig Hamel, A. Frankel, Reese Jones, Laura Swiler, Kyle Johnson, (2021). Mechanics of Materials Utilizing Machine Learning: Examples at Sandia National Laboratories https://doi.org/10.2172/1867564 Publication ID: 78396

Michael Stickland, Justin Li, Thomas Tarman, Laura Swiler, (2021). Uncertainty quantification in cyber experimentation https://www.osti.gov/servlets/purl/1867999 Publication ID: 78424

Laura Swiler, (2021). Sensitivity Analysis for the Latest Crystalline Reference Case https://www.osti.gov/servlets/purl/1868007 Publication ID: 78432

Laura Swiler, Dusty Brooks, (2021). GP and PCE surrogate models for estimation of sensitivity indices https://www.osti.gov/servlets/purl/1868008 Publication ID: 78433

Julien Tranchida, Mary Cusentino, Mitchell Wood, Aidan Thompson, (2021). First-principles and classical computational study of W/ZrC interfaces https://doi.org/10.2172/1866898 Publication ID: 78336

Eric Qin, Geonhwa Jeong, William Won, Sheng Kao, Hyoukjun Kwon, Sudarshan Srinivasan, Dipankar Das, Gordon Moon, Sivasankaran Rajamanickam, Tushar Krishna, (2021). Extending sparse tensor accelerators to support multiple compression formats Proceedings – 2021 IEEE 35th International Parallel and Distributed Processing Symposium, IPDPS 2021 https://doi.org/10.1109/IPDPS49936.2021.00110 Publication ID: 75805

Lenz Fiedler, Austin Ellis, Sivasankaran Rajamanickam, Attila Cangi, (2021). An Introduction to the Materials Learning Algorithms Package (MALA) https://doi.org/10.2172/1867139 Publication ID: 78371

Jennifer Loe, Christian Glusa, Ichitaro Yamazaki, Erik Boman, Sivasankaran Rajamanickam, (2021). Experimental Evaluation of Multiprecision Strategies for GMRES on GPUs https://doi.org/10.2172/1869548 Publication ID: 78515

Mahantesh Halappanavar, Seher Acer, Erik Boman, Aydin Buluc, Saliya Ekanayate, SM Feerdous, Nitin Gawande, Sayan Ghosh, Arif Khan, Marco Minotoli, alex pothen, Sivasankaran Rajamanickam, Oguz Selvitopi, Nathan Tallent, Antonio Tumeo, (2021). Exagraph: Combinatorial Methods for Enabling Exascale Science https://www.osti.gov/servlets/purl/1870360 Publication ID: 78618

Laura Swiler, (2021). Statistical Methods used in the Born Qualified LDRD Project https://www.osti.gov/servlets/purl/1863692 Publication ID: 78088

Mary Cusentino, M. Wood, Aidan Thompson, (2021). Beryllium-driven structural evolution at the divertor surface Nuclear Fusion https://doi.org/10.1088/1741-4326/abe7bd Publication ID: 77317

Mary Cusentino, Mitchell Wood, Chun-Shang Wong, Robert Kolasinski, Brian Wirth, Aidan Thompson, (2021). Molecular Dynamics Simulations of Hydrogen and Nitrogen on Tungsten Surfaces https://doi.org/10.2172/1866199 Publication ID: 78291

Chun-Shang Wong, Robert Kolasinski, Josh Whaley, Mary Cusentino, Mitchell Wood, Brian Wirth, Aidan Thompson, (2021). Nitrogen effects on hydrogen adsorption at tungsten surfaces https://doi.org/10.2172/1866560 Publication ID: 78328

David Poliakoff, Amy Powell, Cory Madsen, Elliott Ridgway, D. LeBrun-Grandie, Sivasankaran Rajamanickam, C.R. Trott, (2021). Kokkos Tools and Performance Tracking https://doi.org/10.2172/1862779 Publication ID: 77974

Michael Sprague, Shreyas Ananthan, Roba Binyahib, Michael Brazell, Marc de Frahan, Ryan King, Paul Mullowney, Jon Rood, Ashesh Sharma, Stephen Thomas, Ganesh Vijayakumar, Paul Crozier, Luc Berger-Vergiat, Lawrence Cheung, David Dement, N. Develder, David Glaze, Jonathan Hu, Robert Knaus, Dong Lee, Neil Matula, Tolulope Okusanya, James Overfelt, Sivasankaran Rajamanickam, Philip Sakievich, Timothy Smith, Johnathan Vo, Alan Williams, Ichitaro Yamazaki, William Turner, Andrey Prokopenko, Robert Wilson, Moser, Jeremy Melvin, Sitaraman, (2021). ExaWind: Exascale Predictive Wind Plant Flow Physics Modeling https://doi.org/10.2172/1863503 Publication ID: 78075

Sivasankaran Rajamanickam, Luc Berger-Vergiat, Erik Boman, Ichitaro Yamazaki, (2021). Sake: Solvers and Kernels for Exascale https://doi.org/10.2172/1863702 Publication ID: 78099

Luc Berger-Vergiat, Sivasankaran Rajamanickam, Vinh Dang, Nathan Ellingwood, Brian Kelley, Evan Harvey, Jeremiah Wilke, Seher Acer, (2021). Kokkos Kernels: FY20 update https://doi.org/10.2172/1863703 Publication ID: 78100

Erik Boman, Karen Devine, Sivasankaran Rajamanickam, Seher Acer, Ian Bogle, George Slota, Kamesh Madduri, Michael Gilbert, (2021). ExaGraph: Partitioning and Coloring https://www.osti.gov/servlets/purl/1882034 Publication ID: 78195

Sivasankaran Rajamanickam, Luc Berger-Vergiat, Ichitaro Yamazaki, Erik Boman, (2021). Sake: Solvers and Kernels for Exascale https://doi.org/10.2172/1877842 Publication ID: 78203

Sivasankaran Rajamanickam, Luc Berger-Vergiat, Seher Acer, Vinh Dang, Nathan Ellingwood, Evan Harvey, Brian Kelley, Jeremiah Wilke, (2021). Kokkos Kernels: FY20 update https://doi.org/10.2172/1884233 Publication ID: 78204

Simon Hammond, Matthew Curry, Kevin Davis, Vinh Dang, Oksana Guba, Robert Hoekstra, James Laros, Kevin Pedretti, David Poliakoff, Sivasankaran Rajamanickam, Christian Trott, Andrew Younge, (2021). Fugaku and A64FX Update – April 2021 https://www.osti.gov/servlets/purl/1882368 Publication ID: 78205

Stan Moore, Aidan Thompson, (2021). Large-Scale Atomistic Simulations [Slides] https://doi.org/10.2172/1773391 Publication ID: 77802

Nathan Porter, Kathryn Maupin, Laura Swiler, Vincent Mousseau, (2021). Validation Metrics for Fixed Effects and Mixed-Effects Calibration Journal of Verification, Validation and Uncertainty Quantification https://doi.org/10.1115/1.4049534 Publication ID: 74591

Laura Swiler, (2021). Epistemic Uncertainty: Computation and Usage https://doi.org/10.2172/1855744 Publication ID: 77617

Anh Tran, Julien Tranchida, Timothy Wildey, Aidan Thompson, (2021). Multi-fidelity ML/UQ and Bayesian Optimization for Materials Design: Application to Ternary Random Alloys https://doi.org/10.2172/1853874 Publication ID: 77392

Steven Plimpton, Aidan Thompson, Mitch Wood, (2021). LAMMPS as a tool in materials modeling workflows https://doi.org/10.2172/1853877 Publication ID: 77396

Mitchell Wood, Charles Sievers, Aidan Thompson, Nicholas Lubbers, Perez Danny, (2021). Building a Better Database to Learn From; Application to Interatomic Potentials https://doi.org/10.2172/1853859 Publication ID: 77408

J. Ellis, Sivasankaran Rajamanickam, Normand Modine, Aidan Thompson, John Stephens, Attila Cangi, (2021). Accelerating Multiscale Materials Modeling with Machine Learning https://doi.org/10.2172/1853873 Publication ID: 77423

Aidan Thompson, (2021). Generalization of SNAP to Arbitrary Machine-Learning Interatomic Potentials in LAMMPS https://doi.org/10.2172/1856085 Publication ID: 77680

Yury Lysogorskiy, Matteo Rinaldi, Sarath Menon, Cas van der Oord, Thomas Hammerschmidt, Matous Mrovec, Aidan Thompson, Gabor Csanyi, Christoph Ortner, Ralf Drautz, (2021). Performant implementation of the atomic cluster expansion https://doi.org/10.2172/1772296 Publication ID: 77681

Daniel Dunlavy, Daniel Dunlavy, (2021). Questa High Performance Data Analytics https://www.osti.gov/servlets/purl/1855745 Publication ID: 77618

James Fox, Beatriz Gonzalez, Rampi Ramprasad, Sivasankaran Rajamanickam, Le Song, (2021). Concentric Spherical GNN for 3D Representation Learning https://doi.org/10.2172/1854067 Publication ID: 77431

Brian Kelley, Sivasankaran Rajamanickam, (2021). Graph Coarsening Techniques for GPUs and Manycore CPUs https://doi.org/10.2172/1854071 Publication ID: 77434

Jennifer Loe, Christian Glusa, Ichitaro Yamazaki, Erik Boman, Sivasankaran Rajamanickam, (2021). Multiprecision Krylov Solvers in Kokkos and Belos https://doi.org/10.2172/1854310 Publication ID: 77452

Gordon Moon, Sivasankaran Rajamanickam, (2021). Mixed-Precision Schemes for Linear Algebra Kernels on GPUs https://doi.org/10.2172/1854428 Publication ID: 77471

Hartwig Anzt, Jennifer Loe, Sivasankaran Rajamanickam, (2021). xSDK Focus Effort Developing Multiprecision Numerics https://doi.org/10.2172/1856293 Publication ID: 77691

Raveesh Garg, Eric Qin, Francisco Martinez, Robert Guirado, Akshay Jain, Sergi Abadal, Jose Abellan, Manuel Acacio, Eduard Alarcon, Sivasankaran Rajamanickam, Tushar Krishna, (2021). A Taxonomy for Classification and Comparison of Dataflows for GNN Accelerators https://doi.org/10.2172/1817326 Publication ID: 77576

James Fox, Bo Zhao, Sivasankaran Rajamanickam, Rampi Ramprasad, Le Song, (2021). Concentric Spherical GNN for 3D Representation Learning https://doi.org/10.2172/1772205 Publication ID: 77664

Cannada Lewis, Clayton Hughes, Simon Hammond, Sivasankaran Rajamanickam, (2021). Using MLIR Framework for Codesign of ML Architectures Algorithms and Simulation Tools https://doi.org/10.2172/1764336 Publication ID: 75211

Laura Swiler, (2021). Epistemic Uncertainty: Computation and Usage https://doi.org/10.2172/1845192 Publication ID: 76636

Laura Swiler, Mamikon Gulian, A. Frankel, Cosmin Safta, John Jakeman, (2021). Constrained Gaussian Processes: A Survey https://doi.org/10.2172/1847480 Publication ID: 77280

Teresa Portone, Laura Swiler, Gianluca Geraci, Michael Eldred, (2021). Application of Multifidelity Uncertainty Quantification Methods to a Subsurface Transport Model https://doi.org/10.2172/1847219 Publication ID: 77339

Bert Debusschere, Gianluca Geraci, John Jakeman, Cosmin Safta, Laura Swiler, (2021). Polynomial Chaos Expansions for Discrete Random Variables in Cyber Security Emulytics Experiments https://doi.org/10.2172/1847628 Publication ID: 77383

Mary Cusentino, Mitchell Wood, Aidan Thompson, (2021). Development of Machine Learned SNAP Potentials for Studying Radiation Damage in Materials https://doi.org/10.2172/1847209 Publication ID: 77316

Roberto Gioiosa, Sivasankaran Rajamanickam, Tushar Krishna, (2021). ARIAA: Center for co-design of ARtificial Intelligence focused Architectures and Algorithms https://www.osti.gov/servlets/purl/1847620 Publication ID: 77225

Sivasankaran Rajamanickam, Tushar Krishna, Simon Hammond, (2021). Vision for Co-designing a Unified-Memory Centric Heterogeneous Node Architecture https://www.osti.gov/servlets/purl/1847621 Publication ID: 77226

Brian Zinser, Samuel Blake, Robert Pfeiffer, Andy Huang, John Himbele, Brian Freno, Vinh Dang, Joseph Kotulski, Sivasankaran Rajamanickam, William Johnson, Salvatore Campione, William Langston, (2021). Gemma: An Electromagnetic Code for Heterogeneous Computer Architectures https://www.osti.gov/servlets/purl/1847565 Publication ID: 77268

Laura Swiler, (2021). Uncertainty and Sensitivity Analysis Overview https://www.osti.gov/servlets/purl/1840824 Publication ID: 75026

Laura Swiler, Sarah Newman, Andrea Staid, Emily Barrett, (2021). Dakota-NAERM Integration https://doi.org/10.2172/1762833 Publication ID: 75059

Laura Swiler, (2021). Uncertainty Analysis of a Medical Resource Demand Model https://www.osti.gov/servlets/purl/1841815 Publication ID: 75093

Gianluca Geraci, Jonathan Crussell, Laura Swiler, Bert Debusschere, (2021). Exploration of multifidelity UQ sampling strategies for computer network applications International Journal for Uncertainty Quantification https://doi.org/10.1615/Int.J.UncertaintyQuantification.2021033774 Publication ID: 76015

George Laity, Allen Robinson, Michael Cuneo, Mary Alam, Kristian Beckwith, Nichelle Bennett, Matthew Bettencourt, Stephen Bond, Kyle Cochrane, Louise Criscenti, Eric Cyr, Karen De Zetter, Richard Drake, Evstati Evstatiev, Andrew Fierro, Thomas Gardiner, Forrest Glines, Ronald Goeke, Nathaniel Hamlin, Russell Hooper, Jason Koski, James Lane, Steven Larson, Kevin Leung, Duncan McGregor, Philip Miller, Sean Miller, Susan Ossareh, Edward Phillips, Sean Simpson, David Sirajuddin, Thomas Smith, Matthew Swan, Aidan Thompson, Julien Tranchida, Asa Bortz-Johnson, Dale Welch, Alex Russell, Eric Watson, David Rose, Ryan McBride, (2021). Towards Predictive Plasma Science and Engineering through Revolutionary Multi-Scale Algorithms and Models (Final Report) https://doi.org/10.2172/1813907 Publication ID: 75144

Stephen Olivier, Nathan Ellingwood, Jonathan Berry, Daniel Dunlavy, (2021). Performance Portability of an SpMV Kernel Across Scientific Computing and Data Science Applications 2021 IEEE High Performance Extreme Computing Conference, HPEC 2021 https://doi.org/10.1109/HPEC49654.2021.9622869 Publication ID: 75415

Jeremy Myers, Daniel Dunlavy, (2021). Using Computation Effectively for Scalable Poisson Tensor Factorization: Comparing Methods beyond Computational Efficiency 2021 IEEE High Performance Extreme Computing Conference, HPEC 2021 https://doi.org/10.1109/HPEC49654.2021.9622795 Publication ID: 75420

Vinh Dang, Joseph Kotulski, Sivasankaran Rajamanickam, (2021). ADELUS: A Performance-Portable Dense LU Solver for Distributed-Memory Hardware-Accelerated Systems Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) https://doi.org/10.1007/978-3-030-74224-9_5 Publication ID: 71441

Vinh Dang, Joseph Kotulski, Sivasankaran Rajamanickam, (2021). ADELUS: A Performance-Portable Dense LU Solver for Distributed-Memory Hardware-Accelerated Systems https://www.osti.gov/servlets/purl/1841514 Publication ID: 75074

Alexander Heinlein, Mauro Perego, Sivasankaran Rajamanickam, (2021). FROSch Preconditioners for Land Ice Simulations of Greenland and Antarctica https://doi.org/10.2172/1763446 Publication ID: 75145

Geonhwa Jeong, Gokcen Kestor, Prasanth Chatarasi, Angshuman Parashar, Po Tsai, Sivasankaran Rajamanickam, Roberto Gioiosa, Tushar Krishna, (2021). Union: A Unified HW-SW Co-Design Ecosystem in MLIR for Evaluating Tensor Operations on Spatial Accelerators Parallel Architectures and Compilation Techniques – Conference Proceedings, PACT https://doi.org/10.1109/PACT52795.2021.00010 Publication ID: 75221

Mary Cusentino, Mitchell Wood, Aidan Thompson, (2020). Machine Learned SNAP Potentials for Materials Modeling https://www.osti.gov/servlets/purl/1837138 Publication ID: 72253

Mary Cusentino, M. Wood, Aidan Thompson, (2020). Suppression of helium bubble nucleation in beryllium exposed tungsten surfaces Nuclear Fusion https://doi.org/10.1088/1741-4326/abb148 Publication ID: 74702

Wenlong Yu, Jamie Elias, Kuan Chen, Ryan Baumbach, T. Nenoff, Normand Modine, W. Pan, Erik Henriksen, (2020). Electronic transport properties of a lithium-decorated ZrTe5 thin film Scientific Reports https://doi.org/10.1038/s41598-020-60545-x Publication ID: 70603

Sivasankaran Rajamanickam, (2020). Towards simulations on the Exascale hardware and beyond https://www.osti.gov/servlets/purl/1835223 Publication ID: 72128

Jennifer Loe, Sivasankaran Rajamanickam, Erik Boman, Hartwig Anzt, (2020). ECP Multiprecision Project Review Slides https://www.osti.gov/servlets/purl/1835661 Publication ID: 72171

Sivasankaran Rajamanickam, (2020). ECP Review : CLOVER Kokkos Kernels https://www.osti.gov/servlets/purl/1835974 Publication ID: 72208

Alexander Heinlein, Mauro Perego, Sivasankaran Rajamanickam, (2020). FROSch Preconditioners for Land Ice Simulations of Greenland and Antarctica https://doi.org/10.2172/1835979 Publication ID: 72213

Christian Glusa, Erik Boman, Edmond Chow, Sivasankaran Rajamanickam, Daniel Szyld, (2020). Scalable asynchronous domain decomposition solvers SIAM Journal on Scientific Computing https://doi.org/10.1137/19m1291303 Publication ID: 74483

J. Lane, Aidan Thompson, I. Srivastava, Gary Grest, Tommy Ao, B. Stoltzfus, K. Austin, H. Fan, D. Morgan, Marcus Knudson, (2020). Scale and rate in CdS pressure-induced phase transition AIP Conference Proceedings https://doi.org/10.1063/12.0001041 Publication ID: 64804

Kathryn Maupin, Laura Swiler, (2020). Model Discrepancy Calibration and Propagation Across Experimental Settings https://doi.org/10.2172/1833158 Publication ID: 71936

Jennifer Loe, Christian Glusa, Erik Boman, Ichitaro Yamazaki, Sivasankaran Rajamanickam, (2020). Multiprecision Krylov Solvers in Trilinos https://www.osti.gov/servlets/purl/1829961 Publication ID: 71611

Ian Bogle, Erik Boman, Karen Devine, Sivasankaran Rajamanickam, George Slota, (2020). Distributed Memory Graph Coloring Algorithms for Multiple GPUs Proceedings of IA3 2020: 10th Workshop on Irregular Applications: Architectures and Algorithms, Held in conjunction with SC 2020: The International Conference for High Performance Computing, Networking, Storage and Analysis https://www.osti.gov/servlets/purl/1825836 Publication ID: 71218

Luca Bertagna, Oksana Guba, Mark Taylor, James Foucar, Jeff Larkin, Andrew Bradley, Sivasankaran Rajamanickam, Andrew Salinger, (2020). A performance-portable nonhydrostatic atmospheric dycore for the energy exascale earth system model running at cloud-resolving resolutions International Conference for High Performance Computing, Networking, Storage and Analysis, SC https://doi.org/10.2172/1830973 Publication ID: 71253

Vinh Dang, Joseph Kotulski, Sivasankaran Rajamanickam, (2020). ADELUS: A Performance-Portable Dense LU Solver for Distributed-Memory Hardware-Accelerated Systems https://doi.org/10.2172/1831759 Publication ID: 71778

Sivasankaran Rajamanickam, (2020). AMD Meeting ? Trilinos / Kokkos Kernels requirements https://www.osti.gov/servlets/purl/1831762 Publication ID: 71783

Sivasankaran Rajamanickam, (2020). Panel:. AI4S Workshop on Artifical Intelligence and Machine Learning for Scientific Applications https://doi.org/10.2172/1882040 Publication ID: 71788

Jennifer Loe, Christian Glusa, Erik Boman, Ichitaro Yamazaki, Sivasankaran Rajamanickam, (2020). Multiprecision GMRES in Trilinos packages Belos and Kokkos https://doi.org/10.2172/1832692 Publication ID: 71889

Sivasankaran Rajamanickam, (2020). FASTMath one slide package summary https://www.osti.gov/servlets/purl/1833147 Publication ID: 71922

Jennifer Loe, Christian Glusa, Ichitaro Yamazaki, Erik Boman, Sivasankaran Rajamanickam, (2020). Mixed-Precision GMRES in Trilinos https://doi.org/10.2172/1833786 Publication ID: 71988

Benjamin Emery, Andrea Staid, Laura Swiler, (2020). Sensitivity and Uncertainty Analysis of Generator Failures under Extreme Temperature Scenarios in Power Systems https://doi.org/10.2172/1808746 Publication ID: 71307

Ian Bogle, Erik Boman, Karen Devine, Sivasankaran Rajamanickam, George Slota, (2020). Distributed Graph Coloring on Multiple GPUs https://doi.org/10.2172/1825832 Publication ID: 71214

Sivasankaran Rajamanickam, (2020). Intersection of Machine Learning and Scientific Simulations: Architectures and Applications perspectives https://doi.org/10.2172/1826454 Publication ID: 71287

Sivasankaran Rajamanickam, (2020). Panel:. How to broaden compiler/architecture research participants by utilizing modern infrastructures https://doi.org/10.2172/1830908 Publication ID: 71440

Keita Teranishi, Daniel Dunlavy, Jeremy Myers, Richard Barrett, (2020). SparTen: Leveraging Kokkos for On-node Parallelism in a Second-Order Method for Fitting Canonical Polyadic Tensor Models to Poisson Data 2020 IEEE High Performance Extreme Computing Conference, HPEC 2020 https://www.osti.gov/servlets/purl/1822300 Publication ID: 70939

Jeremy Myers, Daniel Dunlavy, Keita Teranishi, David Hollman, (2020). Parameter Sensitivity Analysis of the SparTen High Performance Sparse Tensor Decomposition Software 2020 IEEE High Performance Extreme Computing Conference, HPEC 2020 https://www.osti.gov/servlets/purl/1820264 Publication ID: 74785

Stan Moore, Aidan Thompson, (2020). Solidification Kinetics https://www.osti.gov/servlets/purl/1822625 Publication ID: 70962

James Stewart, Normand Modine, Remi Dingreville, (2020). Re-examining the silicon self-interstitial charge states and defect levels: A density functional theory and bounds analysis study AIP Advances https://doi.org/10.1063/5.0016134 Publication ID: 74461

Ian Bogle, Erik Boman, Karen Devine, Sivasankaran Rajamanickam, George Slota, (2020). Distributed Memory Graph Coloring Algorithms for Multiple GPUs https://www.osti.gov/servlets/purl/1820897 Publication ID: 74843

Gordon Moon, J. Ellis, Aravind Sukumaran-Rajam, Srinivasan Parthasarathy, P. Sadayappan, (2020). ALO-NMF: Accelerated Locality-Optimized Non-negative Matrix Factorization Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining https://www.osti.gov/servlets/purl/1808262 Publication ID: 74051

Anh Tran, Timothy Wildey, Julien Tranchida, Aidan Thompson, (2020). Multi-fidelity machine-learning with uncertainty quantification and Bayesian optimization for materials design: Application to ternary random alloys Journal of Chemical Physics https://doi.org/10.1063/5.0015672 Publication ID: 73589

Ichitaro Yamazaki, Sivasankaran Rajamanickam, Nathan Ellingwood, (2020). Performance Portable Supernode-based Sparse Triangular Solver for Manycore Architectures ACM International Conference Proceeding Series https://www.osti.gov/servlets/purl/1813285 Publication ID: 74474

Anh Tran, John Mitchell, Laura Swiler, Tim Wildey, (2020). An active learning high-throughput microstructure calibration framework for solving inverse structure–process problems in materials informatics Acta Materialia https://doi.org/10.1016/j.actamat.2020.04.054 Publication ID: 73364

Mamikon Gulian, Laura Swiler, A. Frankel, Cosmin Safta, John Jakeman, (2020). A Survey of Constrained Gaussian Process Regression: Approaches and Implementation Challenges https://www.osti.gov/servlets/purl/1814448 Publication ID: 74592

Ichitaro Yamazaki, Sivasankaran Rajamanickam, Nathan Ellingwood, (2020). Performance Portable Supernode-based Sparse Triangular Solver for Manycore Architecture https://www.osti.gov/servlets/purl/1814123 Publication ID: 74572

Luca Bertagna, Oksana Guba, Mark Taylor, James Foucar, Jeff Larkin, Andrew Bradley, Sivasankaran Rajamanickam, Andrew Salinger, (2020). A performance-portable nonhydrostatic atmospheric dycore for the Energy Exascale Earth System Model running at cloud-resolving resolutions https://www.osti.gov/servlets/purl/1818055 Publication ID: 74689

Sean DeRosa, Patrick Finley, Melissa Finley, Walter Beyeler, Daniel Krofcheck, Christopher Frazier, Laura Swiler, Teresa Portone, Erin Acquesta, Paula Austin, Drew Levin, Robert Taylor, Katherine Tremba, Monear Makvandi, Ann Hammer, Chad Davis, (2020). COVID-19 Medical Resource Demands https://www.osti.gov/servlets/purl/1807655 Publication ID: 74013

Mamikon Gulian, Laura Swiler, A. Frankel, John Jakeman, Cosmin Safta, (2020). A Survey of Constrained Gaussian Process Regression: Approaches and Implementation Challenges https://www.osti.gov/servlets/purl/1812282 Publication ID: 74359

Aidan Thompson, (2020). Machine-Learning Potentials: The Unreasonable Effectiveness of Linear Cluster Expansions https://www.osti.gov/servlets/purl/1811808 Publication ID: 74284

Daniel Dunlavy, (2020). Tensor Decompositions for Analyzing Multi-Way Data https://www.osti.gov/servlets/purl/1809204 Publication ID: 74146

Scott Heidbrink, Daniel Dunlavy, Kathryn Rodhouse, (2020). Multimodal Deep Learning for Flaw Detection in Software Programs https://www.osti.gov/servlets/purl/1811608 Publication ID: 74247

Sivasankaran Rajamanickam, (2020). Recent experiences withMachine Learning Perspectives fromAlgorithms Architectures and Applications https://www.osti.gov/servlets/purl/1812175 Publication ID: 74354

J. Ellis, (2020). Accelerating Multiscale Materials Modeling with Machine Learning https://www.osti.gov/servlets/purl/1808782 Publication ID: 74105

Laura Swiler, Teresa Portone, (2020). Uncertainty Analysis of a COVID-19 Medical Resource Model https://www.osti.gov/servlets/purl/1807392 Publication ID: 73743

Jonathan Bisila, Daniel Dunlavy, Zoe Gastelum, Craig Ulmer, (2020). TOPIC MODELING WITH NATURAL LANGUAGE PROCESSING FOR IDENTIFICATION OF NUCLEAR PROLIFERATION-RELEVANT SCIENTIFIC AND TECHNICAL PUBLICATIONS https://www.osti.gov/servlets/purl/1807413 Publication ID: 73765

Jeremy Myers, Daniel Dunlavy, Keita Teranishi, David Hollman, (2020). Parameter Sensitivity Analysis of the SparTen High Performance Sparse Tensor Decomposition Software https://www.osti.gov/servlets/purl/1798424 Publication ID: 73836

Keita Teranishi, Daniel Dunlavy, Jeremy Myers, Richard Barrett, (2020). SparTen: Leveraging Kokkos for On-node Parallelism in a Second-Order Method for Fitting Canonical Polyadic Tensor Models to Poisson Data https://www.osti.gov/servlets/purl/1798425 Publication ID: 73837

Jonathan Bisila, Daniel Dunlavy, Zoe Gastelum, Craig Ulmer, (2020). TOPIC MODELING WITH NATURAL LANGUAGE PROCESSING FOR IDENTIFICATION OF NUCLEAR PROLIFERATION-RELEVANT SCIENTIFIC AND TECHNICAL PUBLICATIONS https://www.osti.gov/servlets/purl/1805335 Publication ID: 73955

J. Ellis, Sivasankaran Rajamanickam, (2020). Accelerating Multiscale Materials Modeling with Machine Learning https://www.osti.gov/servlets/purl/1787726 Publication ID: 73650

J. Ellis, Sivasankaran Rajamanickam, (2020). Scalable Inference for Sparse Deep Neural Networks using Kokkos Kernels https://doi.org/10.1109/HPEC.2019.8916378 Publication ID: 73651

Ichitaro Yamazaki, Sivasankaran Rajamanickam, Nathan Ellingwood, (2020). Supernode-based Sparse Triangular Solver using Kokkos https://www.osti.gov/servlets/purl/1804644 Publication ID: 73856

Nathan Ellingwood, Sivasankaran Rajamanickam, (2020). Practices and Challenges of Software Development for a Performance Portable Ecosystem https://www.osti.gov/servlets/purl/1805332 Publication ID: 73951

Gordon Moon, J. Ellis, Aravind Sukumaran-Rajam, Srinivasan Parthasarathy, P. Sadayappan, (2020). ALO-NMF: Accelerated Locality-Optimized Non-negative Matrix Factorization https://www.osti.gov/servlets/purl/1807411 Publication ID: 73763

Gordon Moon, J. Ellis, Aravind Sukumaran-Rajam, Srinivasan Parthasarathy, P. Sadayappan, (2020). ALO-NMF: Accelerated Locality-Optimized Non-negative Matrix Factorization https://www.osti.gov/servlets/purl/1798068 Publication ID: 73822

Walter Beyeler, Christopher Frazier, Laura Swiler, Teresa Portone, Daniel Krofcheck, (2020). Treatment Model Design and Use https://www.osti.gov/servlets/purl/1783073 Publication ID: 73474

Laura Swiler, Teresa Portone, Walter Beyeler, (2020). Uncertainty analysis of Resource Demand Model for Covid-19 https://doi.org/10.2172/1630395 Publication ID: 73459

Seher Acer, Erik Boman, Sivasankaran Rajamanickam, (2020). SPHYNX: Spectral partitioning for HYbrid and aXelerator-enabled systems Proceedings – 2020 IEEE 34th International Parallel and Distributed Processing Symposium Workshops, IPDPSW 2020 https://www.osti.gov/servlets/purl/1771942 Publication ID: 73087

Gordon Moon, Sivasankaran Rajamanickam, Tushar Krishna, Hyoukjun Kwon, Prasanth Chatarasi, Eric Qin, (2020). Utilizing Spatial Accelerators for Machine Learning and Linear Algebra Kernels https://www.osti.gov/servlets/purl/1782497 Publication ID: 73425

Eric Qin, Geonhwa Jeong, William Won, Sheng-Chun Kao, Hyoukjun Kwon, Sudarshan Srinivasan, Dipankar Das, Gordon Moon, Sivasankaran Rajamanickam, Tushar Krishna, (2020). MINT: Microarchitecture for Efficient and Interchangeable CompressioN Formats on Tensor Algebra https://www.osti.gov/servlets/purl/1782675 Publication ID: 73435

Seher Acer, Erik Boman, Sivasankaran Rajamanickam, (2020). SPHYNX: Spectral Partitioning for HYbrid aNd aXelerator-based systems https://www.osti.gov/servlets/purl/1783066 Publication ID: 73470

Joseph Kotulski, Vinh Dang, Sivasankaran Rajamanickam, (2020). ADELUS: A Performance-Portable Dense LU Solver for Distributed-Memory Hardware-Accelerated Systems https://www.osti.gov/servlets/purl/1783676 Publication ID: 73584

Aidan Thompson, Mitchell Wood, Attila Cangi, Michael Desjarlais, Julien Tranchida, (2020). Improving the accuracy of spin-lattice simulations with machine-learning interatomic potentials https://www.osti.gov/servlets/purl/1778150 Publication ID: 73267

Jim Ang, Christine Sweeney, Michael Wolf, J. Ellis, Sayan Ghosh, Ai Kagawa, Yunzhi Huang, Sivasankaran Rajamanickam, Vinay Ramakrishnaiah, Malachi Schram, Shinjae Yoo, (2020). ECP Report: Update on Proxy Applications and Vendor Interactions https://doi.org/10.2172/1608914 Publication ID: 73225

Kathryn Maupin, Laura Swiler, (2020). Calibration Propagation and Validation of Model Discrepancy Across Experimental Settings https://www.osti.gov/servlets/purl/1769563 Publication ID: 72925

Mitchell Wood, Mary Cusentino, Aidan Thompson, (2020). Scale-Bridging From DFT to MD with Machine Learning https://www.osti.gov/servlets/purl/1766923 Publication ID: 72603

Mary Cusentino, Mitchell Wood, Aidan Thompson, (2020). Molecular Dynamics Simulations of Mixed Materials in Tungsten https://www.osti.gov/servlets/purl/1766750 Publication ID: 72638

Judith Brown, D. Kittell, Mitchell Wood, Aidan Thompson, Dan Bolintineanu, (2020). Multiscale modeling to study effects of microstructure in shocked hexanitrostilbene https://www.osti.gov/servlets/purl/1767897 Publication ID: 72758

Mitchell Wood, Steven Plimpton, Aidan Thompson, Danny Perez, Anders Niklasson, (2020). A Path to the Exascale for Atomistic Simulations with Improved Accuracy Length and Time Scales https://www.osti.gov/servlets/purl/1783582 Publication ID: 72854

Aidan Thompson, (2020). Predictive Atomistic Simulations of Materials using SNAP Data-Driven Potentials https://www.osti.gov/servlets/purl/1783594 Publication ID: 72866

Keita Teranishi, David Hollman, Jeremy Myers, Daniel Dunlavy, (2020). Performance and Parallelization of CP-Alternate Poisson Regression Sparse Tensor Decomposition https://www.osti.gov/servlets/purl/1766745 Publication ID: 72606

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May 9, 2023