Publications

Gerber, Richard, Balint Joo, and Scott Parker. 2024. “Deploying Optimized Scientific and Engineering Applications on Exascale Systems.” Computing in Science & Engineering 26 (1): 41–47. https://doi.org/10.1109/mcse.2024.3397209.

Adamson, Ryan, Paul Bryant, Dave Montoya, Jeff Neel, Erik Palmer, Ray Powell, Ryan Prout, and Peter Upton. 2024. “Creating Continuous Integration Infrastructure for Software Development on U.S. Department of Energy High-Performance Computing Systems.” Computing in Science & Engineering 26 (1): 31–39. https://doi.org/10.1109/mcse.2024.3362586.

McInnes, Lois Curfman, Michael A. Heroux, David E. Bernholdt, Anshu Dubey, Elsa Gonsiorowski, Rinku Gupta, Osni Marques, et al. 2024. “A Cast of Thousands: How the IDEAS Productivity Project Has Advanced Software Productivity and Sustainability.” Computing in Science & Engineering 26 (1): 48–60. https://doi.org/10.1109/mcse.2024.3383799.

Heroux, Michael A. 2024. “Scalable Delivery of Scalable Libraries and Tools: How ECP Delivered a Software Ecosystem for Exascale and Beyond.” Computing in Science & Engineering 26 (1): 9–18. https://doi.org/10.1109/mcse.2024.3384937.

Anzt, Hartwig, Axel Huebl, and Xiaoye S. Li. 2024. “Then and Now: Improving Software Portability, Productivity, and 100× Performance.” Computing in Science & Engineering 26 (1): 61–70. https://doi.org/10.1109/mcse.2024.3387302.

Willenbring, James M., Sameer S. Shende, and Todd Gamblin. 2024. “Providing a Flexible and Comprehensive Software Stack Via Spack, an Extreme-Scale Scientific Software Stack, and Software Development Kits.” Computing in Science & Engineering 26 (1): 20–30. https://doi.org/10.1109/mcse.2024.3395016.

Oehmen, Christopher S., Slaven Peles, Katarzyna Swirydowicz, Cosmin G. Petra, Shrirang G. Abhyankar, Wesley Jones, Matthew Reynolds, and Robert C. Rutherford. 2024. “Advanced Computing Is at the Forefront of a New ‘Moonshot’ Revolutionizing the North American Power Grid.” Computing in Science & Engineering, 1–13. https://doi.org/10.1109/mcse.2024.3403029.

Reeve, Samuel Temple, Jean-Luc Fattebert, Stephen DeWitt, David Joy, Pablo Seleson, Stuart Slattery, Aaron Scheinberg, et al. 2024. “Co-Design for Particle Applications at Exascale.” Computing in Science & Engineering, 1–10. https://doi.org/10.1109/mcse.2024.3384052.

Hofmeyr, Steven, Aydin Buluç, Robert Riley, Rob Egan, Oguz Selvitopi, Leonid Oliker, Katherine Yelick, Migun Shakya, Brett Youtsey, and Ariful Azad. 2024. “Exabiome: Advancing Microbial Science through Exascale Computing.” Computing in Science & Engineering, 1–8. https://doi.org/10.1109/mcse.2024.3402546.

McCallen, D., A. Pitarka, H. Tang, R. Pankajakshan, N.A. Petersson, and M. Miah. 2024. “Transformational Regional-Scale Earthquake Simulations with the DOE EarthQuake SIMulation (EQSIM) Exascale Framework.” Computing in Science & Engineering, 1–12. https://doi.org/10.1109/mcse.2024.3397768.

Molins, Sergi, David Trebotich, and Carl I. Steefel. 2024. “Approaches for the Simulation of Coupled Processes in Evolving Fractured Porous Media Enabled by Exascale Computing.” Computing in Science & Engineering, 1–10. https://doi.org/10.1109/mcse.2024.3403983.

Pavlopoulos, Georgios A., Fotis A. Baltoumas, Sirui Liu, Oguz Selvitopi, Antonio Pedro Camargo, Stephen Nayfach, Ariful Azad, et al. 2023. “Unraveling the Functional Dark Matter through Global Metagenomics.” Nature 622 (7983): 594–602. https://doi.org/10.1038/s41586-023-06583-7.

Hategan-Marandiuc, Mihael, Andre Merzky, Nicholson Collier, Ketan Maheshwari, Jonathan Ozik, Matteo Turilli, Andreas Wilke, et al. 2023. “PSI/J: A Portable Interface for Submitting, Monitoring, and Managing Jobs.” 2023 IEEE 19th International Conference on E-Science (e-Science), October. https://doi.org/10.1109/e-science58273.2023.10254912.

Henry De Frahan, Marc T., Mohammad J. Rahimi, Olga Doronina, Bruce A. Perry, Shashank Yellapantula, Ian Cormier, Marc Day, and Michael James Martin. 2023. “Simulation of Methane Oxycombustion in Supercritical Carbon Dioxide.” Volume 12: Supercritical CO2, June. https://doi.org/10.1115/gt2023-101568.

Kang, Hyun-Gyu, Raymond S Tuminaro, Andrey Prokopenko, Seth R Johnson, Andrew G Salinger, and Katherine J Evans. 2023. “An Implicit Barotropic Mode Solver for MPAS-Ocean Using a Modern Fortran Solver Interface.” The International Journal of High Performance Computing Applications 38 (3): 175–91. https://doi.org/10.1177/10943420231205601.

Yoshii, Kazutomo, John Tramm, Bryce Allen, Tomohiro Ueno, Kentaro Sano, Andrew Siegel, and Pete Beckman. 2023. “Hardware Specialization: Estimating Monte Carlo Cross-Section Lookup Kernel Performance and Area.” Proceedings of the SC ’23 Workshops of The International Conference on High Performance Computing, Network, Storage, and Analysis, November. https://doi.org/10.1145/3624062.3625534.

Xiang, Lizhi, Arif Khan, S. M. Ferdous, Sr Aravind, and Mahantesh Halappanavar. 2023. “CuAlign: Scalable Network Alignment on GPU Accelerators.” Proceedings of the SC ’23 Workshops of The International Conference on High Performance Computing, Network, Storage, and Analysis, November. https://doi.org/10.1145/3624062.3625129.

Wang, Daoce, Jesus Pulido, Pascal Grosset, Jiannan Tian, James Ahrens, and Dingwen Tao. 2023. “Analyzing Impact of Data Reduction Techniques on Visualization for AMR Applications Using AMReX Framework.” Proceedings of the SC ’23 Workshops of The International Conference on High Performance Computing, Network, Storage, and Analysis, November. https://doi.org/10.1145/3624062.3625123.

Underwood, Robert R., Sheng Di, Sian Jin, Md Hasanur Rahman, Arham Khan, and Franck Cappello. 2023. “LibPressio-Predict: Flexible and Fast Infrastructure For Inferring Compression Performance.” Proceedings of the SC ’23 Workshops of The International Conference on High Performance Computing, Network, Storage, and Analysis, November. https://doi.org/10.1145/3624062.3625124.

Sukkari, Dalal, Mark Gates, Mohammed Al Farhan, Hartwig Anzt, and Jack Dongarra. 2023. “Task-Based Polar Decomposition Using SLATE on Massively Parallel Systems with Hardware Accelerators.” Proceedings of the SC ’23 Workshops of The International Conference on High Performance Computing, Network, Storage, and Analysis, November. https://doi.org/10.1145/3624062.3624248.

Sarpangala Venkatesh, Ranjan, Greg Eisenhauer, Scott Klasky, and Ada Gavrilovska. 2023. “Enhancing Metadata Transfer Efficiency: Unlocking the Potential of DAOS in the ADIOS Context.” Proceedings of the SC ’23 Workshops of The International Conference on High Performance Computing, Network, Storage, and Analysis, November. https://doi.org/10.1145/3624062.3624193.

Roa Perdomo, Diego A., Rodrigo Ceccato, Rémy Neveu, Hervé Yviquel, Xiaoming Li, Jose M. Monsalve Diaz, and Johannes Doerfert. 2023. “Memory Transfer Decomposition: Exploring Smart Data Movement Through Architecture-Aware Strategies.” Proceedings of the SC ’23 Workshops of The International Conference on High Performance Computing, Network, Storage, and Analysis, November. https://doi.org/10.1145/3624062.3624609.

Ribizel, Tobias, and Hartwig Anzt. 2023. “Parallel Symbolic Cholesky Factorization.” Proceedings of the SC ’23 Workshops of The International Conference on High Performance Computing, Network, Storage, and Analysis, November. https://doi.org/10.1145/3624062.3624253.

Rangel, Esteban Miguel, Simon John Pennycook, Adrian Pope, Nicholas Frontiere, Zhiqiang Ma, and Varsha Madananth. 2023. “A Performance-Portable SYCL Implementation of CRK-HACC for Exascale.” Proceedings of the SC ’23 Workshops of The International Conference on High Performance Computing, Network, Storage, and Analysis, November. https://doi.org/10.1145/3624062.3624187.

Nguyen, Phuong, Pratik Nayak, and Hartwig Anzt. 2023. “Porting Batched Iterative Solvers onto Intel GPUs with SYCL.” Proceedings of the SC ’23 Workshops of The International Conference on High Performance Computing, Network, Storage, and Analysis, November. https://doi.org/10.1145/3624062.3624181.

Luettgau, Jakob, Shane Snyder, Tyler Reddy, Nikolaus Awtrey, Kevin Harms, Jean Luca Bez, Rui Wang, Rob Latham, and Philip Carns. 2023. “Enabling Agile Analysis of I/O Performance Data with PyDarshan.” Proceedings of the SC ’23 Workshops of The International Conference on High Performance Computing, Network, Storage, and Analysis, November. https://doi.org/10.1145/3624062.3624207.

Lindsey, LeAnn, Muhammad Haseeb, Hari Sundar, and Muaaz Awan. 2023. “TANGO: A GPU Optimized Traceback Approach for Sequence Alignment Algorithms.” Proceedings of the SC ’23 Workshops of The International Conference on High Performance Computing, Network, Storage, and Analysis, November. https://doi.org/10.1145/3624062.3625128.

Li, Jiali, George Bosilca, Aurelien Bouteiller, and Bogdan Nicolae. 2023. “Elastic Deep Learning through Resilient Collective Operations.” Proceedings of the SC ’23 Workshops of The International Conference on High Performance Computing, Network, Storage, and Analysis, November. https://doi.org/10.1145/3624062.3626080.

Dharuman, Gautham, Logan Ward, Heng Ma, Priyanka V. Setty, Ozan Gokdemir, Sam Foreman, Murali Emani, et al. 2023. “Protein Generation via Genome-Scale Language Models with Bio-Physical Scoring.” Proceedings of the SC ’23 Workshops of The International Conference on High Performance Computing, Network, Storage, and Analysis, November. https://doi.org/10.1145/3624062.3626087.

Dhakal, Aditya, Philipp Raith, Logan Ward, Rolando P. Hong Enriquez, Gourav Rattihalli, Kyle Chard, Ian Foster, and Dejan Milojicic. 2023. “Fine-Grained Accelerator Partitioning for Machine Learning and Scientific Computing in Function as a Service Platform.” Proceedings of the SC ’23 Workshops of The International Conference on High Performance Computing, Network, Storage, and Analysis, November. https://doi.org/10.1145/3624062.3624238.

Carson, Robert, Matt Rolchigo, John Coleman, Mikhail Titov, Jim Belak, and Matt Bement. 2023. “Uncertainty Quantification of Metal Additive Manufacturing Processing Conditions Through the Use of Exascale Computing.” Proceedings of the SC ’23 Workshops of The International Conference on High Performance Computing, Network, Storage, and Analysis, November. https://doi.org/10.1145/3624062.3624103.

Bellavita, Julian, Mathias Jacquelin, Esmond G. Ng, Dan Bonachea, Johnny Corbino, and Paul H. Hargrove. 2023. “SymPACK: A GPU-Capable Fan-Out Sparse Cholesky Solver.” Proceedings of the SC ’23 Workshops of The International Conference on High Performance Computing, Network, Storage, and Analysis, November. https://doi.org/10.1145/3624062.3624600.

Bader, Jonathan, Jim Belak, Matthew Bement, Matthew Berry, Robert Carson, Daniela Cassol, Stephen Chan, et al. 2023. “Novel Approaches Toward Scalable Composable Workflows in Hyper-Heterogeneous Computing Environments.” Proceedings of the SC ’23 Workshops of The International Conference on High Performance Computing, Network, Storage, and Analysis, November. https://doi.org/10.1145/3624062.3626283.

Antepara, Oscar, Samuel Williams, Hans Johansen, Tuowen Zhao, Samantha Hirsch, Priya Goyal, and Mary Hall. 2023. “Performance Portability Evaluation of Blocked Stencil Computations on GPUs.” Proceedings of the SC ’23 Workshops of The International Conference on High Performance Computing, Network, Storage, and Analysis, November. https://doi.org/10.1145/3624062.3624177.

Abdelfattah, Ahmad, Stanimire Tomov, Piotr Luszczek, Hartwig Anzt, and Jack Dongarra. 2023. “GPU-Based LU Factorization and Solve on Batches of Matrices with Band Structure.” Proceedings of the SC ’23 Workshops of The International Conference on High Performance Computing, Network, Storage, and Analysis, November. https://doi.org/10.1145/3624062.3624247.

Lasa, A., S. Blondel, M.A. Cusentino, D. Dasgupta, P. Hatton, J. Marian, D. Perez, et al. 2024. “Development of Multi-Scale Computational Frameworks to Solve Fusion Materials Science Challenges.” Journal of Nuclear Materials 594 (June): 155011. https://doi.org/10.1016/j.jnucmat.2024.155011.

Dhruv, Akash. 2024. “A Vortex Damping Outflow Forcing for Multiphase Flows with Sharp Interfacial Jumps.” Journal of Computational Physics 511 (August): 113122. https://doi.org/10.1016/j.jcp.2024.113122.

Wilson, David J., Christopher E. Thomas, Jozef J. Dudek, and Robert G. Edwards. 2024. “Scalar and Tensor Charmonium Resonances in Coupled-Channel Scattering from Lattice QCD.” Physical Review Letters 132 (24). https://doi.org/10.1103/physrevlett.132.241901.

Wittwer, Felix, Nicholas K. Sauter, Derek Mendez, Billy K. Poon, Aaron S. Brewster, James M. Holton, Michael E. Wall, William E. Hart, Deborah J. Bard, and Johannes P. Blaschke. 2023. “Accelerating X‐ray Tracing for Exascale Systems Using Kokkos.” Concurrency and Computation: Practice and Experience 36 (5). https://doi.org/10.1002/cpe.7944.

Wittwer, Felix, Nicholas K. Sauter, Derek Mendez, Billy K. Poon, Aaron S. Brewster, James M. Holton, Michael E. Wall, William E. Hart, Deborah J. Bard, and Johannes P. Blaschke. 2023. “Accelerating X‐ray Tracing for Exascale Systems Using Kokkos.” Concurrency and Computation: Practice and Experience 36 (5). https://doi.org/10.1002/cpe.7944.

Edwards, Robert, Colin Egerer, Joseph Karpie, Nikhil Karthik, Christopher Monahan, Wayne Morris, Kostas Orginos, et al. 2023. “Non-Singlet Quark Helicity PDFs of the Nucleon from Pseudo-Distributions.” Journal of High Energy Physics 2023 (3). https://doi.org/10.1007/jhep03(2023)086.

Moses, William S., Sri Hari Krishna Narayanan, Ludger Paehler, Valentin Churavy, Michel Schanen, Jan Hückelheim, Johannes Doerfert, and Paul Hovland. 2022. “Scalable Automatic Differentiation of Multiple Parallel Paradigms through Compiler Augmentation.” SC22: International Conference for High Performance Computing, Networking, Storage and Analysis, November. https://doi.org/10.1109/sc41404.2022.00065.

Pajkos, Michael A., Steven J. VanCamp, Kuo-Chuan Pan, David Vartanyan, Nils Deppe, and Sean M. Couch. 2023. “Characterizing the Directionality of Gravitational Wave Emission from Matter Motions within Core-Collapse Supernovae.” The Astrophysical Journal 959 (1): 21. https://doi.org/10.3847/1538-4357/acfca4.

Sattasathuchana, Tosaporn, Peng Xu, Colleen Bertoni, Yu Lim Kim, Sarom S. Leang, Buu Q. Pham, and Mark S. Gordon. 2024. “The Effective Fragment Molecular Orbital Method: Achieving High Scalability and Accuracy for Large Systems.” Journal of Chemical Theory and Computation 20 (6): 2445–61. https://doi.org/10.1021/acs.jctc.3c01309.

Fedeli, Luca, Axel Huebl, France Boillod-Cerneux, Thomas Clark, Kevin Gott, Conrad Hillairet, Stephan Jaure, et al. 2022. “Pushing the Frontier in the Design of Laser-Based Electron Accelerators with Groundbreaking Mesh-Refined Particle-In-Cell Simulations on Exascale-Class Supercomputers.” SC22: International Conference for High Performance Computing, Networking, Storage and Analysis, November. https://doi.org/10.1109/sc41404.2022.00008.

Hsu, Wei‐Ching, Gabriel J. Kooperman, Walter M. Hannah, Kevin A. Reed, Akintomide A. Akinsanola, and Angeline G. Pendergrass. 2023. “Evaluating Mesoscale Convective Systems Over the US in Conventional and Multiscale Modeling Framework Configurations of E3SMv1.” Journal of Geophysical Research: Atmospheres 128 (23). https://doi.org/10.1029/2023jd038740.

Sharma, Ashesh, Michael J. Brazell, Ganesh Vijayakumar, Shreyas Ananthan, Lawrence Cheung, Nathaniel deVelder, Marc T. Henry de Frahan, et al. 2024. “ExaWind: Open‐source CFD for Hybrid‐RANS/LES Geometry‐resolved Wind Turbine Simulations in Atmospheric Flows.” Wind Energy 27 (3): 225–57. https://doi.org/10.1002/we.2886.

Klion, Hannah, Revathi Jambunathan, Michael E. Rowan, Eloise Yang, Donald Willcox, Jean-Luc Vay, Remi Lehe, Andrew Myers, Axel Huebl, and Weiqun Zhang. 2023. “Particle-in-Cell Simulations of Relativistic Magnetic Reconnection with Advanced Maxwell Solver Algorithms.” The Astrophysical Journal 952 (1): 8. https://doi.org/10.3847/1538-4357/acd75b.

Owen, Landon D., Wenjun Ge, Martin Rieth, Marco Arienti, Lucas Esclapez, Bruno S. Soriano, Michael E. Mueller, Marcus Day, Ramanan Sankaran, and Jacqueline H. Chen. 2024. “PeleMP: The Multiphysics Solver for the Combustion Pele Adaptive Mesh Refinement Code Suite.” Journal of Fluids Engineering 146 (4). https://doi.org/10.1115/1.4064494.

Peng, Liran, Peter N. Blossey, Walter M. Hannah, Christopher S. Bretherton, Christopher R. Terai, Andrea M. Jenney, and Michael Pritchard. 2024. “Improving Stratocumulus Cloud Amounts in a 200‐m Resolution Multi‐Scale Modeling Framework Through Tuning of Its Interior Physics.” Journal of Advances in Modeling Earth Systems 16 (3). https://doi.org/10.1029/2023ms003632.

Mutlu, Erdal, Ajay Panyala, Nitin Gawande, Abhishek Bagusetty, Jeffrey Glabe, Jinsung Kim, Karol Kowalski, et al. 2023. “TAMM: Tensor Algebra for Many-Body Methods.” The Journal of Chemical Physics 159 (2). https://doi.org/10.1063/5.0142433.

Andrej, Julian, Nabil Atallah, Jan-Phillip Bäcker, Jean-Sylvain Camier, Dylan Copeland, Veselin Dobrev, Yohann Dudouit, et al. 2024. “High-Performance Finite Elements with MFEM.” The International Journal of High Performance Computing Applications, June. https://doi.org/10.1177/10943420241261981.

Guo, Jicheng, Vanessa Woo, David A. Andersson, Nathaniel Hoyt, Mark Williamson, Ian Foster, Chris Benmore, Nicholas E. Jackson, and Ganesh Sivaraman. 2023. “AL4GAP: Active Learning Workflow for Generating DFT-SCAN Accurate Machine-Learning Potentials for Combinatorial Molten Salt Mixtures.” The Journal of Chemical Physics 159 (2). https://doi.org/10.1063/5.0153021.

Liu, Nana, Michael S. Pritchard, Andrea M. Jenney, and Walter M. Hannah. 2023. “Understanding Precipitation Bias Sensitivities in E3SM‐Multi‐Scale Modeling Framework From a Dilution Framework.” Journal of Advances in Modeling Earth Systems 15 (4). https://doi.org/10.1029/2022ms003460.

Goff, James, Yu Zhang, Christian Negre, Andrew Rohskopf, and Anders M. N. Niklasson. 2023. “Shadow Molecular Dynamics and Atomic Cluster Expansions for Flexible Charge Models.” Journal of Chemical Theory and Computation 19 (13): 4255–72. https://doi.org/10.1021/acs.jctc.3c00349.

Zaïm, Neïl, Antonin Sainte-Marie, Luca Fedeli, Pierre Bartoli, Axel Huebl, Adrien Leblanc, Jean-Luc Vay, and Henri Vincenti. 2024. “Light-Matter Interaction near the Schwinger Limit Using Tightly Focused Doppler-Boosted Lasers.” Physical Review Letters 132 (17). https://doi.org/10.1103/physrevlett.132.175002.

Min, Misun, Michael Brazell, Ananias Tomboulides, Matthew Churchfield, Paul Fischer, and Michael Sprague. 2024. “Towards Exascale for Wind Energy Simulations.” The International Journal of High Performance Computing Applications, May. https://doi.org/10.1177/10943420241252511.

Howarth, T.L., M.S. Day, H. Pitsch, and A.J. Aspden. 2024. “Thermal Diffusion, Exhaust Gas Recirculation and Blending Effects on Lean Premixed Hydrogen Flames.” Proceedings of the Combustion Institute 40 (1–4): 105429. https://doi.org/10.1016/j.proci.2024.105429.

Chen, Yuxin, Benjamin Brock, Serban Porumbescu, Aydin Buluc, Katherine Yelick, and John Owens. 2022. “Atos: A Task-Parallel GPU Scheduler for Graph Analytics.” Proceedings of the 51st International Conference on Parallel Processing, August. https://doi.org/10.1145/3545008.3545056.

Liang, Xin, Sheng Di, Franck Cappello, Mukund Raj, Chunhui Liu, Kenji Ono, Zizhong Chen, Tom Peterka, and Hanqi Guo. 2023. “Toward Feature-Preserving Vector Field Compression.” IEEE Transactions on Visualization and Computer Graphics 29 (12): 5434–50. https://doi.org/10.1109/tvcg.2022.3214821.

Bez, Jean Luca, Suren Byna, and Shadi Ibrahim. 2023. “I/O Access Patterns in HPC Applications: A 360-Degree Survey.” ACM Computing Surveys 56 (2): 1–41. https://doi.org/10.1145/3611007.

Park, Hyunbae, Zarija Lukić, Jean Sexton, Marcelo A. Alvarez, and Paul R. Shapiro. 2024. “Impact of Self-Shielding Minihalos on the Lyα Forest at High Redshift.” The Astrophysical Journal 969 (1): 46. https://doi.org/10.3847/1538-4357/ad4bdc.

Chen, Zhi, Michael Zingale, and Kiran Eiden. 2023. “Sensitivity of He Flames in X-Ray Bursts to Nuclear Physics.” The Astrophysical Journal 955 (2): 128. https://doi.org/10.3847/1538-4357/acec72.

Cosgrove, Paul, and John R. Tramm. 2023. “The Random Ray Method Versus Multigroup Monte Carlo: The Method of Characteristics in OpenMC and SCONE.” Nuclear Science and Engineering, November, 1–20. https://doi.org/10.1080/00295639.2023.2270618.

Hamilton, Aidan, Jing-Mei Qiu, and Hong Zhang. 2023. “Scalable Riemann Solvers with the Discontinuous Galerkin Method for Hyperbolic Network Simulation.” Proceedings of the Platform for Advanced Scientific Computing Conference, June. https://doi.org/10.1145/3592979.3593421.

Zahariev, Federico, Peng Xu, Bryce M. Westheimer, Simon Webb, Jorge Galvez Vallejo, Ananta Tiwari, Vaibhav Sundriyal, et al. 2023. “The General Atomic and Molecular Electronic Structure System (GAMESS): Novel Methods on Novel Architectures.” Journal of Chemical Theory and Computation 19 (20): 7031–55. https://doi.org/10.1021/acs.jctc.3c00379.

Pazner, Will, Tzanio Kolev, and Jean-Sylvain Camier. 2023. “End-to-End GPU Acceleration of Low-Order-Refined Preconditioning for High-Order Finite Element Discretizations.” The International Journal of High Performance Computing Applications 37 (5): 578–99. https://doi.org/10.1177/10943420231175462.

Amorim, Lígia D, Carlo Benedetti, Stepan S Bulanov, Davide Terzani, Axel Huebl, Carl B Schroeder, Jean-Luc Vay, and Eric Esarey. 2023. “Design Study for a Compact, Two-Stage, Laser-Plasma-Based Source of Positron Beams.” Plasma Physics and Controlled Fusion 65 (8): 085016. https://doi.org/10.1088/1361-6587/ace3f1.

Zhang, Pei, Logan Kearney, Debsindhu Bhowmik, Zachary Fox, Amit K. Naskar, and John Gounley. 2023. “Transferring a Molecular Foundation Model for Polymer Property Predictions.” Journal of Chemical Information and Modeling 63 (24): 7689–98. https://doi.org/10.1021/acs.jcim.3c01650.

Clyde, Austin, Xuefeng Liu, Thomas Brettin, Hyunseung Yoo, Alexander Partin, Yadu Babuji, Ben Blaiszik, et al. 2023. “AI-Accelerated Protein-Ligand Docking for SARS-CoV-2 Is 100-Fold Faster with No Significant Change in Detection.” Scientific Reports 13 (1). https://doi.org/10.1038/s41598-023-28785-9.

Abdelfattah, Ahmad, Natalie Beams, Robert Carson, Pieter Ghysels, Tzanio Kolev, Thomas Stitt, Arturo Vargas, Stanimire Tomov, and Jack Dongarra. 2024. “MAGMA: Enabling Exascale Performance with Accelerated BLAS and LAPACK for Diverse GPU Architectures.” The International Journal of High Performance Computing Applications, June. https://doi.org/10.1177/10943420241261960.

Jiao, Pu, Sheng Di, Jinyang Liu, Xin Liang, and Franck Cappello. 2023. “Characterization and Detection of Artifacts for Error-Controlled Lossy Compressors.” 2023 IEEE 30th International Conference on High Performance Computing, Data, and Analytics (HiPC), December. https://doi.org/10.1109/hipc58850.2023.00027.

Norman, Matthew R., Christopher Eldred, and Muralikrishnan Gopalakrishnan Meena. 2023. “Investigating Inherent Numerical Stabilization for the Moist, Compressible, Non‐Hydrostatic Euler Equations on Collocated Grids.” Journal of Advances in Modeling Earth Systems 15 (10). https://doi.org/10.1029/2023ms003732.

Leventhal, Samuel, Attila Gyulassy, Valerio Pascucci, and Mark Heimann. 2023. “Modeling Hierarchical Topological Structure in Scientific Images with Graph Neural Networks.” 2023 IEEE International Conference on Image Processing (ICIP), October. https://doi.org/10.1109/icip49359.2023.10222089.

Tian, Shilei, Barbara Chapman, and Johannes Doerfert. 2023. “Maximizing Parallelism and GPU Utilization For Direct GPU Compilation Through Ensemble Execution.” Proceedings of the 52nd International Conference on Parallel Processing Workshops, August. https://doi.org/10.1145/3605731.3606016.

Wilkins, Michael, Hanming Wang, Peizhi Liu, Bangyen Pham, Yanfei Guo, Rajeev Thakur, Peter Dinda, and Nikos Hardavellas. 2023. “Generalized Collective Algorithms for the Exascale Era.” 2023 IEEE International Conference on Cluster Computing (CLUSTER), October. https://doi.org/10.1109/cluster52292.2023.00013.

Thavappiragasam, Mathialakan, and Vivek Kale. 2023. “CPU-GPU Tuning for Modern Scientific Applications Using Node-Level Heterogeneity.” 2023 IEEE 30th International Conference on High Performance Computing, Data, and Analytics (HiPC), December. https://doi.org/10.1109/hipc58850.2023.00034.

Helal, Hatem, Jesun Firoz, Jenna A. Bilbrey, Henry Sprueill, Kristina M. Herman, Mario Michael Krell, Tom Murray, et al. 2024. “Acceleration of Graph Neural Network-Based Prediction Models in Chemistry via Co-Design Optimization on Intelligence Processing Units.” Journal of Chemical Information and Modeling 64 (5): 1568–80. https://doi.org/10.1021/acs.jcim.3c01312.

Khan, Arham, Sheng Di, Kai Zhao, Jinyang Liu, Kyle Chard, Ian Foster, and Franck Cappello. 2023. “SECRE: Surrogate-Based Error-Controlled Lossy Compression Ratio Estimation Framework.” 2023 IEEE 30th International Conference on High Performance Computing, Data, and Analytics (HiPC), December. https://doi.org/10.1109/hipc58850.2023.00029.

Ghosh, Supriyo, Julien Zollinger, Miha Zaloznik, Dilip Banerjee, Christopher K. Newman, and Raymundo Arroyave. 2023. “Modeling of Hierarchical Solidification Microstructures in Metal Additive Manufacturing: Challenges and Opportunities.” Additive Manufacturing 78 (September): 103845. https://doi.org/10.1016/j.addma.2023.103845.

Wimer, Nicholas T., Lucas Esclapez, Nicholas Brunhart-Lupo, Marc Henry de Frahan, Mohammad Rahimi, Malik Hassanaly, Jon Rood, et al. 2023. “Visualizations of a Methane/Diesel RCCI Engine Using PeleC and PeleLMeX.” Physical Review Fluids 8 (11). https://doi.org/10.1103/physrevfluids.8.110511.

Cheng, Junyi, James Myra, Seung-Hoe Ku, Robert Hager, Choong-Seock Chang, and Scott Parker. 2023. “Transport Barrier and Spinning Blob Dynamics in the Tokamak Edge.” Nuclear Fusion 63 (8): 086015. https://doi.org/10.1088/1741-4326/acdf01.

Ward, Logan, J. Gregory Pauloski, Valerie Hayot-Sasson, Ryan Chard, Yadu Babuji, Ganesh Sivaraman, Sutanay Choudhury, Kyle Chard, Rajeev Thakur, and Ian Foster. 2023. “Cloud Services Enable Efficient AI-Guided Simulation Workflows across Heterogeneous Resources.” 2023 IEEE International Parallel and Distributed Processing Symposium Workshops (IPDPSW), May. https://doi.org/10.1109/ipdpsw59300.2023.00018.

Bez, Jean Luca, Houjun Tang, Scot Breitenfeld, Huihuo Zheng, Wei‐Keng Liao, Kaiyuan Hou, Zanhua Huang, and Suren Byna. 2024. “H5bench: A Unified Benchmark Suite for Evaluating HDF5 I/O Performance on Pre‐exascale Platforms.” Concurrency and Computation: Practice and Experience 36 (16). https://doi.org/10.1002/cpe.8046.

Chowdhury, Md Kamal Hossain, Houjun Tang, Jean Luca Bez, Purushotham V. Bangalore, and Suren Byna. 2023. “Efficient Asynchronous I/O with Request Merging.” 2023 IEEE International Parallel and Distributed Processing Symposium Workshops (IPDPSW), May. https://doi.org/10.1109/ipdpsw59300.2023.00107.

Rolchigo, Matt, John Coleman, Gerry L. Knapp, and Alex Plotkowski. 2024. “Grain Structure and Texture Selection Regimes in Metal Powder Bed Fusion.” Additive Manufacturing 81 (February): 104024. https://doi.org/10.1016/j.addma.2024.104024.

Finkelstein, Joshua, Christian F. A. Negre, and Jean-Luc Fattebert. 2023. “A Fast, Dense Chebyshev Solver for Electronic Structure on GPUs.” The Journal of Chemical Physics 159 (10). https://doi.org/10.1063/5.0164255.

Dhruv, Akash, and Anshu Dubey. 2023. “Managing Software Provenance to Enhance Reproducibility in Computational Research.” Computing in Science & Engineering 25 (3): 60–65. https://doi.org/10.1109/mcse.2023.3314288.

Valero-Lara, Pedro, Seyong Lee, Joel Denny, Keita Teranishi, Jeffrey Vetter, and Marc Gonzalez-Tallada. 2024. “SKokkos: Enabling Kokkos with Transparent Device Selection on Heterogeneous Systems Using OpenACC.” Proceedings of the International Conference on High Performance Computing in Asia-Pacific Region, January. https://doi.org/10.1145/3635035.3635043.

Valero-Lara, Pedro, and Jeffrey S. Vetter. 2023. “A MultiGPU Performance-Portable Solution for Array Programming Based on Kokkos.” Proceedings of the 9th ACM SIGPLAN International Workshop on Libraries, Languages and Compilers for Array Programming, June. https://doi.org/10.1145/3589246.3595369.

Mishler, Daniel, Jan Ciesko, Stephen Olivier, and George Bosilca. 2023. “Performance Insights into Device-Initiated RMA Using Kokkos Remote Spaces.” 2023 IEEE International Conference on Cluster Computing Workshops (CLUSTER Workshops), October. https://doi.org/10.1109/clusterworkshops61457.2023.00028.

Guidi, Giulia, Gabriel Raulet, Daniel Rokhsar, Leonid Oliker, Katherine Yelick, and Aydin Buluç. 2022. “Distributed-Memory Parallel Contig Generation for De Novo Long-Read Genome Assembly.” Proceedings of the 51st International Conference on Parallel Processing, August. https://doi.org/10.1145/3545008.3545050.

Satkauskas, Ignas, Jonathan Maack, Matthew Reynolds, Devon Sigler, Kinshuk Panda, and Wesley Jones. 2023. “Emergency Asset Positioning for Resilient Transmission Grid Operation.” 2023 IEEE Power & Energy Society General Meeting (PESGM), July. https://doi.org/10.1109/pesgm52003.2023.10252743.

Liu, Yang, Tianhuan Luo, Aman Rani, Hengrui Luo, and Xiaoye Sherry Li. 2023. “Detecting Resonance of Radio-Frequency Cavities Using Fast Direct Integral Equation Solvers and Augmented Bayesian Optimization.” IEEE Journal on Multiscale and Multiphysics Computational Techniques 8: 361–71. https://doi.org/10.1109/jmmct.2023.3311322.

Tomás, Andrés E., Enrique S. Quintana-Orti, and Hartwig Anzt. 2023. “Fast Truncated SVD of Sparse and Dense Matrices on Graphics Processors.” The International Journal of High Performance Computing Applications 37 (3–4): 380–93. https://doi.org/10.1177/10943420231179699.

Raj, Akhilesh, Swann Perarnau, and Aniruddha Gokhale. 2023. “A Reinforcement Learning Approach for Performance-Aware Reduction in Power Consumption of Data Center Compute Nodes.” 2023 IEEE International Conference on Cloud Engineering (IC2E), September. https://doi.org/10.1109/ic2e59103.2023.00022.

Claus, Lisa, Pieter Ghysels, Yang Liu, Thái Anh Nhan, Ramakrishnan Thirumalaisamy, Amneet Pal Singh Bhalla, and Sherry Li. 2023. “Sparse Approximate Multifrontal Factorization with Composite Compression Methods.” ACM Transactions on Mathematical Software 49 (3): 1–28. https://doi.org/10.1145/3611662.

Davis, Philip E., Jacob Merson, Pradeep Subedi, Lee Ricketson, Cameron W. Smith, Mark S. Shephard, and Manish Parashar. 2023. “Benesh: A Framework for Choreographic Coordination of In Situ Workflows.” 2023 IEEE 30th International Conference on High Performance Computing, Data, and Analytics (HiPC), December. https://doi.org/10.1109/hipc58850.2023.00047.

Ganguli, Arkaprabha, Robert Underwood, Julie Bessac, David Krasowska, Jon C. Calhoun, Sheng Di, and Franck Cappello. 2023. “A Lightweight, Effective Compressibility Estimation Method for Error-Bounded Lossy Compression.” 2023 IEEE International Conference on Cluster Computing (CLUSTER), October. https://doi.org/10.1109/cluster52292.2023.00028.

Wright, Eric, Johannes Doerfert, Shilei Tian, Barbara Chapman, and Sunita Chandrasekaran. 2023. “Implementing OpenMP’s SIMD Directive in LLVM’s GPU Runtime.” Proceedings of the 52nd International Conference on Parallel Processing, August. https://doi.org/10.1145/3605573.3605640.

Huang, Jiajun, Kaiming Ouyang, Yujia Zhai, Jinyang Liu, Min Si, Ken Raffenetti, Hui Zhou, et al. 2023. “PiP-MColl: Process-in-Process-Based Multi-Object MPI Collectives.” 2023 IEEE International Conference on Cluster Computing (CLUSTER), October. https://doi.org/10.1109/cluster52292.2023.00037.

Schuchart, Joseph, Sascha Hunold, and George Bosilca. 2023. “Synchronizing MPI Processes in Space and Time.” Proceedings of the 30th European MPI Users’ Group Meeting, September. https://doi.org/10.1145/3615318.3615325.

Mathai, Manish, Matthew Larsen, and Hank Childs. 2023. “A Distributed-Memory Parallel Approach for Volume Rendering with Shadows.” 2023 IEEE 13th Symposium on Large Data Analysis and Visualization (LDAV), October. https://doi.org/10.1109/ldav60332.2023.00010.

Draeger, Erik W., and Andrew Siegel. 2023. “Exascale Was Not Inevitable; Neither Is What Comes Next.” Computing in Science & Engineering 25 (3): 79–83. https://doi.org/10.1109/mcse.2023.3311375.

Malony, Allen D., and Sameer S. Shende. 2022. “Translating High-Performance Computing Tools From Research to Practice: Experiences With the TAU Performance System.” Computing in Science & Engineering 24 (5): 65–71. https://doi.org/10.1109/mcse.2023.3257420.

Connolly, Michael P., and Nicholas J. Higham. 2023. “Probabilistic Rounding Error Analysis of Householder QR Factorization.” SIAM Journal on Matrix Analysis and Applications 44 (3): 1146–63. https://doi.org/10.1137/22m1514817.

Chen, Jie, Robert G. Edwards, and Weizhen Mao. 2023. “Graph Contractions for Calculating Correlation Functions in Lattice QCD.” Proceedings of the Platform for Advanced Scientific Computing Conference, June. https://doi.org/10.1145/3592979.3593409.

Biswas, Ayan, Arindam Bhattacharya, Yi-Tang Chen, and Han-Wei Shen. 2023. “Sub-Linear Time Sampling Approach for Large-Scale Data Visualization Using Reinforcement Learning.” 2023 IEEE 13th Symposium on Large Data Analysis and Visualization (LDAV), October. https://doi.org/10.1109/ldav60332.2023.00008.

Barry, Daniel, Heike Jagode, Anthony Danalis, and Jack Dongarra. 2023. “Memory Traffic and Complete Application Profiling with PAPI Multi-Component Measurements.” 2023 IEEE International Parallel and Distributed Processing Symposium Workshops (IPDPSW), May. https://doi.org/10.1109/ipdpsw59300.2023.00070.

Munikoti, Sai, Deepesh Agarwal, Laya Das, Mahantesh Halappanavar, and Balasubramaniam Natarajan. 2023. “Challenges and Opportunities in Deep Reinforcement Learning With Graph Neural Networks: A Comprehensive Review of Algorithms and Applications.” IEEE Transactions on Neural Networks and Learning Systems, 1–21. https://doi.org/10.1109/tnnls.2023.3283523.

Thompson, Jeremy L., Jed Brown, and Yunhui He. 2023. “Local Fourier Analysis of P-Multigrid for High-Order Finite Element Operators.” SIAM Journal on Scientific Computing 45 (3): S351–70. https://doi.org/10.1137/21m1431199.

Sharma, Himanshu, Joshua D Suetterlein, Sumathi Lakshmiranganatha, Thomas Flynn, Draguna Vrabie, Christine Sweeney, and Vinay Ramakrishniah. 2023. “EXARL-PARS: Parallel Augmented Random Search Using Reinforcement Learning at Scale for Applications in Power Systems.” Companion Proceedings of the 14th ACM International Conference on Future Energy Systems, June. https://doi.org/10.1145/3599733.3600261.

Cao, Qinglei, Sameh Abdulah, Hatem Ltaief, Marc G. Genton, David Keyes, and George Bosilca. 2023. “Reducing Data Motion and Energy Consumption of Geospatial Modeling Applications Using Automated Precision Conversion.” 2023 IEEE International Conference on Cluster Computing (CLUSTER), October. https://doi.org/10.1109/cluster52292.2023.00035.

Berry, Jessica, Paul Romano, and Andrew Osborne. 2024. “Upsampling Monte Carlo Reactor Simulation Tallies in Depleted LWR Assemblies Fueled with LEU and HALEU Using a Convolutional Neural Network.” AIP Advances 14 (1). https://doi.org/10.1063/5.0169833.

Briggs, E. L., Wenchang Lu, and J. Bernholc. 2024. “Adaptive Finite Differencing in High Accuracy Electronic Structure Calculations.” Npj Computational Materials 10 (1). https://doi.org/10.1038/s41524-024-01203-y.

Gillis, Thomas, Ken Raffenetti, Hui Zhou, Yanfei Guo, and Rajeev Thakur. 2023. “Quantifying the Performance Benefits of Partitioned Communication in MPI.” Proceedings of the 52nd International Conference on Parallel Processing, August. https://doi.org/10.1145/3605573.3605599.

Torre, Luis de la, and Mahantesh Halappanavar. 2023. “Scaling Optimal Allocation of Cloud Resources Using Lagrange Relaxation.” Lecture Notes in Computer Science, 173–92. https://doi.org/10.1007/978-3-031-43943-8_9.

Bhowmik, Debsindhu, Pei Zhang, Zachary Fox, Stephan Irle, and John Gounley. 2024. “Enhancing Molecular Design Efficiency: Uniting Language Models and Generative Networks with Genetic Algorithms.” Patterns 5 (4): 100947. https://doi.org/10.1016/j.patter.2024.100947.

Gupta, Vishu, Youjia Li, Alec Peltekian, Muhammed Nur Talha Kilic, Wei-keng Liao, Alok Choudhary, and Ankit Agrawal. 2024. “Simultaneously Improving Accuracy and Computational Cost under Parametric Constraints in Materials Property Prediction Tasks.” Journal of Cheminformatics 16 (1). https://doi.org/10.1186/s13321-024-00811-6.

Bhavsar, S., R. Pitchumani, J. Maack, I. Satkauskas, M. Reynolds, and W. Jones. 2024. “Stochastic Economic Dispatch of Wind Power under Uncertainty Using Clustering-Based Extreme Scenarios.” Electric Power Systems Research 229 (April): 110158. https://doi.org/10.1016/j.epsr.2024.110158.

Nayak, Dibyajyoti, Anirudh Jonnalagadda, Uma Balakrishnan, Hemanth Kolla, and Konduri Aditya. 2024. “A Co-Kurtosis PCA Based Dimensionality Reduction with Nonlinear Reconstruction Using Neural Networks.” Combustion and Flame 259 (January): 113192. https://doi.org/10.1016/j.combustflame.2023.113192.

Blaschke, Johannes P., Aaron S. Brewster, Daniel W. Paley, Derek Mendez, Asmit Bhowmick, Nicholas K. Sauter, Wilko Kröger, Murali Shankar, Bjoern Enders, and Deborah Bard. 2024. “Real‐time XFEL Data Analysis at SLAC and NERSC: A Trial Run of Nascent Exascale Experimental Data Analysis.” Concurrency and Computation: Practice and Experience 36 (12). https://doi.org/10.1002/cpe.8019.

Gupta, Vishu, Kamal Choudhary, Brian DeCost, Francesca Tavazza, Carelyn Campbell, Wei-keng Liao, Alok Choudhary, and Ankit Agrawal. 2024. “Structure-Aware Graph Neural Network Based Deep Transfer Learning Framework for Enhanced Predictive Analytics on Diverse Materials Datasets.” Npj Computational Materials 10 (1). https://doi.org/10.1038/s41524-023-01185-3.

Xu, Peng, Samuel L. Leonard, William O’Brien, and Mark S. Gordon. 2023. “R–8 Dispersion Interaction: Derivation and Application to the Effective Fragment Potential Method.” The Journal of Physical Chemistry A 128 (1): 292–327. https://doi.org/10.1021/acs.jpca.3c05115.

Lee, Jungmin, Walter M. Hannah, and David C. Bader. 2023. “Representation of Atmosphere-Induced Heterogeneity in Land–Atmosphere Interactions in E3SM–MMFv2.” Geoscientific Model Development 16 (24): 7275–87. https://doi.org/10.5194/gmd-16-7275-2023.

Williams-Young, David B., Andrey Asadchev, Doru Thom Popovici, David Clark, Jonathan Waldrop, Theresa L. Windus, Edward F. Valeev, and Wibe A. de Jong. 2023. “Distributed Memory, GPU Accelerated Fock Construction for Hybrid, Gaussian Basis Density Functional Theory.” The Journal of Chemical Physics 158 (23). https://doi.org/10.1063/5.0151070.

Zvyagin, Maxim, Alexander Brace, Kyle Hippe, Yuntian Deng, Bin Zhang, Cindy Orozco Bohorquez, Austin Clyde, et al. 2023. “GenSLMs: Genome-Scale Language Models Reveal SARS-CoV-2 Evolutionary Dynamics.” The International Journal of High Performance Computing Applications 37 (6): 683–705. https://doi.org/10.1177/10943420231201154.

Lee, Jungmin M., Cheng Tao, Walter M. Hannah, Shaocheng Xie, and David C. Bader. 2023. “Assessment of Warm and Dry Bias over ARM SGP Site in E3SMv2 and E3SM-MMF.” Journal of the Atmospheric Sciences 80 (10): 2545–56. https://doi.org/10.1175/jas-d-23-0062.1.

Carson, Erin, Jörg Liesen, and Zdeněk Strakoš. 2024. “Towards Understanding CG and GMRES through Examples.” Linear Algebra and Its Applications 692 (July): 241–91. https://doi.org/10.1016/j.laa.2024.04.003.

Marshall, Andrew, Adam Generale, Surya R. Kalidindi, Bala Radhakrishnan, and Jim Belak. 2024. “A Gaussian Process Autoregressive Model Capturing Microstructure Evolution Paths in a Ni–Mo–Nb Alloy.” Journal of Materials Science 59 (12): 4863–81. https://doi.org/10.1007/s10853-024-09345-6.

Luo, Hengrui, Younghyun Cho, James W. Demmel, Xiaoye S. Li, and Yang Liu. 2024. “Hybrid Parameter Search and Dynamic Model Selection for Mixed-Variable Bayesian Optimization.” Journal of Computational and Graphical Statistics, March, 1–14. https://doi.org/10.1080/10618600.2024.2308216.

Anderson, Tyler A., Manolo C. Per, and C. J. Umrigar. 2024. “Reducing the Time-Step Errors in Diffusion Monte Carlo.” The Journal of Chemical Physics 160 (10). https://doi.org/10.1063/5.0190346.

Dahshan, Mai, Nicholas Polys, Leanna House, Chris North, Ryan M. Pollyea, Terece L. Turton, and David H. Rogers. 2024. “Human–Machine Partnerships at the Exascale: Exploring Simulation Ensembles through Image Databases.” Journal of Visualization, May. https://doi.org/10.1007/s12650-024-00999-7.

Świrydowicz, Kasia, Nicholson Koukpaizan, Tobias Ribizel, Fritz Göbel, Shrirang Abhyankar, Hartwig Anzt, and Slaven Peleš. 2024. “GPU-Resident Sparse Direct Linear Solvers for Alternating Current Optimal Power Flow Analysis.” International Journal of Electrical Power & Energy Systems 155 (January): 109517. https://doi.org/10.1016/j.ijepes.2023.109517.

Lupo Pasini, Massimiliano, and M. Paul Laiu. 2024. “Anderson Acceleration with Approximate Calculations: Applications to Scientific Computing.” Numerical Linear Algebra with Applications, May. https://doi.org/10.1002/nla.2562.

Mccoy, Hunter, and Prashant Pandey. 2024. “Gallatin: A General-Purpose GPU Memory Manager.” Proceedings of the 29th ACM SIGPLAN Annual Symposium on Principles and Practice of Parallel Programming, February. https://doi.org/10.1145/3627535.3638499.

Ricketson, L.F., and G. Chen. 2023. “A Pseudospectral Implicit Particle-in-Cell Method with Exact Energy and Charge Conservation.” Computer Physics Communications 291 (October): 108811. https://doi.org/10.1016/j.cpc.2023.108811.

Del Angel Cruz, Daniel, Jorge L. Galvez Vallejo, and Mark S. Gordon. 2023. “Analysis of the Bonding in Tetrahedrane and Phosphorus-Substituted Tetrahedranes.” Physical Chemistry Chemical Physics 25 (40): 27276–92. https://doi.org/10.1039/d3cp03619g.

Thomas, Stephen, Arielle Carr, Paul Mullowney, Katarzyna Świrydowicz, and Marcus Day. 2023. “Scaled ILU Smoothers for Navier–Stokes Pressure Projection.” International Journal for Numerical Methods in Fluids 96 (4): 537–60. https://doi.org/10.1002/fld.5254.

Gong, Qian, Jieyang Chen, Ben Whitney, Xin Liang, Viktor Reshniak, Tania Banerjee, Jaemoon Lee, et al. 2023. “MGARD: A Multigrid Framework for High-Performance, Error-Controlled Data Compression and Refactoring.” SoftwareX 24 (December): 101590. https://doi.org/10.1016/j.softx.2023.101590.

Garmon, Andrew, Xiang-Yang Liu, David Andersson, and Danny Perez. 2023. “Diffusion of Small Anti-Schottky Clusters in UO2.” Journal of Nuclear Materials 585 (November): 154630. https://doi.org/10.1016/j.jnucmat.2023.154630.

Alkan, Melisa, Haley K. Banovetz, Mark S. Gordon, and Levi M. Stanley. 2023. “Computational and Mechanistic Studies of Pd-Catalyzed Alkene Carboacylation via Ester C–O Bond Activation.” ACS Catalysis 13 (14): 9766–76. https://doi.org/10.1021/acscatal.3c01405.

Persaud, Daniel, Logan Ward, and Jason Hattrick-Simpers. 2024. “Reproducibility in Materials Informatics: Lessons from ‘A General-Purpose Machine Learning Framework for Predicting Properties of Inorganic Materials.’” Digital Discovery 3 (2): 281–86. https://doi.org/10.1039/d3dd00199g.

Zhao, Jisheng, Colleen Bertoni, Jeffrey Young, Kevin Harms, Vivek Sarkar, and Brice Videau. 2023. “HIPLZ: Enabling Performance Portability for Exascale Systems.” Concurrency and Computation: Practice and Experience 35 (25). https://doi.org/10.1002/cpe.7866.

Johnson, Matthew S., and William H. Green. 2024. “A Machine Learning Based Approach to Reaction Rate Estimation.” Reaction Chemistry & Engineering 9 (6): 1364–80. https://doi.org/10.1039/d3re00684k.

Lattanzi, Aaron M., William D. Fullmer, Andrew Myers, and Jordan Musser. 2024. “Toward Polydisperse Flows With mfix-exa.” Journal of Fluids Engineering 146 (4). https://doi.org/10.1115/1.4064533.

Dunham, Samuel J., Eirik Endeve, Anthony Mezzacappa, John M. Blondin, Jesse Buffaloe, and Kelly Holley-Bockelmann. 2024. “A Parametric Study of the SASI Comparing General Relativistic and Nonrelativistic Treatments*.” The Astrophysical Journal 964 (1): 38. https://doi.org/10.3847/1538-4357/ad206c.

Galvez Vallejo, Jorge L., Calum Snowdon, Ryan Stocks, Fazeleh Kazemian, Fiona Chuo Yan Yu, Christopher Seidl, Zoe Seeger, et al. 2023. “Toward an Extreme-Scale Electronic Structure System.” The Journal of Chemical Physics 159 (4). https://doi.org/10.1063/5.0156399.

Huang, Junfei, and David McCallen. 2024. “Applicability of 1D Site Response Analysis to Shallow Sedimentary Basins: A Critical Evaluation through Physics‐based 3D Ground Motion Simulations.” Earthquake Engineering & Structural Dynamics 53 (9): 2876–2907. https://doi.org/10.1002/eqe.4142.

Petra, Cosmin G., and Ignacio Aravena. 2023. “A Surrogate-Based Asynchronous Decomposition Technique for Realistic Security-Constrained Optimal Power Flow Problems.” Operations Research 71 (6): 2015–30. https://doi.org/10.1287/opre.2022.0229.

Carson, Erin, and Ieva Daužickaitė. 2024. “The Stability of Split-Preconditioned FGMRES in Four Precisions.” ETNA - Electronic Transactions on Numerical Analysis 60: 40–58. https://doi.org/10.1553/etna_vol60s40.

Nelson, Philip M., Zachary L. Glick, and C. David Sherrill. 2023. “Approximating Large-Basis Coupled-Cluster Theory Vibrational Frequencies Using Focal-Point Approximations.” The Journal of Chemical Physics 159 (9). https://doi.org/10.1063/5.0168608.

Merlo, Gabriele, Mattia Dicorato, Bryce Allen, Tilman Dannert, Kai Germaschewski, and Frank Jenko. 2023. “On the Effect of Negative Triangularity on Ion Temperature Gradient Turbulence in Tokamaks.” Physics of Plasmas 30 (10). https://doi.org/10.1063/5.0167292.

Blanchard, Andrew E., Debsindhu Bhowmik, Zachary Fox, John Gounley, Jens Glaser, Belinda S. Akpa, and Stephan Irle. 2023. “Adaptive Language Model Training for Molecular Design.” Journal of Cheminformatics 15 (1). https://doi.org/10.1186/s13321-023-00719-7.

Dubey, Anshu, Tal Ben-Nun, Bradford L. Chamberlain, Bronis R. de Supinski, and Damian Rouson. 2023. “Performance on HPC Platforms Is Possible Without C++.” Computing in Science & Engineering 25 (5): 48–52. https://doi.org/10.1109/mcse.2023.3329330.

Yokelson, Dewi, Oskar Lappi, Srinivasan Ramesh, Miikka S. Väisälä, Kevin Huck, Touko Puro, Boyana Norris, Maarit Korpi‐Lagg, Keijo Heljanko, and Allen D. Malony. 2024. “SOMA: Observability, Monitoring, and in Situ Analytics for Exascale Applications.” Concurrency and Computation: Practice and Experience, June. https://doi.org/10.1002/cpe.8141.

Yu, Jiankai, and Benoit Forget. 2024. “Release of Windowed Multipole Library for ENDF/B-VIII.0 in Support of OpenMC Criticality and Depletion Analysis.” Progress in Nuclear Energy 168 (March): 104996. https://doi.org/10.1016/j.pnucene.2023.104996.

John, Joseph, Josh Milthorpe, Thomas Herault, and George Bosilca. 2024. “Multi-GPU Work Sharing in a Task-Based Dataflow Programming Model.” Future Generation Computer Systems 156 (July): 313–24. https://doi.org/10.1016/j.future.2024.03.017.

Peterson, Adam J, Don Willcox, and Philipp Mösta. 2023. “Code Generation for AMReX with Applications to Numerical Relativity.” Classical and Quantum Gravity 40 (24): 245013. https://doi.org/10.1088/1361-6382/ad0b37.

Oktay, Eda, and Erin Carson. 2023. “Mixed Precision Rayleigh Quotient Iteration for Total Least Squares Problems.” Numerical Algorithms 96 (2): 777–98. https://doi.org/10.1007/s11075-023-01665-z.

Godoy, William F., Ritu Arora, Keith Beattie, David E. Bernholdt, Sarah E. Bratt, Daniel S. Katz, Ignacio Laguna, et al. 2022. “Giving Research Software Engineers a Larger Stage Through the Better Scientific Software Fellowship.” Computing in Science & Engineering 24 (5): 6–13. https://doi.org/10.1109/mcse.2023.3253847.

Godoy, William F., Pedro Valero-Lara, T. Elise Dettling, Christian Trefftz, Ian Jorquera, Thomas Sheehy, Ross G. Miller, Marc Gonzalez-Tallada, Jeffrey S. Vetter, and Valentin Churavy. 2023. “Evaluating Performance and Portability of High-Level Programming Models: Julia, Python/Numba, and Kokkos on Exascale Nodes.” 2023 IEEE International Parallel and Distributed Processing Symposium Workshops (IPDPSW), May. https://doi.org/10.1109/ipdpsw59300.2023.00068.

Godoy, William F., Pedro Valero-Lara, Caira Anderson, Katrina W. Lee, Ana Gainaru, Rafael Ferreira Da Silva, and Jeffrey S. Vetter. 2023. “Julia as a Unifying End-to-End Workflow Language on the Frontier Exascale System.” Proceedings of the SC ’23 Workshops of The International Conference on High Performance Computing, Network, Storage, and Analysis, November. https://doi.org/10.1145/3624062.3624278.

Kothe, Douglas, Stephen Lee, and Irene Qualters. 2019. “Exascale Computing in the United States.” Computing in Science & Engineering 21 (1): 17–29. https://doi.org/10.1109/mcse.2018.2875366.

Yadav, Rohan, Alex Aiken, and Fredrik Kjolstad. 2022. “SpDISTAL: Compiling Distributed Sparse Tensor Computations.” SC22: International Conference for High Performance Computing, Networking, Storage and Analysis, November. https://doi.org/10.1109/sc41404.2022.00064.

Aggarwal, Isha, Pratik Nayak, Aditya Kashi, and Hartwig Anzt. 2022. “Preconditioners for Batched Iterative Linear Solvers on GPUs.” Accelerating Science and Engineering Discoveries Through Integrated Research Infrastructure for Experiment, Big Data, Modeling and Simulation, 38–53. https://doi.org/10.1007/978-3-031-23606-8_3.

Tang, Li, and Scott Pakin. 2022. “Cross-Level Characterization of Program Execution.” 2022 30th International Symposium on Modeling, Analysis, and Simulation of Computer and Telecommunication Systems (MASCOTS), October. https://doi.org/10.1109/mascots56607.2022.00013.

Asadchev, Andrey, and Edward F. Valeev. 2023. “Memory-Efficient Recursive Evaluation of 3-Center Gaussian Integrals.” Journal of Chemical Theory and Computation 19 (6): 1698–1710. https://doi.org/10.1021/acs.jctc.2c00995.

Osborne, Andrew, Joffrey Dorville, and Paul Romano. 2023. “Upsampling Monte Carlo Neutron Transport Simulation Tallies Using a Convolutional Neural Network.” Energy and AI 13 (July): 100247. https://doi.org/10.1016/j.egyai.2023.100247.

Whyte, Travis, Andreas Stathopoulos, Eloy Romero, and Kostas Orginos. 2022. “Interpolation as a Means of Shift Selection for Multilevel Monte Carlo with Lattice Displacements.” Proceedings of The 39th International Symposium on Lattice Field Theory — PoS(LATTICE2022), November. https://doi.org/10.22323/1.430.0255.

Tan, Zujun, Yebin Chon, Michael Kruse, Johannes Doerfert, Ziyang Xu, Brian Homerding, Simone Campanoni, and David I. August. 2023. “SPLENDID: Supporting Parallel LLVM-IR Enhanced Natural Decompilation for Interactive Development.” Proceedings of the 28th ACM International Conference on Architectural Support for Programming Languages and Operating Systems, Volume 3, March. https://doi.org/10.1145/3582016.3582058.

Smith, Alexander I., Eric T. Johnson, Zhi Chen, Kiran Eiden, Donald E. Willcox, Brendan Boyd, Lyra Cao, Christopher J. DeGrendele, and Michael Zingale. 2023. “Pynucastro: A Python Library for Nuclear Astrophysics.” The Astrophysical Journal 947 (2): 65. https://doi.org/10.3847/1538-4357/acbaff.

Richard, Ryan M., Kristopher Keipert, Jonathan Waldrop, Murat Keçeli, David Williams-Young, Raymond Bair, Jeffery Boschen, et al. 2023. “PluginPlay: Enabling Exascale Scientific Software One Module at a Time.” The Journal of Chemical Physics 158 (18). https://doi.org/10.1063/5.0147903.

Liu, Xin, J D Emberson, Michael Buehlmann, Nicholas Frontiere, and Salman Habib. 2023. “Numerical Discreteness Errors in Multispecies Cosmological N-Body Simulations.” Monthly Notices of the Royal Astronomical Society 522 (3): 3631–47. https://doi.org/10.1093/mnras/stad1176.

Dawn, William C., and Scott Palmtag. 2023. “Solving the Neutron Transport Equation for Microreactor Modeling Using Unstructured Meshes and Exascale Computing Architectures.” Nuclear Science and Engineering 197 (12): 3138–59. https://doi.org/10.1080/00295639.2023.2189510.

Barik, Reet, Marco Minutoli, Mahantesh Halappanavar, and Ananth Kalyanaraman. 2022. “IMpart: A Partitioning-Based Parallel Approach to Accelerate Influence Maximization.” 2022 IEEE 29th International Conference on High Performance Computing, Data, and Analytics (HiPC), December. https://doi.org/10.1109/hipc56025.2022.00028.

Reed, K. A., A. M. Stansfield, W.‐C. Hsu, G. J. Kooperman, A. A. Akinsanola, W. M. Hannah, A. G. Pendergrass, and B. Medeiros. 2023. “Evaluating the Simulation of CONUS Precipitation by Storm Type in E3SM.” Geophysical Research Letters 50 (12). https://doi.org/10.1029/2022gl102409.

D’Ambra, Pasqua, Fabio Durastante, S M Ferdous, Salvatore Filippone, Mahantesh Halappanavar, and Alex Pothen. 2023. “AMG Preconditioners Based on Parallel Hybrid Coarsening and Multi-Objective Graph Matching.” 2023 31st Euromicro International Conference on Parallel, Distributed and Network-Based Processing (PDP), March. https://doi.org/10.1109/pdp59025.2023.00017.

Halver, Rene, Christoph Junghans, and Godehard Sutmann. 2023. “Using Heterogeneous GPU Nodes with a Cabana-Based Implementation of MPCD.” Parallel Computing 117 (September): 103033. https://doi.org/10.1016/j.parco.2023.103033.

Carson, Erin, and Noaman Khan. 2023. “Mixed Precision Iterative Refinement with Sparse Approximate Inverse Preconditioning.” SIAM Journal on Scientific Computing 45 (3): C131–53. https://doi.org/10.1137/22m1487709.

Thirumalaisamy, Ramakrishnan, Kaustubh Khedkar, Pieter Ghysels, and Amneet Pal Singh Bhalla. 2023. “An Effective Preconditioning Strategy for Volume Penalized Incompressible/Low Mach Multiphase Flow Solvers.” Journal of Computational Physics 490 (October): 112325. https://doi.org/10.1016/j.jcp.2023.112325.

Lenz, David, Oana Marin, Vijay Mahadevan, Raine Yeh, and Tom Peterka. 2023. “Fourier-Informed Knot Placement Schemes for B-Spline Approximation.” Mathematics and Computers in Simulation 213 (November): 374–93. https://doi.org/10.1016/j.matcom.2023.05.017.

Kammerdiener, Brandon, J. Zach McMichael, Michael R. Jantz, Kshitij A. Doshi, and Terry Jones. 2023. “Flexible and Effective Object Tiering for Heterogeneous Memory Systems.” Proceedings of the 2023 ACM SIGPLAN International Symposium on Memory Management, June. https://doi.org/10.1145/3591195.3595277.

Kale, Bharat, Austin Clyde, Maoyuan Sun, Arvind Ramanathan, Rick Stevens, and Michael E. Papka. 2023. “ChemoGraph: Interactive Visual Exploration of the Chemical Space.” Computer Graphics Forum 42 (3): 13–24. https://doi.org/10.1111/cgf.14807.

Cheung, Lawrence, Alan Hsieh, Myra Blaylock, Thomas Herges, Nathaniel deVelder, Kenneth Brown, Philip Sakievich, et al. 2023. “Investigations of Farm-to-Farm Interactions and Blockage Effects from AWAKEN Using Large-Scale Numerical Simulations.” Journal of Physics: Conference Series 2505 (1): 012023. https://doi.org/10.1088/1742-6596/2505/1/012023.

Zingale, Michael, Kiran Eiden, and Max Katz. 2023. “Comparing Early Evolution of Flames in X-Ray Bursts in Two and Three Dimensions.” The Astrophysical Journal 952 (2): 160. https://doi.org/10.3847/1538-4357/ace04e.

Shah, Milan, Xiaodong Yu, Sheng Di, Danylo Lykov, Yuri Alexeev, Michela Becchi, and Franck Cappello. 2023. “GPU-Accelerated Error-Bounded Compression Framework for Quantum Circuit Simulations.” 2023 IEEE International Parallel and Distributed Processing Symposium (IPDPS), May. https://doi.org/10.1109/ipdps54959.2023.00081.

Kurt, Süreyya Emre, Jinghua Yan, Aravind Sukumaran-Rajam, Prashant Pandey, and P. Sadayappan. 2023. “Communication Optimization for Distributed Execution of Graph Neural Networks.” 2023 IEEE International Parallel and Distributed Processing Symposium (IPDPS), May. https://doi.org/10.1109/ipdps54959.2023.00058.

Cho, Younghyun, James W. Demmel, Jacob King, Xiaoye S. Li, Yang Liu, and Hengrui Luo. 2023. “Harnessing the Crowd for Autotuning High-Performance Computing Applications.” 2023 IEEE International Parallel and Distributed Processing Symposium (IPDPS), May. https://doi.org/10.1109/ipdps54959.2023.00069.

Brim, Michael J., Adam T. Moody, Seung-Hwan Lim, Ross Miller, Swen Boehm, Cameron Stanavige, Kathryn M. Mohror, and Sarp Oral. 2023. “UnifyFS: A User-Level Shared File System for Unified Access to Distributed Local Storage.” 2023 IEEE International Parallel and Distributed Processing Symposium (IPDPS), May. https://doi.org/10.1109/ipdps54959.2023.00037.

Aliaga, José I., Hartwig Anzt, Enrique S. Quintana‐Ortí, and Andrés E. Tomás. 2023. “Sparse Matrix‐vector and Matrix‐multivector Products for the Truncated SVD on Graphics Processors.” Concurrency and Computation: Practice and Experience 35 (28). https://doi.org/10.1002/cpe.7871.

Randall, Thomas, Jaehoon Koo, Brice Videau, Michael Kruse, Xingfu Wu, Paul Hovland, Mary Hall, Rong Ge, and Prasanna Balaprakash. 2023. “Transfer-Learning-Based Autotuning Using Gaussian Copula.” Proceedings of the 37th International Conference on Supercomputing, June. https://doi.org/10.1145/3577193.3593712.

Nayak, Pratik, and Hartwig Anzt. 2023. “Utilizing Batched Solver Ideas for Efficient Solution of Non-Batched Linear Systems.” 2023 IEEE International Parallel and Distributed Processing Symposium Workshops (IPDPSW), May. https://doi.org/10.1109/ipdpsw59300.2023.00113.

Zhang, Boyuan, Jiannan Tian, Sheng Di, Xiaodong Yu, Yunhe Feng, Xin Liang, Dingwen Tao, and Franck Cappello. 2023. “FZ-GPU: A Fast and High-Ratio Lossy Compressor for Scientific Computing Applications on GPUs.” Proceedings of the 32nd International Symposium on High-Performance Parallel and Distributed Computing, August. https://doi.org/10.1145/3588195.3592994.

Tsai, Yu-Hsiang Mike, Natalie Beams, and Hartwig Anzt. 2023. “Three-Precision Algebraic Multigrid on GPUs.” Future Generation Computer Systems 149 (December): 280–93. https://doi.org/10.1016/j.future.2023.07.024.

Tang, Li, and Scott Pakin. 2023. “CLC: A Cross-Level Program Characterization Method.” Performance Evaluation 161 (September): 102354. https://doi.org/10.1016/j.peva.2023.102354.

Neff, Reece, Marco Minutoli, Antonino Tumeo, and Michela Becchi. 2023. “High-Level Synthesis of Irregular Applications.” Proceedings of the 20th ACM International Conference on Computing Frontiers, May. https://doi.org/10.1145/3587135.3592196.

Huang, Jiajun, Kaiming Ouyang, Yujia Zhai, Jinyang Liu, Min Si, Ken Raffenetti, Hui Zhou, et al. 2023. “Accelerating MPI Collectives with Process-in-Process-Based Multi-Object Techniques.” Proceedings of the 32nd International Symposium on High-Performance Parallel and Distributed Computing, August. https://doi.org/10.1145/3588195.3595955.

Dong, Bin, Jean Luca Bez, and Suren Byna. 2023. “AIIO: Using Artificial Intelligence for Job-Level and Automatic I/O Performance Bottleneck Diagnosis.” Proceedings of the 32nd International Symposium on High-Performance Parallel and Distributed Computing, August. https://doi.org/10.1145/3588195.3592986.

Bolstad, Mark, Kenneth Moreland, David Pugmire, David Rogers, Li-Ta Lo, Berk Geveci, Hank Childs, and Silvio Rizzi. 2023. “VTK-m: Visualization for the Exascale Era and Beyond.” ACM SIGGRAPH 2023 Talks, August. https://doi.org/10.1145/3587421.3595466.

Sattar, Naw Safrin, Aydin Buluc, Khaled Z. Ibrahim, and Shaikh Arifuzzaman. 2023. “Exploring Temporal Community Evolution: Algorithmic Approaches and Parallel Optimization for Dynamic Community Detection.” Applied Network Science 8 (1). https://doi.org/10.1007/s41109-023-00592-1.

Whyte, Travis, Andreas Stathopoulos, Eloy Romero, and Kostas Orginos. 2024. “Optimizing Shift Selection in Multilevel Monte Carlo for Disconnected Diagrams in Lattice QCD.” Computer Physics Communications 294 (January): 108928. https://doi.org/10.1016/j.cpc.2023.108928.

Underwood, Robert, and Bogdan Nicolae. 2023. “MPIGDB: A Flexible Debugging Infrastructure for MPI Programs.” Proceedings of the 13th Workshop on AI and Scientific Computing at Scale Using Flexible Computing, August. https://doi.org/10.1145/3589013.3596675.

Rohskopf, A., J. Goff, D. Sema, K. Gordiz, N. C. Nguyen, A. Henry, A. P. Thompson, and M. A. Wood. 2023. “Exploring Model Complexity in Machine Learned Potentials for Simulated Properties.” Journal of Materials Research 38 (24): 5136–50. https://doi.org/10.1557/s43578-023-01152-0.

Ferran Pousa, A., S. Jalas, M. Kirchen, A. Martinez de la Ossa, M. Thévenet, S. Hudson, J. Larson, A. Huebl, J.-L. Vay, and R. Lehe. 2023. “Bayesian Optimization of Laser-Plasma Accelerators Assisted by Reduced Physical Models.” Physical Review Accelerators and Beams 26 (8). https://doi.org/10.1103/physrevaccelbeams.26.084601.

Camargo, Antonio Pedro, Simon Roux, Frederik Schulz, Michal Babinski, Yan Xu, Bin Hu, Patrick S. G. Chain, Stephen Nayfach, and Nikos C. Kyrpides. 2023. “Identification of Mobile Genetic Elements with GeNomad.” Nature Biotechnology, September. https://doi.org/10.1038/s41587-023-01953-y.

Tian, Shilei, Barbara Chapman, and Johannes Doerfert. 2023. “Exploring the Limits of Generic Code Execution on GPUs via Direct (OpenMP) Offload.” Lecture Notes in Computer Science, 179–92. https://doi.org/10.1007/978-3-031-40744-4_12.

Mishra, Alok, Abid M. Malik, Meifeng Lin, and Barbara Chapman. 2023. “OpenMP Advisor: A Compiler Tool for Heterogeneous Architectures.” Lecture Notes in Computer Science, 34–48. https://doi.org/10.1007/978-3-031-40744-4_3.

Miah, Mamun, David McCallen, Arben Pitarka, and Floriana Petrone. 2023. “Simulation‐based Characterization of the Variability of Earthquake Risk to Buildings in the Near‐field.” Earthquake Engineering & Structural Dynamics 53 (1): 237–60. https://doi.org/10.1002/eqe.4007.

Kenawy, Maha, David McCallen, and Arben Pitarka. 2023. “Characteristics and Selection of Near-Fault Simulated Earthquake Ground Motions for Nonlinear Analysis of Buildings.” Earthquake Spectra 39 (4): 2281–2322. https://doi.org/10.1177/87552930231182164.

Gayatri, Rahulkumar, Stephen L. Olivier, Christian R. Trott, Johannes Doerfert, Jan Ciesko, and Damien Lebrun-Grandie. 2023. “The Kokkos OpenMPTarget Backend: Implementation and Lessons Learned.” Lecture Notes in Computer Science, 99–113. https://doi.org/10.1007/978-3-031-40744-4_7.

Daoudi, Idriss, Thierry Gautier, Samuel Thibault, and Swann Perarnau. 2023. “Improving Simulations of Task-Based Applications on Complex NUMA Architectures.” Lecture Notes in Computer Science, 195–209. https://doi.org/10.1007/978-3-031-40744-4_13.

Alkan, Melisa, Buu Q. Pham, Jeff R. Hammond, and Mark S. Gordon. 2023. “Enabling Fortran Standard Parallelism in GAMESS for Accelerated Quantum Chemistry Calculations.” Journal of Chemical Theory and Computation 19 (13): 3798–3805. https://doi.org/10.1021/acs.jctc.3c00380.

Pham, Buu Q., Laura Carrington, Ananta Tiwari, Sarom S. Leang, Melisa Alkan, Colleen Bertoni, Dipayan Datta, Tosaporn Sattasathuchana, Peng Xu, and Mark S. Gordon. 2023. “Porting Fragmentation Methods to GPUs Using an OpenMP API: Offloading the Resolution-of-the-Identity Second-Order Møller–Plesset Perturbation Method.” The Journal of Chemical Physics 158 (16). https://doi.org/10.1063/5.0143424.

Anzt, Hartwig, Terry Cojean, Goran Flegar, Fritz Göbel, Thomas Grützmacher, Pratik Nayak, Tobias Ribizel, Yuhsiang Mike Tsai, and Enrique S. Quintana-Ortí. 2022. “Ginkgo  : A Modern Linear Operator Algebra Framework for High Performance Computing.” ACM Transactions on Mathematical Software 48 (1): 1–33. https://doi.org/10.1145/3480935.

Tsai, Yu‐Hsiang M., Terry Cojean, and Hartwig Anzt. 2022. “Providing Performance Portable Numerics for Intel GPUs.” Concurrency and Computation: Practice and Experience, October. https://doi.org/10.1002/cpe.7400.

Georgiou, Vasileios, Christos Boutsikas, Petros Drineas, and Hartwig Anzt. 2023. “A Mixed Precision Randomized Preconditioner for the LSQR Solver on GPUs.” High Performance Computing, 164–81. https://doi.org/10.1007/978-3-031-32041-5_9.

Kashi, Aditya, Pratik Nayak, Dhruva Kulkarni, Aaron Scheinberg, Paul Lin, and Hartwig Anzt. 2023. “Integrating Batched Sparse Iterative Solvers for the Collision Operator in Fusion Plasma Simulations on GPUs.” Journal of Parallel and Distributed Computing 178 (August): 69–81. https://doi.org/10.1016/j.jpdc.2023.03.012.

Gates, Mark, Asim YarKhan, Dalal Sukkari, Kadir Akbudak, Sebastien Cayrols, Daniel Bielich, Ahmad Abdelfattah, Mohammed Al Farhan, and Jack Dongarra. 2022. “Portable and Efficient Dense Linear Algebra in the Beginning of the Exascale Era.” 2022 IEEE/ACM International Workshop on Performance, Portability and Productivity in HPC (P3HPC), November. https://doi.org/10.1109/p3hpc56579.2022.00009.

Lindquist, Neil, Piotr Luszczek, and Jack Dongarra. 2023. “Using Additive Modifications in LU Factorization Instead of Pivoting.” Proceedings of the 37th International Conference on Supercomputing, June. https://doi.org/10.1145/3577193.3593731.

Tsai, Yaohung M., Piotr Luszczek, and Jack Dongarra. 2022. “Mixed-Precision Algorithm for Finding Selected Eigenvalues and Eigenvectors of Symmetric and Hermitian Matrices1.” 2022 IEEE/ACM Workshop on Latest Advances in Scalable Algorithms for Large-Scale Heterogeneous Systems (ScalAH), November. https://doi.org/10.1109/scalah56622.2022.00011.

Lindquist, Neil, Mark Gates, Piotr Luszczek, and Jack Dongarra. 2022. “Threshold Pivoting for Dense LU Factorization.” 2022 IEEE/ACM Workshop on Latest Advances in Scalable Algorithms for Large-Scale Heterogeneous Systems (ScalAH), November. https://doi.org/10.1109/scalah56622.2022.00010.

Lindquist, Neil, Piotr Luszczek, and Jack Dongarra. 2020. “Replacing Pivoting in Distributed Gaussian Elimination with Randomized Techniques.” 2020 IEEE/ACM 11th Workshop on Latest Advances in Scalable Algorithms for Large-Scale Systems (ScalA), November. https://doi.org/10.1109/scala51936.2020.00010.

Fortenberry, Anna, and Stanimire Tomov. 2022. “Extending MAGMA Portability with OneAPI.” 2022 Workshop on Accelerator Programming Using Directives (WACCPD), November. https://doi.org/10.1109/waccpd56842.2022.00008.

Cayrols, Sebastien, Jiali Li, George Bosilca, Stanimire Tomov, Alan Ayala, and Jack Dongarra. 2022. “Lossy All-to-All Exchange for Accelerating Parallel 3-D FFTs on Hybrid Architectures with GPUs.” 2022 IEEE International Conference on Cluster Computing (CLUSTER), September. https://doi.org/10.1109/cluster51413.2022.00029.

Sharp, Daniel, Miroslav Stoyanov, Stanimire Tomov, and Jack Dongarra. 2021. “A More Portable HeFFTe: Implementing a Fallback Algorithm for Scalable Fourier Transforms.” 2021 IEEE High Performance Extreme Computing Conference (HPEC), September. https://doi.org/10.1109/hpec49654.2021.9622811.

Hoang, Duong, Harsh Bhatia, Peter Lindstrom, and Valerio Pascucci. 2023. “Progressive Tree-Based Compression of Large-Scale Particle Data.” IEEE Transactions on Visualization and Computer Graphics, 1–18. https://doi.org/10.1109/tvcg.2023.3260628.

Moreland, Kenneth, Andrew C. Bauer, Berk Geveci, Patrick O’Leary, and Brad Whitlock. 2022. “Leveraging Production Visualization Tools In Situ.” In Situ Visualization for Computational Science, 205–31. https://doi.org/10.1007/978-3-030-81627-8_10.

Wang, Daoce, Jesus Pulido, Pascal Grosset, Sian Jin, Jiannan Tian, James Ahrens, and Dingwen Tao. 2022. “TAC.” Proceedings of the 31st International Symposium on High-Performance Parallel and Distributed Computing, June. https://doi.org/10.1145/3502181.3531458.

Haseeb, Muhammad, Nan Ding, Jack Deslippe, and Muaaz Awan. 2021. “Evaluating Performance and Portability of a Core Bioinformatics Kernel on Multiple Vendor GPUs.” 2021 International Workshop on Performance, Portability and Productivity in HPC (P3HPC), November. https://doi.org/10.1109/p3hpc54578.2021.00010.

McCoy, Hunter, Steven Hofmey, Katherine Yelick, and Prashant Pandey. 2023. “Singleton Sieving: Overcoming the Memory/Speed Trade-Off in Exascale κ-Mer Analysis.” SIAM Conference on Applied and Computational Discrete Algorithms (ACDA23), January, 213–24. https://doi.org/10.1137/1.9781611977714.19.

Ellis, Marquita, Evangelos Georganas, Rob Egan, Steven Hofmeyr, Aydın Buluç, Brandon Cook, Leonid Oliker, and Katherine Yelick. 2017. “Performance Characterization of De Novo Genome Assembly on Leading Parallel Systems.” Euro-Par 2017: Parallel Processing, 79–91. https://doi.org/10.1007/978-3-319-64203-1_6.

Moses, Melanie E., Steven Hofmeyr, Judy L. Cannon, Akil Andrews, Rebekah Gridley, Monica Hinga, Kirtus Leyba, et al. 2021. “Spatially Distributed Infection Increases Viral Load in a Computational Model of SARS-CoV-2 Lung Infection.” Edited by Amber M Smith. PLOS Computational Biology 17 (12): e1009735. https://doi.org/10.1371/journal.pcbi.1009735.

Riley, Robert, Robert M. Bowers, Antonio Pedro Camargo, Ashley Campbell, Rob Egan, Emiley A. Eloe-Fadrosh, Brian Foster, et al. 2023. “Terabase-Scale Coassembly of a Tropical Soil Microbiome.” Edited by Erik F. Y. Hom. Microbiology Spectrum 11 (4). https://doi.org/10.1128/spectrum.00200-23.

Li, Xiaoye S., Paul Lin, Yang Liu, and Piyush Sao. 2023. “Newly Released Capabilities in the Distributed-Memory SuperLU Sparse Direct Solver.” ACM Transactions on Mathematical Software 49 (1): 1–20. https://doi.org/10.1145/3577197.

Rebrova, Elizaveta, Gustavo Chavez, Yang Liu, Pieter Ghysels, and Xiaoye Sherry Li. 2018. “A Study of Clustering Techniques and Hierarchical Matrix Formats for Kernel Ridge Regression.” 2018 IEEE International Parallel and Distributed Processing Symposium Workshops (IPDPSW), May. https://doi.org/10.1109/ipdpsw.2018.00140.

Barclay, Paul L., and Duan Z. Zhang. 2021. “Coalescence and Splashing Threshold for Head-on Collisions of Liquid Metal Nanodroplets.” Physics of Fluids 33 (6). https://doi.org/10.1063/5.0052819.

Zhang, Duan Z. 2021. “Stress from Long-Range Interactions in Particulate Systems.” Multiscale Modeling & Simulation 19 (2): 1066–82. https://doi.org/10.1137/20m1365065.

Rolchigo, Matthew, Alex Plotkowski, and James Belak. 2021. “Sensitivity of Cellular Automata Grain Structure Predictions for High Solidification Rates.” Computational Materials Science 196 (August): 110498. https://doi.org/10.1016/j.commatsci.2021.110498.

Barclay, Paul L., and Duan Z. Zhang. 2021. “Periodic Boundary Conditions for Arbitrary Deformations in Molecular Dynamics Simulations.” Journal of Computational Physics 435 (June): 110238. https://doi.org/10.1016/j.jcp.2021.110238.

Zhang, Duan Z. 2021. “Ensemble Average and Nearest Particle Statistics in Disperse Multiphase Flows.” Journal of Fluid Mechanics 910 (January). https://doi.org/10.1017/jfm.2020.974.

Wang, Min, and Duan Z. Zhang. 2021. “Deformation Accommodating Periodic Computational Domain for a Uniform Velocity Gradient.” Computer Methods in Applied Mechanics and Engineering 374 (February): 113607. https://doi.org/10.1016/j.cma.2020.113607.

Wang, Min, Yunchao Yang, Duan Z. Zhang, and S. Balachandar. 2021. “Numerical Calculation of the Particle–Fluid–Particle Stress in Random Arrays of Fixed Particles.” Physical Review Fluids 6 (10). https://doi.org/10.1103/physrevfluids.6.104306.

Malviya-Thakur, Addi, Reed Milewicz, Samuel Grayson, Philip Fackler, James Belak, and John A Turner. 2022. “Real-World Experiences Adopting Workflows at Exascale on the ExaAM Project.” 2022 IEEE 18th International Conference on E-Science (e-Science), October. https://doi.org/10.1109/escience55777.2022.00084.

Qiu, Yuxing, Samuel Temple Reeve, Minchen Li, Yin Yang, Stuart Ryan Slattery, and Chenfanfu Jiang. 2023. “A Sparse Distributed Gigascale Resolution Material Point Method.” ACM Transactions on Graphics 42 (2): 1–21. https://doi.org/10.1145/3570160.

Knapp, G.L., J. Coleman, M. Rolchigo, M. Stoyanov, and A. Plotkowski. 2023. “Calibrating Uncertain Parameters in Melt Pool Simulations of Additive Manufacturing.” Computational Materials Science 218 (February): 111904. https://doi.org/10.1016/j.commatsci.2022.111904.

Sabau, Adrian S., Lang Yuan, Jean-Luc Fattebert, and John A. Turner. 2023. “An OpenMP GPU-Offload Implementation of a Non-Equilibrium Solidification Cellular Automata Model for Additive Manufacturing.” Computer Physics Communications 284 (March): 108605. https://doi.org/10.1016/j.cpc.2022.108605.

Peng, Ivy, Roger Pearce, and Maya Gokhale. 2020. “On the Memory Underutilization: Exploring Disaggregated Memory on HPC Systems.” 2020 IEEE 32nd International Symposium on Computer Architecture and High Performance Computing (SBAC-PAD), September. https://doi.org/10.1109/sbac-pad49847.2020.00034.

Hawila, Ismail, Sophie Cerf, Raphael Bleuse, Swann Perarnau, and Eric Rutten. 2022. “Adaptive Power Control for Sober High-Performance Computing.” 2022 IEEE Conference on Control Technology and Applications (CCTA), August. https://doi.org/10.1109/ccta49430.2022.9966115.

Dominski, J., J. Cheng, G. Merlo, V. Carey, R. Hager, L. Ricketson, J. Choi, et al. 2021. “Spatial Coupling of Gyrokinetic Simulations, a Generalized Scheme Based on First-Principles.” Physics of Plasmas 28 (2): 022301. https://doi.org/10.1063/5.0027160.

Gu, Junmin, Greg Eisenhauer, Scott Klasky, Norbert Podhorszki, Ruonan Wang, and Kesheng Wu. 2022. “Exploring Large All-Flash Storage System with Scientific Simulation.” 34th International Conference on Scientific and Statistical Database Management, July. https://doi.org/10.1145/3538712.3538734.

Suchyta, Eric, Jong Youl Choi, Seung-Hoe Ku, David Pugmire, Ana Gainaru, Kevin Huck, Ralph Kube, et al. 2022. “Hybrid Analysis of Fusion Data for Online Understanding of Complex Science on Extreme Scale Computers.” 2022 IEEE International Conference on Cluster Computing (CLUSTER), September. https://doi.org/10.1109/cluster51413.2022.00035.

Underwood, Robert, Julie Bessac, David Krasowska, Jon C Calhoun, Sheng Di, and Franck Cappello. 2023. “Black-Box Statistical Prediction of Lossy Compression Ratios for Scientific Data.” The International Journal of High Performance Computing Applications 37 (3–4): 412–33. https://doi.org/10.1177/10943420231179417.

Liu, Jinyang, Sheng Di, Kai Zhao, Xin Liang, Zizhong Chen, and Franck Cappello. 2023. “FAZ: A Flexible Auto-Tuned Modular Error-Bounded Compression Framework for Scientific Data.” Proceedings of the 37th International Conference on Supercomputing, June. https://doi.org/10.1145/3577193.3593721.

Zhang, Boyuan, Jiannan Tian, Sheng Di, Xiaodong Yu, Martin Swany, Dingwen Tao, and Franck Cappello. 2023. “GPULZ: Optimizing LZSS Lossless Compression for Multi-Byte Data on Modern GPUs.” Proceedings of the 37th International Conference on Supercomputing, June. https://doi.org/10.1145/3577193.3593706.

Shah, Milan, Xiaodong Yu, Sheng Di, Michela Becchi, and Franck Cappello. 2023. “Lightweight Huffman Coding for Efficient GPU Compression.” Proceedings of the 37th International Conference on Supercomputing, June. https://doi.org/10.1145/3577193.3593736.

Liang, Xin, Kai Zhao, Sheng Di, Sihuan Li, Robert Underwood, Ali M. Gok, Jiannan Tian, et al. 2023. “SZ3: A Modular Framework for Composing Prediction-Based Error-Bounded Lossy Compressors.” IEEE Transactions on Big Data 9 (2): 485–98. https://doi.org/10.1109/tbdata.2022.3201176.

Jiao, Pu, Sheng Di, Hanqi Guo, Kai Zhao, Jiannan Tian, Dingwen Tao, Xin Liang, and Franck Cappello. 2022. “Toward Quantity-of-Interest Preserving Lossy Compression for Scientific Data.” Proceedings of the VLDB Endowment 16 (4): 697–710. https://doi.org/10.14778/3574245.3574255.

Dube, Griffin, Jiannan Tian, Sheng Di, Dingwen Tao, Jon C. Calhoun, and Franck Cappello. 2022. “Efficient Error-Bounded Lossy Compression for CPU Architectures.” 2022 30th International Symposium on Modeling, Analysis, and Simulation of Computer and Telecommunication Systems (MASCOTS), October. https://doi.org/10.1109/mascots56607.2022.00020.

Underwood, Robert, Julie Bessac, Sheng Di, and Franck Cappello. 2022. “Understanding the Effects of Modern Compressors on the Community Earth Science Model.” 2022 IEEE/ACM 8th International Workshop on Data Analysis and Reduction for Big Scientific Data (DRBSD), November. https://doi.org/10.1109/drbsd56682.2022.00006.

Jin, Sian, Sheng Di, Jiannan Tian, Suren Byna, Dingwen Tao, and Franck Cappello. 2022. “Improving Prediction-Based Lossy Compression Dramatically via Ratio-Quality Modeling.” 2022 IEEE 38th International Conference on Data Engineering (ICDE), May. https://doi.org/10.1109/icde53745.2022.00232.

Su, Zhaoyuan, Sheng Di, Ali Murat Gok, Yue Cheng, and Franck Cappello. 2022. “Understanding Impact of Lossy Compression on Derivative-Related Metrics in Scientific Datasets.” 2022 IEEE/ACM 8th International Workshop on Data Analysis and Reduction for Big Scientific Data (DRBSD), November. https://doi.org/10.1109/drbsd56682.2022.00011.

Zhao, Kai, Sheng Di, Danny Perez, Xin Liang, Zizhong Chen, and Franck Cappello. 2022. “MDZ: An Efficient Error-Bounded Lossy Compressor for Molecular Dynamics.” 2022 IEEE 38th International Conference on Data Engineering (ICDE), May. https://doi.org/10.1109/icde53745.2022.00007.

Liu, Jinyang, Sheng Di, Kai Zhao, Xin Liang, Zizhong Chen, and Franck Cappello. 2022. “Dynamic Quality Metric Oriented Error Bounded Lossy Compression for Scientific Datasets.” SC22: International Conference for High Performance Computing, Networking, Storage and Analysis, November. https://doi.org/10.1109/sc41404.2022.00067.

Liu, Yuanjian, Sheng Di, Kai Zhao, Sian Jin, Cheng Wang, Kyle Chard, Dingwen Tao, Ian Foster, and Franck Cappello. 2022. “Optimizing Error-Bounded Lossy Compression for Scientific Data With Diverse Constraints.” IEEE Transactions on Parallel and Distributed Systems 33 (12): 4440–57. https://doi.org/10.1109/tpds.2022.3194695.

Reza, Tasmia, Jon Calhoun, Kristopher Keipert, Sheng Di, and Franck Cappello. 2019. “Analyzing the Performance and Accuracy of Lossy Checkpointing on Sub-Iteration of NWChem.” 2019 IEEE/ACM 5th International Workshop on Data Analysis and Reduction for Big Scientific Data (DRBSD-5), November. https://doi.org/10.1109/drbsd-549595.2019.00009.

Zou, Xiangyu, Tao Lu, Sheng Di, Dingwen Tao, Wen Xia, Xuan Wang, Weizhe Zhang, and Qing Liao. 2019. “Accelerating Lossy Compression on HPC Datasets via Partitioning Computation for Parallel Processing.” 2019 IEEE 21st International Conference on High Performance Computing and Communications; IEEE 17th International Conference on Smart City; IEEE 5th International Conference on Data Science and Systems (HPCC/SmartCity/DSS), August. https://doi.org/10.1109/hpcc/smartcity/dss.2019.00246.

Morrow, Zachary, and Miroslav Stoyanov. 2020. “A Method for Dimensionally Adaptive Sparse Trigonometric Interpolation of Periodic Functions.” SIAM Journal on Scientific Computing 42 (4): A2436–60. https://doi.org/10.1137/19m1283483.

Prokopenko, Andrey, Piyush Sao, and Damien Lebrun-Grandie. 2022. “A Single-Tree Algorithm to Compute the Euclidean Minimum Spanning Tree on GPUs.” Proceedings of the 51st International Conference on Parallel Processing, August. https://doi.org/10.1145/3545008.3546185.

Boman, Erik G., Andrew J. Higgins, and Daniel B. Szyld. 2022. “Optimal Size of the Block in Block GMRES on GPUs: Computational Model and Experiments.” Numerical Algorithms 92 (1): 119–47. https://doi.org/10.1007/s11075-022-01439-z.

Kelley, Brian, and Sivasankaran Rajamanickam. 2022. “Parallel, Portable Algorithms for Distance-2 Maximal Independent Set and Graph Coarsening.” 2022 IEEE International Parallel and Distributed Processing Symposium (IPDPS), May. https://doi.org/10.1109/ipdps53621.2022.00035.

Liegeois, Kim, Sivasankaran Rajamanickam, and Luc Berger-Vergiat. 2023. “Performance Portable Batched Sparse Linear Solvers.” IEEE Transactions on Parallel and Distributed Systems 34 (5): 1524–35. https://doi.org/10.1109/tpds.2023.3249110.

Liu, Yang, Wissam M. Sid-Lakhdar, Osni Marques, Xinran Zhu, Chang Meng, James W. Demmel, and Xiaoye S. Li. 2021. “GPTune.” Proceedings of the 26th ACM SIGPLAN Symposium on Principles and Practice of Parallel Programming, February. https://doi.org/10.1145/3437801.3441621.

Yamazaki, Ichitaro, Christian Glusa, Jennifer Loe, Piotr Luszczek, Sivasankaran Rajamanickam, and Jack Dongarra. 2022. “High-Performance GMRES Multi-Precision Benchmark: Design, Performance, and Challenges.” 2022 IEEE/ACM International Workshop on Performance Modeling, Benchmarking and Simulation of High Performance Computer Systems (PMBS), November. https://doi.org/10.1109/pmbs56514.2022.00015.

Balos, Cody J., Piotr Luszczek, Sarah Osborn, James Willenbring, and Ulrike M. Yang. 2022. “Challenges of and Opportunities for a Large Diverse Software Team.” Computing in Science & Engineering 24 (3): 16–24. https://doi.org/10.1109/mcse.2022.3172873.

Kashi, Aditya, Pratik Nayak, Dhruva Kulkarni, Aaron Scheinberg, Paul Lin, and Hartwig Anzt. 2022. “Batched Sparse Iterative Solvers on GPU for the Collision Operator for Fusion Plasma Simulations.” 2022 IEEE International Parallel and Distributed Processing Symposium (IPDPS), May. https://doi.org/10.1109/ipdps53621.2022.00024.

Zhu, Xinran, Yang Liu, Pieter Ghysels, David Bindel, and Xiaoye S. Li. 2022. “GPTuneBand: Multi-Task and Multi-Fidelity Autotuning for Large-Scale High Performance Computing Applications.” Proceedings of the 2022 SIAM Conference on Parallel Processing for Scientific Computing (PP), January, 1–13. https://doi.org/10.1137/1.9781611977141.1.

Aliaga, José I, Hartwig Anzt, Thomas Grützmacher, Enrique S Quintana-Ortí, and Andrés E Tomás. 2022. “Compressed Basis GMRES on High-Performance Graphics Processing Units.” The International Journal of High Performance Computing Applications 37 (2): 82–100. https://doi.org/10.1177/10943420221115140.

Fasi, Massimiliano, Nicholas J. Higham, Florent Lopez, Theo Mary, and Mantas Mikaitis. 2023. “Matrix Multiplication in Multiword Arithmetic: Error Analysis and Application to GPU Tensor Cores.” SIAM Journal on Scientific Computing 45 (1): C1–19. https://doi.org/10.1137/21m1465032.

Li, Xiaoye S., Paul Lin, Yang Liu, and Piyush Sao. 2023. “Newly Released Capabilities in the Distributed-Memory SuperLU Sparse Direct Solver.” ACM Transactions on Mathematical Software 49 (1): 1–20. https://doi.org/10.1145/3577197.

Gardner, David J., Daniel R. Reynolds, Carol S. Woodward, and Cody J. Balos. 2022. “Enabling New Flexibility in the SUNDIALS Suite of Nonlinear and Differential/Algebraic Equation Solvers.” ACM Transactions on Mathematical Software 48 (3): 1–24. https://doi.org/10.1145/3539801.

Reynolds, Daniel R., David J. Gardner, Carol S. Woodward, and Rujeko Chinomona. 2023. “ARKODE: A Flexible IVP Solver Infrastructure for One-Step Methods.” ACM Transactions on Mathematical Software 49 (2): 1–26. https://doi.org/10.1145/3594632.

Falgout, Robert D., Ruipeng Li, Björn Sjögreen, Lu Wang, and Ulrike Meier Yang. 2021. “Porting Hypre to Heterogeneous Computer Architectures: Strategies and Experiences.” Parallel Computing 108 (December): 102840. https://doi.org/10.1016/j.parco.2021.102840.

Huber, Thomas, Swaroop Pophale, Nolan Baker, Michael Carr, Nikhil Rao, Jaydon Reap, Kristina Holsapple, et al. 2022. “ECP SOLLVE: Validation and Verification Testsuite Status Update and Compiler Insight for OpenMP.” 2022 IEEE/ACM International Workshop on Performance, Portability and Productivity in HPC (P3HPC), November. https://doi.org/10.1109/p3hpc56579.2022.00017.

Lu, Wenbin, Baodi Shan, Eric Raut, Jie Meng, Mauricio Araya-Polo, Johannes Doerfert, Abid M. Malik, and Barbara Chapman. 2022. “Towards Efficient Remote OpenMP Offloading.” Lecture Notes in Computer Science, 17–31. https://doi.org/10.1007/978-3-031-15922-0_2.

Shan, Baodi, Mauricio Araya-Polo, Abid M. Malik, and Barbara Chapman. 2023. “MPI-Based Remote OpenMP Offloading: A More Efficient and Easy-to-Use Implementation.” Proceedings of the 14th International Workshop on Programming Models and Applications for Multicores and Manycores, February. https://doi.org/10.1145/3582514.3582519.

Doerfert, Johannes, Atemn Patel, Joseph Huber, Shilei Tian, Jose M Monsalve Diaz, Barbara Chapman, and Giorgis Georgakoudis. 2022. “Co-Designing an OpenMP GPU Runtime and Optimizations for Near-Zero Overhead Execution.” 2022 IEEE International Parallel and Distributed Processing Symposium (IPDPS), May. https://doi.org/10.1109/ipdps53621.2022.00055.

Tian, Shilei, Joseph Huber, John Tramm, Barbara Chapman, and Johannes Doerfert. 2022. “Just-in-Time Compilation and Link-Time Optimization for OpenMP Target Offloading.” Lecture Notes in Computer Science, 145–58. https://doi.org/10.1007/978-3-031-15922-0_10.

Tian, Shilei, Joseph Huber, Konstantinos Parasyris, Barbara Chapman, and Johannes Doerfert. 2022. “Direct GPU Compilation and Execution for Host Applications with OpenMP Parallelism.” 2022 IEEE/ACM Eighth Workshop on the LLVM Compiler Infrastructure in HPC (LLVM-HPC), November. https://doi.org/10.1109/llvm-hpc56686.2022.00010.

Guaitero, Rafael A. Herrera, Jose M Monsalve Diaz, Thomas Applencourt, Xiaoming Li, and Johannes Doerfert. 2022. “Automatic Asynchronous Execution of Synchronously Offloaded OpenMP Target Regions.” 2022 IEEE/ACM Eighth Workshop on the LLVM Compiler Infrastructure in HPC (LLVM-HPC), November. https://doi.org/10.1109/llvm-hpc56686.2022.00008.

Doerfert, Johannes, Marc Jasper, Joseph Huber, Khaled Abdelaal, Giorgis Georgakoudis, Thomas Scogland, and Konstantinos Parasyris. 2022. “Breaking the Vendor Lock.” Proceedings of the International Conference on Parallel Architectures and Compilation Techniques, October. https://doi.org/10.1145/3559009.3569687.

Talaashrafi, Delaram, Marc Moreno Maza, and Johannes Doerfert. 2022. “Towards Automatic OpenMP-Aware Utilization of Fast GPU Memory.” Lecture Notes in Computer Science, 67–80. https://doi.org/10.1007/978-3-031-15922-0_5.

Talaashrafi, Delaram, Johannes Doerfert, and Marc Moreno Maza. 2022. “A Pipeline Pattern Detection Technique in Polly.” Workshop Proceedings of the 51st International Conference on Parallel Processing, August. https://doi.org/10.1145/3547276.3548445.

Suchyta, Eric, Jong Youl Choi, Seung-Hoe Ku, David Pugmire, Ana Gainaru, Kevin Huck, Ralph Kube, et al. 2022. “Hybrid Analysis of Fusion Data for Online Understanding of Complex Science on Extreme Scale Computers.” 2022 IEEE International Conference on Cluster Computing (CLUSTER), September. https://doi.org/10.1109/cluster51413.2022.00035.

Biswas, Ayan, Soumya Dutta, Terece L. Turton, and James Ahrens. 2022. “Sampling for Scientific Data Analysis and Reduction.” In Situ Visualization for Computational Science, 11–36. https://doi.org/10.1007/978-3-030-81627-8_2.

Marsaglia, Nicole, Meghanto Majumder, and Hank Childs. 2022. “A Trigger-Based Approach for Optimizing Camera Placement Over Time.” 2022 IEEE/ACM International Workshop on In Situ Infrastructures for Enabling Extreme-Scale Analysis and Visualization (ISAV), November. https://doi.org/10.1109/isav56555.2022.00008.

Dutta, Soumya, Terece Turton, David Rogers, Jordan M. Musser, James Ahrens, and Ann S. Almgren. 2022. “In Situ Feature Analysis for Large-Scale Multiphase Flow Simulations.” Journal of Computational Science 63 (September): 101773. https://doi.org/10.1016/j.jocs.2022.101773.

Hussain, Shahid, Kaley Chicoine, and Boyana Norris. 2021. “Empirical Investigation of Code Quality Rule Violations in HPC Applications.” Evaluation and Assessment in Software Engineering, June. https://doi.org/10.1145/3463274.3463787.

Adams, Mark, Satish Balay, Oana Marin, Lois Curfman McInnes, Richard Tran Mills, Todd Munson, Hong Zhang, et al. 2022. “The PETSc Community as Infrastructure.” Computing in Science & Engineering 24 (3): 6–15. https://doi.org/10.1109/mcse.2022.3169974.

Pandey, Santosh, Xiaoye Sherry Li, Aydin Buluc, Jiejun Xu, and Hang Liu. 2019. “H-INDEX: Hash-Indexing for Parallel Triangle Counting on GPUs.” 2019 IEEE High Performance Extreme Computing Conference (HPEC), September. https://doi.org/10.1109/hpec.2019.8916492.

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Bronkhorst, C.A., J.R. Mayeur, V. Livescu, R. Pokharel, D.W. Brown, and G.T. Gray. 2019. “Structural Representation of Additively Manufactured 316L Austenitic Stainless Steel.” International Journal of Plasticity 118 (July): 70–86. https://doi.org/10.1016/j.ijplas.2019.01.012.

Patabandi, Tharindu R., and Mary Hall. 2023. “Efficiently Learning Locality Optimizations by Decomposing Transformation Domains.” Proceedings of the 32nd ACM SIGPLAN International Conference on Compiler Construction, February. https://doi.org/10.1145/3578360.3580272.

Min, Misun, Yu-Hsiang Lan, Paul Fischer, Elia Merzari, Stefan Kerkemeier, Malachi Phillips, Thilina Rathnayake, et al. 2022. “Optimization of Full-Core Reactor Simulations on Summit.” SC22: International Conference for High Performance Computing, Networking, Storage and Analysis, November. https://doi.org/10.1109/sc41404.2022.00079.

McCoy, Hunter, Steven Hofmeyr, Katherine Yelick, and Prashant Pandey. 2023. “High-Performance Filters for GPUs.” Proceedings of the 28th ACM SIGPLAN Annual Symposium on Principles and Practice of Parallel Programming, February. https://doi.org/10.1145/3572848.3577507.

Jin, Sian, Dingwen Tao, Houjun Tang, Sheng Di, Suren Byna, Zarija Lukic, and Franck Cappello. 2022. “Accelerating Parallel Write via Deeply Integrating Predictive Lossy Compression with HDF5.” SC22: International Conference for High Performance Computing, Networking, Storage and Analysis, November. https://doi.org/10.1109/sc41404.2022.00066.

Dutta, Soumya, Dan Lipsa, Terece L. Turton, Berk Geveci, and James Ahrens. 2022. “In Situ Analysis and Visualization of Extreme-Scale Particle Simulations.” High Performance Computing. ISC High Performance 2022 International Workshops, 283–94. https://doi.org/10.1007/978-3-031-23220-6_19.

Bauer, Michael, Elliott Slaughter, Sean Treichler, Wonchan Lee, Michael Garland, and Alex Aiken. 2023. “Visibility Algorithms for Dynamic Dependence Analysis and Distributed Coherence.” Proceedings of the 28th ACM SIGPLAN Annual Symposium on Principles and Practice of Parallel Programming, February. https://doi.org/10.1145/3572848.3577515.

Barca, Giuseppe M. J., Calum Snowdon, Jorge L. Galvez Vallejo, Fazeleh Kazemian, Alistair P. Rendell, and Mark S. Gordon. 2022. “Scaling Correlated Fragment Molecular Orbital Calculations on Summit.” SC22: International Conference for High Performance Computing, Networking, Storage and Analysis, November. https://doi.org/10.1109/sc41404.2022.00012.

Abdelfattah, Ahmad, Pieter Ghysels, Wajih Boukaram, Stanimire Tomov, Xiaoye Sherry Li, and Jack Dongarra. 2022. “Addressing Irregular Patterns of Matrix Computations on GPUs and Their Impact on Applications Powered by Sparse Direct Solvers.” SC22: International Conference for High Performance Computing, Networking, Storage and Analysis, November. https://doi.org/10.1109/sc41404.2022.00031.

Porcu, Roberto, Jordan Musser, Ann S. Almgren, John B. Bell, William D. Fullmer, and Deepak Rangarajan. 2023. “MFIX-Exa: CFD-DEM Simulations of Thermodynamics and Chemical Reactions in Multiphase Flows.” Chemical Engineering Science 273 (June): 118614. https://doi.org/10.1016/j.ces.2023.118614.

Biswas, Ayan, James P. Ahrens, Soumya Dutta, Jordan M. Musser, Ann S. Almgren, and Terece L. Turton. 2021. “Feature Analysis, Tracking, and Data Reduction: An Application to Multiphase Reactor Simulation MFiX-Exa for In-Situ Use Case.” Computing in Science & Engineering 23 (1): 75–82. https://doi.org/10.1109/mcse.2020.3016927.

Fedeli, Luca, Neïl Zaïm, Antonin Sainte-Marie, Maxence Thévenet, Axel Huebl, Andrew Myers, Jean-Luc Vay, and Henri Vincenti. 2022. “PICSAR-QED: A Monte Carlo Module to Simulate Strong-Field Quantum Electrodynamics in Particle-in-Cell Codes for Exascale Architectures.” New Journal of Physics 24 (2): 025009. https://doi.org/10.1088/1367-2630/ac4ef1.

Hakimi, Sahel, Lieselotte Obst-Huebl, Axel Huebl, Kei Nakamura, Stepan S. Bulanov, Sven Steinke, Wim P. Leemans, et al. 2022. “Laser–Solid Interaction Studies Enabled by the New Capabilities of the IP2 BELLA PW Beamline.” Physics of Plasmas 29 (8). https://doi.org/10.1063/5.0089331.

Lehe, Remi, Aurore Blelly, Lorenzo Giacomel, Revathi Jambunathan, and Jean-Luc Vay. 2022. “Absorption of Charged Particles in Perfectly Matched Layers by Optimal Damping of the Deposited Current.” Physical Review E 106 (4). https://doi.org/10.1103/physreve.106.045306.

Zhao, Y., R. Lehe, A. Myers, M. Thévenet, A. Huebl, C. B. Schroeder, and J.-L. Vay. 2022. “Plasma Electron Contribution to Beam Emittance Growth from Coulomb Collisions in Plasma-Based Accelerators.” Physics of Plasmas 29 (10). https://doi.org/10.1063/5.0102919.

Blanchard, Andrew E., Mayanka Chandra Shekar, Shang Gao, John Gounley, Isaac Lyngaas, Jens Glaser, and Debsindhu Bhowmik. 2022. “Automating Genetic Algorithm Mutations for Molecules Using a Masked Language Model.” IEEE Transactions on Evolutionary Computation 26 (4): 793–99. https://doi.org/10.1109/tevc.2022.3144045.

Blanchard, Andrew E, John Gounley, Debsindhu Bhowmik, Mayanka Chandra Shekar, Isaac Lyngaas, Shang Gao, Junqi Yin, Aristeidis Tsaris, Feiyi Wang, and Jens Glaser. 2022. “Language Models for the Prediction of SARS-CoV-2 Inhibitors.” The International Journal of High Performance Computing Applications 36 (5–6): 587–602. https://doi.org/10.1177/10943420221121804.

Chabanier, Solène, J D Emberson, Zarija Lukić, Jesus Pulido, Salman Habib, Esteban Rangel, Jean Sexton, Nicholas Frontiere, and Michael Buehlmann. 2022. “Modelling the Lyman-α Forest with Eulerian and SPH Hydrodynamical Methods.” Monthly Notices of the Royal Astronomical Society 518 (3): 3754–76. https://doi.org/10.1093/mnras/stac3294.

Emberson, J. D., Nicholas Frontiere, Salman Habib, Katrin Heitmann, Patricia Larsen, Hal Finkel, and Adrian Pope. 2019. “The Borg Cube Simulation: Cosmological Hydrodynamics with CRK-SPH.” The Astrophysical Journal 877 (2): 85. https://doi.org/10.3847/1538-4357/ab1b31.

Frontiere, Nicholas, J. D. Emberson, Michael Buehlmann, Joseph Adamo, Salman Habib, Katrin Heitmann, and Claude-André Faucher-Giguère. 2023. “Simulating Hydrodynamics in Cosmology with CRK-HACC.” The Astrophysical Journal Supplement Series 264 (2): 34. https://doi.org/10.3847/1538-4365/aca58d.

Satkauskas, Ignas, Jonathan Maack, Matthew Reynolds, Devon Sigler, Kinshuk Panda, and Wesley Jones. 2022. “Simulating Impacts of Extreme Events on Grids with High Penetrations of Wind Power Resources.” 2022 IEEE/PES Transmission and Distribution Conference and Exposition (T&D), April. https://doi.org/10.1109/td43745.2022.9816884.

Reynolds, Matthew, Ignas Satkauskas, Jonathan Maack, Devon Sigler, and Wesley Jones. 2020. “Scenario Creation and Power-Conditioning Strategies for Operating Power Grids with Two-Stage Stochastic Economic Dispatch.” 2020 IEEE Power & Energy Society General Meeting (PESGM), August. https://doi.org/10.1109/pesgm41954.2020.9281609.

Rao, Vishwas, Anirudh Subramanyam, Michel Schanen, Youngdae Kim, Ignas Satkauskas, and Mihai Anitescu. 2022. “Frequency Recovery in Power Grids Using High-Performance Computing.” Workshop Proceedings of the 51st International Conference on Parallel Processing, August. https://doi.org/10.1145/3547276.3548632.

Pacaud, François, Michel Schanen, Daniel Adrian Maldonado, Alexis Montoison, Valentin Churavy, Julian Samaroo, and Mihai Anitescu. 2022. “Batched Second-Order Adjoint Sensitivity for Reduced Space Methods.” Proceedings of the 2022 SIAM Conference on Parallel Processing for Scientific Computing (PP), January, 60–71. https://doi.org/10.1137/1.9781611977141.6.

Kim, Youngdae, and Kibaek Kim. 2022. “Accelerated Computation and Tracking of AC Optimal Power Flow Solutions Using GPUs.” Workshop Proceedings of the 51st International Conference on Parallel Processing, August. https://doi.org/10.1145/3547276.3548631.

Świrydowicz, Kasia, Eric Darve, Wesley Jones, Jonathan Maack, Shaked Regev, Michael A. Saunders, Stephen J. Thomas, and Slaven Peleš. 2022. “Linear Solvers for Power Grid Optimization Problems: A Review of GPU-Accelerated Linear Solvers.” Parallel Computing 111 (July): 102870. https://doi.org/10.1016/j.parco.2021.102870.

Wang, Jingyi, Nai-Yuan Chiang, and Cosmin G. Petra. 2021. “An Asynchronous Distributed-Memory Optimization Solver for Two-Stage Stochastic Programming Problems.” 2021 20th International Symposium on Parallel and Distributed Computing (ISPDC), July. https://doi.org/10.1109/ispdc52870.2021.9521613.

Bertagna, Luca, Oksana Guba, Mark A. Taylor, James G. Foucar, Jeff Larkin, Andrew M. Bradley, Sivasankaran Rajamanickam, and Andrew G. Salinger. 2020. “A Performance-Portable Nonhydrostatic Atmospheric Dycore for the Energy Exascale Earth System Model Running at Cloud-Resolving Resolutions.” SC20: International Conference for High Performance Computing, Networking, Storage and Analysis, November. https://doi.org/10.1109/sc41405.2020.00096.

Hannah, Walter, Kyle Pressel, Mikhail Ovchinnikov, and Gregory Elsaesser. 2022. “Checkerboard Patterns in E3SMv2 and E3SM-MMFv2.” Geoscientific Model Development 15 (15): 6243–57. https://doi.org/10.5194/gmd-15-6243-2022.

Pajkos, Michael A., MacKenzie L. Warren, Sean M. Couch, Evan P. O’Connor, and Kuo-Chuan Pan. 2021. “Determining the Structure of Rotating Massive Stellar Cores with Gravitational Waves.” The Astrophysical Journal 914 (2): 80. https://doi.org/10.3847/1538-4357/abfb65.

Laiu, M. Paul, Eirik Endeve, Ran Chu, J. Austin Harris, and O. E. Bronson Messer. 2021. “A DG-IMEX Method for Two-Moment Neutrino Transport: Nonlinear Solvers for Neutrino–Matter Coupling*.” The Astrophysical Journal Supplement Series 253 (2): 52. https://doi.org/10.3847/1538-4365/abe2a8.

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Yadav, Rohan, Alex Aiken, and Fredrik Kjolstad. 2022. “DISTAL: The Distributed Tensor Algebra Compiler.” Proceedings of the 43rd ACM SIGPLAN International Conference on Programming Language Design and Implementation, June. https://doi.org/10.1145/3519939.3523437.

Slaughter, Elliott, Wei Wu, Yuankun Fu, Legend Brandenburg, Nicolai Garcia, Wilhem Kautz, Emily Marx, et al. 2020. “Task Bench: A Parameterized Benchmark for Evaluating Parallel Runtime Performance.” SC20: International Conference for High Performance Computing, Networking, Storage and Analysis, November. https://doi.org/10.1109/sc41405.2020.00066.

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Norman, Matthew, Isaac Lyngaas, Abhishek Bagusetty, and Mark Berrill. 2022. “Portable C++ Code That Can Look and Feel Like Fortran Code with Yet Another Kernel Launcher (YAKL).” International Journal of Parallel Programming 51 (4–5): 209–30. https://doi.org/10.1007/s10766-022-00739-0.

Yang, Qiu, Walter M. Hannah, and L. Ruby Leung. 2022. “Convective Momentum Transport and Its Impact on the Madden‐Julian Oscillation in E3SM‐MMF.” Journal of Advances in Modeling Earth Systems 14 (11). https://doi.org/10.1029/2022ms003206.

Lin, Guangxing, L. Ruby Leung, Jungmin Lee, Bryce E. Harrop, Ian T. Baker, Mark D. Branson, A. Scott Denning, et al. 2023. “Modeling Land‐Atmosphere Coupling at Cloud‐Resolving Scale Within the Multiple Atmosphere Multiple Land (MAML) Framework in SP‐E3SM.” Journal of Advances in Modeling Earth Systems 15 (2). https://doi.org/10.1029/2022ms003101.

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Molins, Sergi, David Trebotich, Bhavna Arora, Carl I. Steefel, and Hang Deng. 2019. “Multi-Scale Model of Reactive Transport in Fractured Media: Diffusion Limitations on Rates.” Transport in Porous Media 128 (2): 701–21. https://doi.org/10.1007/s11242-019-01266-2.

Gorman, Christopher, Gustavo Chávez, Pieter Ghysels, Théo Mary, François-Henry Rouet, and Xiaoye Sherry Li. 2019. “Robust and Accurate Stopping Criteria for Adaptive Randomized Sampling in Matrix-Free Hierarchically Semiseparable Construction.” SIAM Journal on Scientific Computing 41 (5): S61–85. https://doi.org/10.1137/18m1194961.

Liu, Yang, Pieter Ghysels, Lisa Claus, and Xiaoye Sherry Li. 2021. “Sparse Approximate Multifrontal Factorization with Butterfly Compression for High-Frequency Wave Equations.” SIAM Journal on Scientific Computing 43 (5): S367–91. https://doi.org/10.1137/20m1349667.

Patil, Onkar, Latchesar Ionkov, Jason Lee, Frank Mueller, and Michael Lang. 2019. “Performance Characterization of a DRAM-NVM Hybrid Memory Architecture for HPC Applications Using Intel Optane DC Persistent Memory Modules.” Proceedings of the International Symposium on Memory Systems, September. https://doi.org/10.1145/3357526.3357541.

Mathuriya, Amrita, Ye Luo, Raymond C. Clay, Anouar Benali, Luke Shulenburger, and Jeongnim Kim. 2017. “Embracing a New Era of Highly Efficient and Productive Quantum Monte Carlo Simulations.” Proceedings of the International Conference for High Performance Computing, Networking, Storage and Analysis, November. https://doi.org/10.1145/3126908.3126952.

Kim, Jeongnim, Andrew D Baczewski, Todd D Beaudet, Anouar Benali, M Chandler Bennett, Mark A Berrill, Nick S Blunt, et al. 2018. “QMCPACK: An Open SourceAb InitioQuantum Monte Carlo Package for the Electronic Structure of Atoms, Molecules and Solids.” Journal of Physics: Condensed Matter 30 (19): 195901. https://doi.org/10.1088/1361-648x/aab9c3.

Archibald, R., J. T. Krogel, and P. R. C. Kent. 2018. “Gaussian Process Based Optimization of Molecular Geometries Using Statistically Sampled Energy Surfaces from Quantum Monte Carlo.” The Journal of Chemical Physics 149 (16). https://doi.org/10.1063/1.5040584.

Choi, Jaemin, David F. Richards, Laxmikant V. Kale, and Abhinav Bhatele. 2020. “End-to-End Performance Modeling of Distributed GPU Applications.” Proceedings of the 34th ACM International Conference on Supercomputing, June. https://doi.org/10.1145/3392717.3392737.

Choi, Jaemin, David F. Richards, and Laxmikant V. Kale. 2020. “Achieving Computation-Communication Overlap with Overdecomposition on GPU Systems.” 2020 IEEE/ACM Fifth International Workshop on Extreme Scale Programming Models and Middleware (ESPM2), November. https://doi.org/10.1109/espm251964.2020.00006.

Kim, Jungwon, Seyong Lee, and Jeffrey S. Vetter. 2017. “PapyrusKV.” Proceedings of the International Conference for High Performance Computing, Networking, Storage and Analysis, November. https://doi.org/10.1145/3126908.3126943.

Wolfe, Michael, Seyong Lee, Jungwon Kim, Xiaonan Tian, Rengan Xu, Barbara Chapman, and Sunita Chandrasekaran. 2018. “The OpenACC Data Model: Preliminary Study on Its Major Challenges and Implementations.” Parallel Computing 78 (October): 15–27. https://doi.org/10.1016/j.parco.2018.07.003.

Belviranli, Mehmet E., Seyong Lee, Jeffrey S. Vetter, and Laxmi N. Bhuyan. 2018. “Juggler.” Proceedings of the 23rd ACM SIGPLAN Symposium on Principles and Practice of Parallel Programming, February. https://doi.org/10.1145/3178487.3178492.

Kruse, Michael, and Hal Finkel. 2018. “User-Directed Loop-Transformations in Clang.” 2018 IEEE/ACM 5th Workshop on the LLVM Compiler Infrastructure in HPC (LLVM-HPC), November. https://doi.org/10.1109/llvm-hpc.2018.8639402.

Finkel, Hal, David Poliakoff, Jean-Sylvain Camier, and David F. Richards. 2019. “ClangJIT: Enhancing C++ with Just-in-Time Compilation.” 2019 IEEE/ACM International Workshop on Performance, Portability and Productivity in HPC (P3HPC), November. https://doi.org/10.1109/p3hpc49587.2019.00013.

Zhao, Tuowen, Samuel Williams, Mary Hall, and Hans Johansen. 2018. “Delivering Performance-Portable Stencil Computations on CPUs and GPUs Using Bricks.” 2018 IEEE/ACM International Workshop on Performance, Portability and Productivity in HPC (P3HPC), November. https://doi.org/10.1109/p3hpc.2018.00009.

Zhao, Tuowen, Protonu Basu, Samuel Williams, Mary Hall, and Hans Johansen. 2019. “Exploiting Reuse and Vectorization in Blocked Stencil Computations on CPUs and GPUs.” Proceedings of the International Conference for High Performance Computing, Networking, Storage and Analysis, November. https://doi.org/10.1145/3295500.3356210.

Denny, Joel E., Seyong Lee, and Jeffrey S. Vetter. 2018. “CLACC: Translating OpenACC to OpenMP in Clang.” 2018 IEEE/ACM 5th Workshop on the LLVM Compiler Infrastructure in HPC (LLVM-HPC), November. https://doi.org/10.1109/llvm-hpc.2018.8639349.

Belviranli, Mehmet E., and Jeffrey S. Vetter. 2019. “FLAME: Graph-Based Hardware Representations for Rapid and Precise Performance Modeling.” 2019 Design, Automation & Test in Europe Conference & Exhibition (DATE), March. https://doi.org/10.23919/date.2019.8747521.

Kim, Jungwon, and Jeffrey S Vetter. 2019. “Implementing Efficient Data Compression and Encryption in a Persistent Key-Value Store for HPC.” The International Journal of High Performance Computing Applications 33 (6): 1098–1112. https://doi.org/10.1177/1094342019847264.

Lambert, Jacob, Seyong Lee, Jeffrey S. Vetter, and Allen D. Malony. 2020. “CCAMP: An Integrated Translation and Optimization Framework for OpenACC and OpenMP.” SC20: International Conference for High Performance Computing, Networking, Storage and Analysis, November. https://doi.org/10.1109/sc41405.2020.00102.

Lambert, Jacob, Seyong Lee, Jeffrey S. Vetter, and Allen Malony. 2020. “In-Depth Optimization with the OpenACC-to-FPGA Framework on an Arria 10 FPGA.” 2020 IEEE International Parallel and Distributed Processing Symposium Workshops (IPDPSW), May. https://doi.org/10.1109/ipdpsw50202.2020.00084.

Lambert, Jacob, Seyong Lee, Allen Malony, and Jeffrey S. Vetter. 2020. “CCAMP: OpenMP and OpenACC Interoperable Framework.” Lecture Notes in Computer Science, 357–69. https://doi.org/10.1007/978-3-030-48340-1_28.

Coti, Camille, Joel E. Denny, Kevin Huck, Seyong Lee, Allen D. Malony, Sameer Shende, and Jeffrey S. Vetter. 2020. “OpenACC Profiling Support for Clang and LLVM Using Clacc and TAU.” 2020 IEEE/ACM International Workshop on HPC User Support Tools (HUST) and Workshop on Programming and Performance Visualization Tools (ProTools), November. https://doi.org/10.1109/hustprotools51951.2020.00012.

Kolla, Hemanth, and Jacqueline H. Chen. 2017. “Turbulent Combustion Simulations with High-Performance Computing.” Modeling and Simulation of Turbulent Combustion, December, 73–97. https://doi.org/10.1007/978-981-10-7410-3_3.

Ge, Wenjun, and Ramanan Sankaran. 2019. “An Adaptive Particle Tracking Algorithm for Lagrangian-Eulerian Simulations of Dispersed Multiphase Flows.” AIAA Scitech 2019 Forum, January. https://doi.org/10.2514/6.2019-0728.

Martin, Michael J., Shashank Yellapantula, Marc Day, John B. Bell, and Ray W. Grout. 2019. “Impingement of a Supercritical Carbon Dioxide Jet on a Planar Surface.” AIAA Scitech 2019 Forum, January. https://doi.org/10.2514/6.2019-1559.

Klippenstein, Stephen J., and Carlo Cavallotti. 2019. “Ab Initio Kinetics for Pyrolysis and Combustion Systems.” Mathematical Modelling of Gas-Phase Complex Reaction Systems: Pyrolysis and Combustion, 115–67. https://doi.org/10.1016/b978-0-444-64087-1.00002-4.

Ge, Wenjun, Vimal Ramanuj, and Ramanan Sankaran. 2020. “Lagrangian Simulations of Spray Interaction with a Surface Using a Stochastic Multi-Regime Impingement Model.” AIAA Scitech 2020 Forum, January. https://doi.org/10.2514/6.2020-0910.

Martin, Michael James, Elizabeth G. Rasmussen, and Shashank Yellapantula. 2019. “Nonlinear Heat Transfer From Particles in Supercritical Carbon Dioxide Near the Critical Point.” Journal of Thermal Science and Engineering Applications 12 (3). https://doi.org/10.1115/1.4045222.

Elliott, Sarah N., Kevin B. Moore, Andreas V. Copan, Murat Keçeli, Carlo Cavallotti, Yuri Georgievskii, Henry F. Schaefer, and Stephen J. Klippenstein. 2021. “Automated Theoretical Chemical Kinetics: Predicting the Kinetics for the Initial Stages of Pyrolysis.” Proceedings of the Combustion Institute 38 (1): 375–84. https://doi.org/10.1016/j.proci.2020.06.019.

Hoque, Reazul, Thomas Herault, George Bosilca, and Jack Dongarra. 2017. “Dynamic Task Discovery in PaRSEC.” Proceedings of the 8th Workshop on Latest Advances in Scalable Algorithms for Large-Scale Systems, November. https://doi.org/10.1145/3148226.3148233.

Poppl, Alexander, Scott Baden, and Michael Bader. 2019. “A UPC++ Actor Library and Its Evaluation On a Shallow Water Proxy Application.” 2019 IEEE/ACM Parallel Applications Workshop, Alternatives To MPI (PAW-ATM), November. https://doi.org/10.1109/paw-atm49560.2019.00007.

Bonachea, Dan, and Paul H. Hargrove. 2019. “GASNet-EX: A High-Performance, Portable Communication Library for Exascale.” Lecture Notes in Computer Science, 138–58. https://doi.org/10.1007/978-3-030-34627-0_11.

Peng, Chong, Justus A. Calvin, and Edward F. Valeev. 2019. “Coupled‐cluster Singles, Doubles and Perturbative Triples with Density Fitting Approximation for Massively Parallel Heterogeneous Platforms.” International Journal of Quantum Chemistry 119 (12). https://doi.org/10.1002/qua.25894.

Kumar, Ashutosh, Frank Neese, and Edward F. Valeev. 2020. “Explicitly Correlated Coupled Cluster Method for Accurate Treatment of Open-Shell Molecules with Hundreds of Atoms.” The Journal of Chemical Physics 153 (9). https://doi.org/10.1063/5.0012753.

Dang, Hoang-Vu, and Marc Snir. 2018. “FULT.” Proceedings of the 47th International Conference on Parallel Processing, August. https://doi.org/10.1145/3225058.3225115.

Chunduri, Sudheer, Scott Parker, Pavan Balaji, Kevin Harms, and Kalyan Kumaran. 2018. “Characterization of MPI Usage on a Production Supercomputer.” SC18: International Conference for High Performance Computing, Networking, Storage and Analysis, November. https://doi.org/10.1109/sc.2018.00033.

Amer, Abdelhalim, Huiwei Lu, Pavan Balaji, Milind Chabbi, Yanjie Wei, Jeff Hammond, and Satoshi Matsuoka. 2018. “Lock Contention Management in Multithreaded MPI.” ACM Transactions on Parallel Computing 5 (3): 1–21. https://doi.org/10.1145/3275443.

Wilkins, Michael, Yanfei Guo, Rajeev Thakur, Nikos Hardavellas, Peter Dinda, and Min Si. 2021. “A FACT-Based Approach: Making Machine Learning Collective Autotuning Feasible on Exascale Systems.” 2021 Workshop on Exascale MPI (ExaMPI), November. https://doi.org/10.1109/exampi54564.2021.00010.

Lee, Wonchan, George Stelle, Patrick McCormick, and Alex Aiken. 2018. “Correctness of Dynamic Dependence Analysis for Implicitly Parallel Tasking Systems.” 2018 IEEE/ACM 2nd International Workshop on Software Correctness for HPC Applications (Correctness), November. https://doi.org/10.1109/correctness.2018.00007.

Lee, Wonchan, Elliott Slaughter, Michael Bauer, Sean Treichler, Todd Warszawski, Michael Garland, and Alex Aiken. 2018. “Dynamic Tracing: Memoization of Task Graphs for Dynamic Task-Based Runtimes.” SC18: International Conference for High Performance Computing, Networking, Storage and Analysis, November. https://doi.org/10.1109/sc.2018.00037.

Soi, Rupanshu, Michael Bauer, Sean Treichler, Manolis Papadakis, Wonchan Lee, Patrick McCormick, Alex Aiken, and Elliott Slaughter. 2021. “Index Launches.” Proceedings of the International Conference for High Performance Computing, Networking, Storage and Analysis, November. https://doi.org/10.1145/3458817.3476175.

Brower, Richard C., Evan Weinberg, M. A. Clark, and Alexei Strelchenko. 2018. “Multigrid Algorithm for Staggered Lattice Fermions.” Physical Review D 97 (11). https://doi.org/10.1103/physrevd.97.114513.

Zhou, Keren, and John Mellor-Crummey. 2019. “A Tool for Performance Analysis of GPU-Accelerated Applications.” 2019 IEEE/ACM International Symposium on Code Generation and Optimization (CGO), February. https://doi.org/10.1109/cgo.2019.8661169.

Zhou, Keren, Yueming Hao, John Mellor-Crummey, Xiaozhu Meng, and Xu Liu. 2020. “GVPROF: A Value Profiler for GPU-Based Clusters.” SC20: International Conference for High Performance Computing, Networking, Storage and Analysis, November. https://doi.org/10.1109/sc41405.2020.00093.

Zahariev, F., and M. S. Gordon. 2019. “Development of a Combined Quantum Monte Carlo-Effective Fragment Molecular Orbital Method.” Molecular Physics 117 (9–12): 1532–40. https://doi.org/10.1080/00268976.2019.1574363.

Mironov, Vladimir, Yuri Alexeev, and Dmitri G. Fedorov. 2019. “Multithreaded Parallelization of the Energy and Analytic Gradient in the Fragment Molecular Orbital Method.” International Journal of Quantum Chemistry 119 (12). https://doi.org/10.1002/qua.25937.

Barca, Giuseppe M. J., David L. Poole, Jorge L. Galvez Vallejo, Melisa Alkan, Colleen Bertoni, Alistair P. Rendell, and Mark S. Gordon. 2020. “Scaling the Hartree-Fock Matrix Build on Summit.” SC20: International Conference for High Performance Computing, Networking, Storage and Analysis, November. https://doi.org/10.1109/sc41405.2020.00085.

Sprague, M A, S Ananthan, G Vijayakumar, and M Robinson. 2020. “ExaWind: A Multifidelity Modeling and Simulation Environment for Wind Energy.” Journal of Physics: Conference Series 1452 (1): 012071. https://doi.org/10.1088/1742-6596/1452/1/012071.

Mullowney, Paul, Ruipeng Li, Stephen Thomas, Shreyas Ananthan, Ashesh Sharma, Jon S. Rood, Alan B. Williams, and Michael A. Sprague. 2021. “Preparing an Incompressible-Flow Fluid Dynamics Code for Exascale-Class Wind Energy Simulations.” Proceedings of the International Conference for High Performance Computing, Networking, Storage and Analysis, November. https://doi.org/10.1145/3458817.3476185.

Paul Laiu, M, J Austin Harris, Ran Chu, and Eirik Endeve. 2020. “Thornado-Transport: Anderson- and GPU-Accelerated Nonlinear Solvers for Neutrino-Matter Coupling1.” Journal of Physics: Conference Series 1623 (1): 012013. https://doi.org/10.1088/1742-6596/1623/1/012013.

Chu, Ran, Eirik Endeve, Cory D. Hauck, Anthony Mezzacappa, and Bronson Messer. 2019. “Thornado-Transport: IMEX Schemes for Two-Moment Neutrino Transport Respecting Fermi-Dirac Statistics.” Journal of Physics: Conference Series 1225 (1): 012013. https://doi.org/10.1088/1742-6596/1225/1/012013.

Chu, Ran, Eirik Endeve, Cory D. Hauck, and Anthony Mezzacappa. 2019. “Realizability-Preserving DG-IMEX Method for the Two-Moment Model of Fermion Transport.” Journal of Computational Physics 389 (July): 62–93. https://doi.org/10.1016/j.jcp.2019.03.037.

Zingale, M., A. S. Almgren, M. Barrios Sazo, J. B. Bell, K. Eiden, A. Harpole, M. P. Katz, A. J. Nonaka, D. E. Willcox, and W. Zhang. 2020. “The Castro AMR Simulation Code: Current and Future Developments.” Journal of Physics: Conference Series 1623 (1): 012021. https://doi.org/10.1088/1742-6596/1623/1/012021.

Romano, Paul K., Amanda L. Lund, and Andrew R. Siegel. 2017. “Optimal Run Strategies in Monte Carlo Iterated Fission Source Simulations.” Nuclear Science and Engineering 188 (1): 43–56. https://doi.org/10.1080/00295639.2017.1340692.

Hamilton, Steven P., and Thomas M. Evans. 2019. “Continuous-Energy Monte Carlo Neutron Transport on GPUs in the Shift Code.” Annals of Nuclear Energy 128 (June): 236–47. https://doi.org/10.1016/j.anucene.2019.01.012.

Peng, Xingjie, Pablo Ducru, Shichang Liu, Benoit Forget, Jingang Liang, and Kord Smith. 2018. “Converting Point-Wise Nuclear Cross Sections to Pole Representation Using Regularized Vector Fitting.” Computer Physics Communications 224 (March): 52–62. https://doi.org/10.1016/j.cpc.2017.12.004.

Romano, Paul K., and Jonathan A. Walsh. 2018. “An Improved Target Velocity Sampling Algorithm for Free Gas Elastic Scattering.” Annals of Nuclear Energy 114 (April): 318–24. https://doi.org/10.1016/j.anucene.2017.12.044.

Shriver, Forrest, Seyong Lee, Steven Hamilton, Jeffrey Vetter, and Justin Watson. 2019. “Enhancing Monte Carlo Proxy Applications on GPUs.” 2019 IEEE/ACM Performance Modeling, Benchmarking and Simulation of High Performance Computer Systems (PMBS), November. https://doi.org/10.1109/pmbs49563.2019.00009.

Forget, B., S. Kumar, and K. Smith. 2019. “Stationarity Diagnostics for Monte Carlo Problems That Utilize Source Acceleration Schemes.” Transactions of the American Nuclear Society - Volume 121. https://doi.org/10.13182/t31349.

Grayson, B., and L. Kerby. 2019. “Spherical Functional Expansions in MOOSE.” Transactions of the American Nuclear Society - Volume 121. https://doi.org/10.13182/t30905.

Boyd, William, Adam Nelson, Paul K. Romano, Samuel Shaner, Benoit Forget, and Kord Smith. 2019. “Multigroup Cross-Section Generation with the OpenMC Monte Carlo Particle Transport Code.” Nuclear Technology 205 (7): 928–44. https://doi.org/10.1080/00295450.2019.1571828.

Tramm, John R., Andrew R. Siegel, Amanda L. Lund, and Paul K. Romano. 2021. “A COMPARISON OF STOCHASTIC MESH CELL VOLUME COMPUTATION STRATEGIES FOR THE RANDOM RAY METHOD OF NEUTRAL PARTICLE TRANSPORT.” Edited by M. Margulis and P. Blaise. EPJ Web of Conferences 247: 03021. https://doi.org/10.1051/epjconf/202124703021.

Shriwise, Patrick C., John R. Tramm, Andrew Davis, and Paul K. Romano. 2021. “TOWARDS CAD-BASED GEOMETRY MODELLING WITH THE RANDOM RAY METHOD.” Edited by M. Margulis and P. Blaise. EPJ Web of Conferences 247: 03023. https://doi.org/10.1051/epjconf/202124703023.

Lund, A., A. Johnson, J. Liang, and P. Romano. 2020. “Energy Deposition in the OpenMC Monte Carlo Particle Transport Code.” Transactions of the American Nuclear Society - Volume 123. https://doi.org/10.13182/t123-33100.

Romano, Paul K., Steven P. Hamilton, Ronald O. Rahaman, April Novak, Elia Merzari, Sterling M. Harper, and Patrick C. Shriwise. 2021. “DESIGN OF A CODE-AGNOSTIC DRIVER APPLICATION FOR HIGH-FIDELITY COUPLED NEUTRONICS AND THERMAL-HYDRAULIC SIMULATIONS.” Edited by M. Margulis and P. Blaise. EPJ Web of Conferences 247: 06053. https://doi.org/10.1051/epjconf/202124706053.

Jin, Sian, Pascal Grosset, Christopher M. Biwer, Jesus Pulido, Jiannan Tian, Dingwen Tao, and James Ahrens. 2020. “Understanding GPU-Based Lossy Compression for Extreme-Scale Cosmological Simulations.” 2020 IEEE International Parallel and Distributed Processing Symposium (IPDPS), May. https://doi.org/10.1109/ipdps47924.2020.00021.

Jin, Sian, Jesus Pulido, Pascal Grosset, Jiannan Tian, Dingwen Tao, and James Ahrens. 2021. “Adaptive Configuration of In Situ Lossy Compression for Cosmology Simulations via Fine-Grained Rate-Quality Modeling.” Proceedings of the 30th International Symposium on High-Performance Parallel and Distributed Computing, June. https://doi.org/10.1145/3431379.3460653.

Jain, Arpan, Tim Moon, Tom Benson, Hari Subramoni, Sam Ade Jacobs, Dhabaleswar K Panda, and Brian Van Essen. 2021. “SUPER: SUb-Graph Parallelism for TransformERs.” 2021 IEEE International Parallel and Distributed Processing Symposium (IPDPS), May. https://doi.org/10.1109/ipdps49936.2021.00071.

Ward, Logan, Ben Blaiszik, Ian Foster, Rajeev S. Assary, Badri Narayanan, and Larry Curtiss. 2019. “Machine Learning Prediction of Accurate Atomization Energies of Organic Molecules from Low-Fidelity Quantum Chemical Calculations.” MRS Communications 9 (3): 891–99. https://doi.org/10.1557/mrc.2019.107.

Zhang, Zhao, Lei Huang, J. Gregory Pauloski, and Ian T. Foster. 2020. “Efficient I/O for Neural Network Training with Compressed Data.” 2020 IEEE International Parallel and Distributed Processing Symposium (IPDPS), May. https://doi.org/10.1109/ipdps47924.2020.00050.

Pauloski, J. Gregory, Zhao Zhang, Lei Huang, Weijia Xu, and Ian T. Foster. 2020. “Convolutional Neural Network Training with Distributed K-FAC.” SC20: International Conference for High Performance Computing, Networking, Storage and Analysis, November. https://doi.org/10.1109/sc41405.2020.00098.

Xiang, Lizhi, Arif Khan, Edoardo Serra, Mahantesh Halappanavar, and Aravind Sukumaran-Rajam. 2021. “CuTS.” Proceedings of the International Conference for High Performance Computing, Networking, Storage and Analysis, November. https://doi.org/10.1145/3458817.3476214.

Tang, Yu-Hang, Oguz Selvitopi, Doru Thom Popovici, and Aydin Buluc. 2020. “A High-Throughput Solver for Marginalized Graph Kernels on GPU.” 2020 IEEE International Parallel and Distributed Processing Symposium (IPDPS), May. https://doi.org/10.1109/ipdps47924.2020.00080.

Barik, Reet, Marco Minutoli, Mahantesh Halappanavar, Nathan R. Tallent, and Ananth Kalyanaraman. 2020. “Vertex Reordering for Real-World Graphs and Applications: An Empirical Evaluation.” 2020 IEEE International Symposium on Workload Characterization (IISWC), October. https://doi.org/10.1109/iiswc50251.2020.00031.

Bogle, Ian, Erik G. Boman, Karen Devine, Sivasankaran Rajamanickam, and George M. Slota. 2020. “Distributed Memory Graph Coloring Algorithms for Multiple GPUs.” 2020 IEEE/ACM 10th Workshop on Irregular Applications: Architectures and Algorithms (IA3), November. https://doi.org/10.1109/ia351965.2020.00013.

Thayer, Jana B., Gabriella Carini, Wilko Kroeger, Chris O’Grady, Amedeo Perazzo, Murali Shankar, and Matt Weaver. 2017. “Building a Data System for LCLS-II.” 2017 IEEE Nuclear Science Symposium and Medical Imaging Conference (NSS/MIC), October. https://doi.org/10.1109/nssmic.2017.8533033.

Thayer, Jana, Clemens Weninger, Seshu Yamajala, Sioan Zohar, Daniel Damiani, Mikhail Dubrovin, Christopher Ford, et al. 2019. “Data Processing at the Linac Coherent Light Source.” 2019 IEEE/ACM 1st Annual Workshop on Large-Scale Experiment-in-the-Loop Computing (XLOOP), November. https://doi.org/10.1109/xloop49562.2019.00011.

Azad, Ariful, Georgios A Pavlopoulos, Christos A Ouzounis, Nikos C Kyrpides, and Aydin Buluç. 2018. “HipMCL: A High-Performance Parallel Implementation of the Markov Clustering Algorithm for Large-Scale Networks.” Nucleic Acids Research 46 (6): e33–e33. https://doi.org/10.1093/nar/gkx1313.

Azad, Ariful, and Aydin Buluc. 2019. “LACC: A Linear-Algebraic Algorithm for Finding Connected Components in Distributed Memory.” 2019 IEEE International Parallel and Distributed Processing Symposium (IPDPS), May. https://doi.org/10.1109/ipdps.2019.00012.

Selvitopi, Oguz, Md Taufique Hussain, Ariful Azad, and Aydin Buluc. 2020. “Optimizing High Performance Markov Clustering for Pre-Exascale Architectures.” 2020 IEEE International Parallel and Distributed Processing Symposium (IPDPS), May. https://doi.org/10.1109/ipdps47924.2020.00022.

Zeni, Alberto, Giulia Guidi, Marquita Ellis, Nan Ding, Marco D. Santambrogio, Steven Hofmeyr, Aydin Buluc, Leonid Oliker, and Katherine Yelick. 2020. “LOGAN: High-Performance GPU-Based X-Drop Long-Read Alignment.” 2020 IEEE International Parallel and Distributed Processing Symposium (IPDPS), May. https://doi.org/10.1109/ipdps47924.2020.00055.

Tripathy, Alok, Katherine Yelick, and Aydin Buluc. 2020. “Reducing Communication in Graph Neural Network Training.” SC20: International Conference for High Performance Computing, Networking, Storage and Analysis, November. https://doi.org/10.1109/sc41405.2020.00074.

Selvitopi, Oguz, Saliya Ekanayake, Giulia Guidi, Georgios A. Pavlopoulos, Ariful Azad, and Aydin Buluc. 2020. “Distributed Many-to-Many Protein Sequence Alignment Using Sparse Matrices.” SC20: International Conference for High Performance Computing, Networking, Storage and Analysis, November. https://doi.org/10.1109/sc41405.2020.00079.

Peverelli, Francesco, Lorenzo Di Tucci, Marco D. Santambrogio, Nan Ding, Steven Hofmeyr, Aydin Buluc, Leonid Oliker, and Katherine Yelick. 2020. “GPU Accelerated Partial Order Multiple Sequence Alignment for Long Reads Self-Correction.” 2020 IEEE International Parallel and Distributed Processing Symposium Workshops (IPDPSW), May. https://doi.org/10.1109/ipdpsw50202.2020.00039.

Pandey, Prashant, Brian Wheatman, Helen Xu, and Aydin Buluc. 2021. “Terrace: A Hierarchical Graph Container for Skewed Dynamic Graphs.” Proceedings of the 2021 International Conference on Management of Data, June. https://doi.org/10.1145/3448016.3457313.

Nisa, Israt, Prashant Pandey, Marquita Ellis, Leonid Oliker, Aydin Buluc, and Katherine Yelick. 2021. “Distributed-Memory k-Mer Counting on GPUs.” 2021 IEEE International Parallel and Distributed Processing Symposium (IPDPS), May. https://doi.org/10.1109/ipdps49936.2021.00061.

Yuan, L, A S Sabau, D StJohn, A Prasad, and P D Lee. 2020. “Columnar-to-Equiaxed Transition in a Laser Scan for Metal Additive Manufacturing.” IOP Conference Series: Materials Science and Engineering 861 (1): 012007. https://doi.org/10.1088/1757-899x/861/1/012007.

Hyde, David A. B., Steven W. Gagniere, Alan Marquez-Razon, and Joseph Teran. 2020. “An Implicit Updated Lagrangian Formulation for Liquids with Large Surface Energy.” ACM Transactions on Graphics 39 (6): 1–13. https://doi.org/10.1145/3414685.3417845.

Gagniere, S., D. Hyde, A. Marquez‐Razon, C. Jiang, Z. Ge, X. Han, Q. Guo, and J. Teran. 2020. “A Hybrid Lagrangian/Eulerian Collocated Velocity Advection and Projection Method for Fluid Simulation.” Computer Graphics Forum 39 (8): 1–14. https://doi.org/10.1111/cgf.14096.

Yang, L., and B. D. Wirth. 2018. “Energetics of Hydrogen and Helium-Vacancy Complexes in Bulk and near Surfaces of Tungsten: First-Principles Study.” Journal of Applied Physics 123 (21). https://doi.org/10.1063/1.5027805.

Yang, L., Z.J. Bergstrom, and B.D. Wirth. 2018. “Effect of Interatomic Potential on the Energetics of Hydrogen and Helium-Vacancy Complexes in Bulk, or near Surfaces of Tungsten.” Journal of Nuclear Materials 512 (December): 357–70. https://doi.org/10.1016/j.jnucmat.2018.10.032.

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Yang, L., B.D. Wirth, Danny Perez, and Arthur F. Voter. 2019. “Mobility of Tungsten Clusters on Tungsten Surfaces.” Nuclear Instruments and Methods in Physics Research Section B: Beam Interactions with Materials and Atoms 453 (August): 61–66. https://doi.org/10.1016/j.nimb.2019.05.078.

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Karabin, Mariia, and Danny Perez. 2020. “An Entropy-Maximization Approach to Automated Training Set Generation for Interatomic Potentials.” The Journal of Chemical Physics 153 (9). https://doi.org/10.1063/5.0013059.

Petrone, Floriana, Norman Abrahamson, David McCallen, and Mamun Miah. 2020. “Validation of (Not‐historical) Large‐event Near‐fault Ground‐motion Simulations for Use in Civil Engineering Applications.” Earthquake Engineering & Structural Dynamics 50 (1): 116–34. https://doi.org/10.1002/eqe.3366.

Tang, Houjun, Suren Byna, N Anders Petersson, and David McCallen. 2021. “Tuning Parallel Data Compression and I/O for Large-Scale Earthquake Simulation.” 2021 IEEE International Conference on Big Data (Big Data), December. https://doi.org/10.1109/bigdata52589.2021.9671876.

Terai, C. R., M. S. Pritchard, P. Blossey, and C. S. Bretherton. 2020. “The Impact of Resolving Subkilometer Processes on Aerosol‐Cloud Interactions of Low‐Level Clouds in Global Model Simulations.” Journal of Advances in Modeling Earth Systems 12 (11). https://doi.org/10.1029/2020ms002274.

Hou, Kaiyuan, Reda Al-Bahrani, Esteban Rangel, Ankit Agrawal, Robert Latham, Robert Ross, Alok Choudhary, and Wei-keng Liao. 2018. “Integration of Burst Buffer in High-Level Parallel I/O Library for Exa-Scale Computing Era.” 2018 IEEE/ACM 3rd International Workshop on Parallel Data Storage & Data Intensive Scalable Computing Systems (PDSW-DISCS), November. https://doi.org/10.1109/pdsw-discs.2018.000-1.

Kang, Qiao, Sunwoo Lee, Kaiyuan Hou, Robert Ross, Ankit Agrawal, Alok Choudhary, and Wei-keng Liao. 2020. “Improving MPI Collective I/O for High Volume Non-Contiguous Requests With Intra-Node Aggregation.” IEEE Transactions on Parallel and Distributed Systems 31 (11): 2682–95. https://doi.org/10.1109/tpds.2020.3000458.

Mniszewski, Susan M., Romain Perriot, Emanuel H. Rubensson, Christian F. A. Negre, Marc J. Cawkwell, and Anders M. N. Niklasson. 2018. “Linear Scaling Pseudo Fermi-Operator Expansion for Fractional Occupation.” Journal of Chemical Theory and Computation 15 (1): 190–200. https://doi.org/10.1021/acs.jctc.8b00887.

Perriot, Romain, Christian F. A. Negre, Shawn D. McGrane, and Marc J. Cawkwell. 2018. “Density Functional Tight Binding Calculations for the Simulation of Shocked Nitromethane with LATTE-LAMMPS.” AIP Conference Proceedings. https://doi.org/10.1063/1.5044797.

Bock, Nicolas, Christian F. A. Negre, Susan M. Mniszewski, Jamaludin Mohd-Yusof, Bálint Aradi, Jean-Luc Fattebert, Daniel Osei-Kuffuor, Timothy C. Germann, and Anders M. N. Niklasson. 2018. “The Basic Matrix Library (BML) for Quantum Chemistry.” The Journal of Supercomputing 74 (11): 6201–19. https://doi.org/10.1007/s11227-018-2533-0.

Pouchard, Line, Abid Malik, Huub Van Dam, Cong Xie, Wei Xu, and Kerstin Kleese Van Dam. 2017. “Capturing Provenance as a Diagnostic Tool for Workflow Performance Evaluation and Optimization.” 2017 New York Scientific Data Summit (NYSDS), August. https://doi.org/10.1109/nysds.2017.8085043.

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Pouchard, Line, Kevin Huck, Gyorgy Matyasfalvi, Dingwen Tao, Li Tang, Huub Van Dam, and Shinaje Yoo. 2018. “Prescriptive Provenance for Streaming Analysis of Workflows at Scale.” 2018 New York Scientific Data Summit (NYSDS), August. https://doi.org/10.1109/nysds.2018.8538951.

Ainsworth, Mark, Ozan Tugluk, Ben Whitney, and Scott Klasky. 2018. “Multilevel Techniques for Compression and Reduction of Scientific Data—the Univariate Case.” Computing and Visualization in Science 19 (5–6): 65–76. https://doi.org/10.1007/s00791-018-00303-9.

Retzlaff, Michael, Todd Munson, and Zichao Di. 2019. “Data Compression for Optimization of a Molecular Dynamics System: Preserving Basins of Attraction.” Computational Science – ICCS 2019, 457–70. https://doi.org/10.1007/978-3-030-22744-9_36.

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Imre, Martin, Jun Han, Julien Dominski, Michael Churchill, Ralph Kube, Choong-Seock Chang, Tom Peterka, Hanqi Guo, and Chaoli Wang. 2019. “ContourNet: Salient Local Contour Identification for Blob Detection in Plasma Fusion Simulation Data.” Lecture Notes in Computer Science, 289–301. https://doi.org/10.1007/978-3-030-33720-9_22.

Pouchard, Line, Sterling Baldwin, Todd Elsethagen, Shantenu Jha, Bibi Raju, Eric Stephan, Li Tang, and Kerstin Kleese Van Dam. 2019. “Computational Reproducibility of Scientific Workflows at Extreme Scales.” The International Journal of High Performance Computing Applications 33 (5): 763–76. https://doi.org/10.1177/1094342019839124.

Ainsworth, Mark, Ozan Tugluk, Ben Whitney, and Scott Klasky. 2019. “Multilevel Techniques for Compression and Reduction of Scientific Data---The Multivariate Case.” SIAM Journal on Scientific Computing 41 (2): A1278–1303. https://doi.org/10.1137/18m1166651.

Zhao, Kai, Sheng Di, Xin Lian, Sihuan Li, Dingwen Tao, Julie Bessac, Zizhong Chen, and Franck Cappello. 2020. “SDRBench: Scientific Data Reduction Benchmark for Lossy Compressors.” 2020 IEEE International Conference on Big Data (Big Data), December. https://doi.org/10.1109/bigdata50022.2020.9378449.

Underwood, Robert, Sheng Di, Jon C. Calhoun, and Franck Cappello. 2020. “FRaZ: A Generic High-Fidelity Fixed-Ratio Lossy Compression Framework for Scientific Floating-Point Data.” 2020 IEEE International Parallel and Distributed Processing Symposium (IPDPS), May. https://doi.org/10.1109/ipdps47924.2020.00065.

Yakushin, Igor, Kshitij Mehta, Jieyang Chen, Matthew Wolf, Ian Foster, Scott Klasky, and Todd Munson. 2020. “Feature-Preserving Lossy Compression for In Situ Data Analysis.” 49th International Conference on Parallel Processing - ICPP : Workshops, August. https://doi.org/10.1145/3409390.3409400.

Li, Heyi, Yuewei Lin, Klaus Mueller, and Wei Xu. 2020. “Interpreting Galaxy Deblender GAN from the Discriminator’s Perspective.” Lecture Notes in Computer Science, 239–50. https://doi.org/10.1007/978-3-030-64559-5_18.

George, Jithin, and Zichao Di. 2020. “Trilateration-Based Multilevel Method for Minimizing the Lennard-Jones Potential.” Computational Science – ICCS 2020, 163–75. https://doi.org/10.1007/978-3-030-50426-7_13.

Shu, Tong, Yanfei Guo, Justin Wozniak, Xiaoning Ding, Ian Foster, and Tahsin Kurc. 2021. “Bootstrapping In-Situ Workflow Auto-Tuning via Combining Performance Models of Component Applications.” Proceedings of the International Conference for High Performance Computing, Networking, Storage and Analysis, November. https://doi.org/10.1145/3458817.3476197.

Haidar, Azzam, Khairul Kabir, Diana Fayad, Stanimire Tomov, and Jack Dongarra. 2017. “Out of Memory SVD Solver for Big Data.” 2017 IEEE High Performance Extreme Computing Conference (HPEC), September. https://doi.org/10.1109/hpec.2017.8091029.

Dong, Tingxing, Azzam Haidar, Stanimire Tomov, and Jack Dongarra. 2017. “Optimizing the SVD Bidiagonalization Process for a Batch of Small Matrices.” Procedia Computer Science 108: 1008–18. https://doi.org/10.1016/j.procs.2017.05.237.

Luszczek, Piotr, Jakub Kurzak, Ichitaro Yamazaki, and Jack Dongarra. 2017. “Towards Numerical Benchmark for Half-Precision Floating Point Arithmetic.” 2017 IEEE High Performance Extreme Computing Conference (HPEC), September. https://doi.org/10.1109/hpec.2017.8091031.

Kabir, Khairul, Azzam Haidar, Stanimire Tomov, Aurelien Bouteiller, and Jack Dongarra. 2017. “A Framework for Out of Memory SVD Algorithms.” High Performance Computing, 158–78. https://doi.org/10.1007/978-3-319-58667-0_9.

Haidar, Azzam, Panruo Wu, Stanimire Tomov, and Jack Dongarra. 2017. “Investigating Half Precision Arithmetic to Accelerate Dense Linear System Solvers.” Proceedings of the 8th Workshop on Latest Advances in Scalable Algorithms for Large-Scale Systems, November. https://doi.org/10.1145/3148226.3148237.

Haidar, Azzam, Ahmad Abdelfattah, Mawussi Zounon, Panruo Wu, Srikara Pranesh, Stanimire Tomov, and Jack Dongarra. 2018. “The Design of Fast and Energy-Efficient Linear Solvers: On the Potential of Half-Precision Arithmetic and Iterative Refinement Techniques.” Computational Science – ICCS 2018, 586–600. https://doi.org/10.1007/978-3-319-93698-7_45.

Abdelfattah, Ahmad, Azzam Haidar, Stanimire Tomov, and Jack Dongarra. 2018. “Analysis and Design Techniques towards High-Performance and Energy-Efficient Dense Linear Solvers on GPUs.” IEEE Transactions on Parallel and Distributed Systems 29 (12): 2700–2712. https://doi.org/10.1109/tpds.2018.2842785.

Abdelfattah, Ahmad, Azzam Haidar, Stanimire Tomov, and Jack Dongarra. 2018. “Batched One-Sided Factorizations of Tiny Matrices Using GPUs: Challenges and Countermeasures.” Journal of Computational Science 26 (May): 226–36. https://doi.org/10.1016/j.jocs.2018.01.005.

Dongarra, Jack, Mark Gates, Azzam Haidar, Jakub Kurzak, Piotr Luszczek, Stanimire Tomov, and Ichitaro Yamazaki. 2018. “The Singular Value Decomposition: Anatomy of Optimizing an Algorithm for Extreme Scale.” SIAM Review 60 (4): 808–65. https://doi.org/10.1137/17m1117732.

Dong, Tingxing, Azzam Haidar, Stanimire Tomov, and Jack Dongarra. 2018. “Accelerating the SVD Bi-Diagonalization of a Batch of Small Matrices Using GPUs.” Journal of Computational Science 26 (May): 237–45. https://doi.org/10.1016/j.jocs.2018.01.007.

Anzt, Hartwig, Thomas K. Huckle, Jürgen Bräckle, and Jack Dongarra. 2018. “Incomplete Sparse Approximate Inverses for Parallel Preconditioning.” Parallel Computing 71 (January): 1–22. https://doi.org/10.1016/j.parco.2017.10.003.

Haidar, Azzam, Stanimire Tomov, Jack Dongarra, and Nicholas J. Higham. 2018. “Harnessing GPU Tensor Cores for Fast FP16 Arithmetic to Speed up Mixed-Precision Iterative Refinement Solvers.” SC18: International Conference for High Performance Computing, Networking, Storage and Analysis, November. https://doi.org/10.1109/sc.2018.00050.

Abdelfattah, Ahmad, Stanimire Tomov, and Jack Dongarra. 2019. “Progressive Optimization of Batched LU Factorization on GPUs.” 2019 IEEE High Performance Extreme Computing Conference (HPEC), September. https://doi.org/10.1109/hpec.2019.8916270.

Abdelfattah, Ahmad, Stanimire Tomov, and Jack Dongarra. 2019. “Towards Half-Precision Computation for Complex Matrices: A Case Study for Mixed Precision Solvers on GPUs.” 2019 IEEE/ACM 10th Workshop on Latest Advances in Scalable Algorithms for Large-Scale Systems (ScalA), November. https://doi.org/10.1109/scala49573.2019.00008.

Anzt, Hartwig, Yuhsiang M. Tsai, Ahmad Abdelfattah, Terry Cojean, and Jack Dongarra. 2020. “Evaluating the Performance of NVIDIA’s A100 Ampere GPU for Sparse and Batched Computations.” 2020 IEEE/ACM Performance Modeling, Benchmarking and Simulation of High Performance Computer Systems (PMBS), November. https://doi.org/10.1109/pmbs51919.2020.00009.

Beams, Natalie, Ahmad Abdelfattah, Stan Tomov, Jack Dongarra, Tzanio Kolev, and Yohann Dudouit. 2020. “High-Order Finite Element Method Using Standard and Device-Level Batch GEMM on GPUs.” 2020 IEEE/ACM 11th Workshop on Latest Advances in Scalable Algorithms for Large-Scale Systems (ScalA), November. https://doi.org/10.1109/scala51936.2020.00012.

Ozik, Jonathan, Nicholson Collier, Justin M. Wozniak, Charles Macal, Chase Cockrell, Samuel H. Friedman, Ahmadreza Ghaffarizadeh, Randy Heiland, Gary An, and Paul Macklin. 2018. “High-Throughput Cancer Hypothesis Testing with an Integrated PhysiCell-EMEWS Workflow.” BMC Bioinformatics 19 (S18). https://doi.org/10.1186/s12859-018-2510-x.

Gao, Shang, Michael T Young, John X Qiu, Hong-Jun Yoon, James B Christian, Paul A Fearn, Georgia D Tourassi, and Arvind Ramanthan. 2017. “Hierarchical Attention Networks for Information Extraction from Cancer Pathology Reports.” Journal of the American Medical Informatics Association 25 (3): 321–30. https://doi.org/10.1093/jamia/ocx131.

Bhattacharya, Tanmoy, Thomas Brettin, James H. Doroshow, Yvonne A. Evrard, Emily J. Greenspan, Amy L. Gryshuk, Thuc T. Hoang, et al. 2019. “AI Meets Exascale Computing: Advancing Cancer Research With Large-Scale High Performance Computing.” Frontiers in Oncology 9 (October). https://doi.org/10.3389/fonc.2019.00984.

Young, M. Todd, Jacob Hinkle, Arvind Ramanathan, and Ramakrishnan Kannan. 2018. “HyperSpace: Distributed Bayesian Hyperparameter Optimization.” 2018 30th International Symposium on Computer Architecture and High Performance Computing (SBAC-PAD), September. https://doi.org/10.1109/cahpc.2018.8645954.

Wozniak, Justin M., Hyunseung Yoo, Jamaludin Mohd-Yusof, Bogdan Nicolae, Nicholson Collier, Jonathan Ozik, Thomas Brettin, and Rick Stevens. 2020. “High-Bypass Learning: Automated Detection of Tumor Cells That Significantly Impact Drug Response.” 2020 IEEE/ACM Workshop on Machine Learning in High Performance Computing Environments (MLHPC) and Workshop on Artificial Intelligence and Machine Learning for Scientific Applications (AI4S), November. https://doi.org/10.1109/mlhpcai4s51975.2020.00012.

Yoon, Hong-Jun, Hilda B. Klasky, Eric B. Durbin, Xiao-Cheng Wu, Antoinette Stroup, Jennifer Doherty, Linda Coyle, et al. 2021. “Privacy-Preserving Knowledge Transfer with Bootstrap Aggregation of Teacher Ensembles.” Lecture Notes in Computer Science, 87–99. https://doi.org/10.1007/978-3-030-71055-2_9.

Li, Ang, Shuaiwen Leon Song, Jieyang Chen, Xu Liu, Nathan Tallent, and Kevin Barker. 2018. “Tartan: Evaluating Modern GPU Interconnect via a Multi-GPU Benchmark Suite.” 2018 IEEE International Symposium on Workload Characterization (IISWC), September. https://doi.org/10.1109/iiswc.2018.8573483.

Katz, Max P., Ann Almgren, Maria Barrios Sazo, Kiran Eiden, Kevin Gott, Alice Harpole, Jean M. Sexton, Don E. Willcox, Weiqun Zhang, and Michael Zingale. 2020. “Preparing Nuclear Astrophysics for Exascale.” SC20: International Conference for High Performance Computing, Networking, Storage and Analysis, November. https://doi.org/10.1109/sc41405.2020.00095.

Godoy, William F., Norbert Podhorszki, Ruonan Wang, Chuck Atkins, Greg Eisenhauer, Junmin Gu, Philip Davis, et al. 2020. “ADIOS 2: The Adaptable Input Output System. A Framework for High-Performance Data Management.” SoftwareX 12 (July): 100561. https://doi.org/10.1016/j.softx.2020.100561.

Mehraban, A., J. Thompson, J. Brown, R. Regueiro, V. Barra, and H. Tufo. 2021. “Simulating Compressible and Nearly-Incompressible Linear Elasticity Using an Efficient Parallel Scalable Matrix-Free High-Order Finite Element Method.” 14th WCCM-ECCOMAS Congress. https://doi.org/10.23967/wccm-eccomas.2020.302.

Maldonado, Daniel Adrian, Michel Schanen, François Pacaud, and Mihai Anitescu. 2021. “Domain Decomposition Preconditioners for Unstructured Network Problems in Parallel Vector Architectures.” 50th International Conference on Parallel Processing Workshop, August. https://doi.org/10.1145/3458744.3473363.

Zhou, Hui, Ken Raffenetti, Yanfei Guo, and Rajeev Thakur. 2022. “MPIX Stream: An Explicit Solution to Hybrid MPI+X Programming.” Proceedings of the 29th European MPI Users’ Group Meeting, September. https://doi.org/10.1145/3555819.3555820.

Zingale, M., M. P. Katz, A. Nonaka, and M. Rasmussen. 2022. “An Improved Method for Coupling Hydrodynamics with Astrophysical Reaction Networks.” The Astrophysical Journal 936 (1): 6. https://doi.org/10.3847/1538-4357/ac8478.

Rolchigo, Matt, Samuel Temple Reeve, Benjamin Stump, Gerald L. Knapp, John Coleman, Alex Plotkowski, and James Belak. 2022. “ExaCA: A Performance Portable Exascale Cellular Automata Application for Alloy Solidification Modeling.” Computational Materials Science 214 (November): 111692. https://doi.org/10.1016/j.commatsci.2022.111692.

Pacaud, François, Daniel Adrian Maldonado, Sungho Shin, Michel Schanen, and Mihai Anitescu. 2022. “A Feasible Reduced Space Method for Real-Time Optimal Power Flow.” Electric Power Systems Research 212 (November): 108268. https://doi.org/10.1016/j.epsr.2022.108268.

Montes de Oca Zapiain, David, Mitchell A. Wood, Nicholas Lubbers, Carlos Z. Pereyra, Aidan P. Thompson, and Danny Perez. 2022. “Training Data Selection for Accuracy and Transferability of Interatomic Potentials.” Npj Computational Materials 8 (1). https://doi.org/10.1038/s41524-022-00872-x.

Dutta, Soumya, Terece Turton, David Rogers, Jordan M. Musser, James Ahrens, and Ann S. Almgren. 2022. “In Situ Feature Analysis for Large-Scale Multiphase Flow Simulations.” Journal of Computational Science 63 (September): 101773. https://doi.org/10.1016/j.jocs.2022.101773.

Choi, Jaemin, Zane Fink, Sam White, Nitin Bhat, David F. Richards, and Laxmikant V. Kale. 2022. “Accelerating Communication for Parallel Programming Models on GPU Systems.” Parallel Computing 113 (October): 102969. https://doi.org/10.1016/j.parco.2022.102969.

Iwabuchi, Keita, Karim Youssef, Kaushik Velusamy, Maya Gokhale, and Roger Pearce. 2022. “Metall: A Persistent Memory Allocator for Data-Centric Analytics.” Parallel Computing 111 (July): 102905. https://doi.org/10.1016/j.parco.2022.102905.

Olson, M. Ben, Brandon Kammerdiener, Michael R. Jantz, Kshitij A. Doshi, and Terry Jones. 2022. “Online Application Guidance for Heterogeneous Memory Systems.” ACM Transactions on Architecture and Code Optimization 19 (3): 1–27. https://doi.org/10.1145/3533855.

Loe, Jennifer A., Christian A. Glusa, Ichitaro Yamazaki, Erik G. Boman, and Sivasankaran Rajamanickam. 2021. “Experimental Evaluation of Multiprecision Strategies for GMRES on GPUs.” 2021 IEEE International Parallel and Distributed Processing Symposium Workshops (IPDPSW), June. https://doi.org/10.1109/ipdpsw52791.2021.00078.

Liu, Yuanjian, Sheng Di, Kai Zhao, Sian Jin, Cheng Wang, Kyle Chard, Dingwen Tao, Ian Foster, and Franck Cappello. 2021. “Optimizing Multi-Range Based Error-Bounded Lossy Compression for Scientific Datasets.” 2021 IEEE 28th International Conference on High Performance Computing, Data, and Analytics (HiPC), December. https://doi.org/10.1109/hipc53243.2021.00036.

Liu, Jinyang, Sihuan Li, Sheng Di, Xin Liang, Kai Zhao, Dingwen Tao, Zizhong Chen, and Franck Cappello. 2021. “Improving Lossy Compression for SZ by Exploring the Best-Fit Lossless Compression Techniques.” 2021 IEEE International Conference on Big Data (Big Data), December. https://doi.org/10.1109/bigdata52589.2021.9671954.

Liu, Jinyang, Sheng Di, Kai Zhao, Sian Jin, Dingwen Tao, Xin Liang, Zizhong Chen, and Franck Cappello. 2021. “Exploring Autoencoder-Based Error-Bounded Compression for Scientific Data.” 2021 IEEE International Conference on Cluster Computing (CLUSTER), September. https://doi.org/10.1109/cluster48925.2021.00034.

Liu, Yuanjian, Sheng Di, Kai Zhao, Sian Jin, Cheng Wang, Kyle Chard, Dingwen Tao, Ian Foster, and Franck Cappello. 2021. “Understanding Effectiveness of Multi-Error-Bounded Lossy Compression for Preserving Ranges of Interest in Scientific Analysis.” 2021 7th International Workshop on Data Analysis and Reduction for Big Scientific Data (DRBSD-7), November. https://doi.org/10.1109/drbsd754563.2021.00010.

Liang, Xin, Qian Gong, Jieyang Chen, Ben Whitney, Lipeng Wan, Qing Liu, David Pugmire, Rick Archibald, Norbert Podhorszki, and Scott Klasky. 2021. “Error-Controlled, Progressive, and Adaptable Retrieval of Scientific Data with Multilevel Decomposition.” Proceedings of the International Conference for High Performance Computing, Networking, Storage and Analysis, November. https://doi.org/10.1145/3458817.3476179.

Li, Sihuan, Sheng Di, Kai Zhao, Xin Liang, Zizhong Chen, and Franck Cappello. 2021. “Resilient Error-Bounded Lossy Compressor for Data Transfer.” Proceedings of the International Conference for High Performance Computing, Networking, Storage and Analysis, November. https://doi.org/10.1145/3458817.3476195.

Lee, Sunwoo, Qiao Kang, Kewei Wang, Jan Balewski, Alex Sim, Ankit Agrawal, Alok Choudhary, Peter Nugent, Kesheng Wu, and Wei-keng Liao. 2021. “Asynchronous I/O Strategy for Large-Scale Deep Learning Applications.” 2021 IEEE 28th International Conference on High Performance Computing, Data, and Analytics (HiPC), December. https://doi.org/10.1109/hipc53243.2021.00046.

Kwack, JaeHyuk, John Tramm, Colleen Bertoni, Yasaman Ghadar, Brian Homerding, Esteban Rangel, Christopher Knight, and Scott Parker. 2021. “Evaluation of Performance Portability of Applications and Mini-Apps across AMD, Intel and NVIDIA GPUs.” 2021 International Workshop on Performance, Portability and Productivity in HPC (P3HPC), November. https://doi.org/10.1109/p3hpc54578.2021.00008.

Kruse, Michael. 2021. “Loop Transformations Using Clang’s Abstract Syntax Tree.” 50th International Conference on Parallel Processing Workshop, August. https://doi.org/10.1145/3458744.3473359.

Krasowska, David, Julie Bessac, Robert Underwood, Jon C. Calhoun, Sheng Di, and Franck Cappello. 2021. “Exploring Lossy Compressibility through Statistical Correlations of Scientific Datasets.” 2021 7th International Workshop on Data Analysis and Reduction for Big Scientific Data (DRBSD-7), November. https://doi.org/10.1109/drbsd754563.2021.00011.

Koo, Jaehoon, Prasanna Balaprakash, Michael Kruse, Xingfu Wu, Paul Hovland, and Mary Hall. 2021. “Customized Monte Carlo Tree Search for LLVM/Polly’s Composable Loop Optimization Transformations.” 2021 International Workshop on Performance Modeling, Benchmarking and Simulation of High Performance Computer Systems (PMBS), November. https://doi.org/10.1109/pmbs54543.2021.00015.

Kang, Qiao, Scot Breitenfeld, Kaiyuan Hou, Wei-keng Liao, Robert Ross, and Suren Byna. 2021. “Optimizing Performance of Parallel I/O Accesses to Non-Contiguous Blocks in Multiple Array Variables.” 2021 IEEE International Conference on Big Data (Big Data), December. https://doi.org/10.1109/bigdata52589.2021.9671638.

Kamil, Amir, and Dan Bonachea. 2021. “Optimization of Asynchronous Communication Operations through Eager Notifications.” 2021 SC Workshops Supplementary Proceedings (SCWS), November. https://doi.org/10.1109/scws55283.2021.00014.

Jayatilaka, Tarindu, Hideto Ueno, Giorgis Georgakoudis, EunJung Park, and Johannes Doerfert. 2021. “Towards Compile-Time-Reducing Compiler Optimization Selection via Machine Learning.” 50th International Conference on Parallel Processing Workshop, August. https://doi.org/10.1145/3458744.3473355.

Hussain, Md Taufique, Oguz Selvitopi, Aydin Buluc, and Ariful Azad. 2021. “Communication-Avoiding and Memory-Constrained Sparse Matrix-Matrix Multiplication at Extreme Scale.” 2021 IEEE International Parallel and Distributed Processing Symposium (IPDPS), May. https://doi.org/10.1109/ipdps49936.2021.00018.

Huckelheim, Jan, and Johannes Doerfert. 2021. “Spray: Sparse Reductions of Arrays in OPENMP.” 2021 IEEE International Parallel and Distributed Processing Symposium (IPDPS), May. https://doi.org/10.1109/ipdps49936.2021.00056.

Huber, Joseph, Weile Wei, Giorgis Georgakoudis, Johannes Doerfert, and Oscar Hernandez. 2021. “A Case Study of LLVM-Based Analysis for Optimizing SIMD Code Generation.” Lecture Notes in Computer Science, 142–55. https://doi.org/10.1007/978-3-030-85262-7_10.

Huang, Xuan, Pavol Klacansky, Steve Petruzza, Attila Gyulassy, Peer-Timo Bremer, and Valerio Pascucci. 2021. “Distributed Merge Forest.” Proceedings of the ACM International Conference on Supercomputing, June. https://doi.org/10.1145/3447818.3460358.

Holmes, Daniel J., Anthony Skjellum, Julien Jaeger, Ryan E. Grant, Purushotham V. Bangalore, Matthew G.F. Dosanjh, Amanda Bienz, and Derek Schafer. 2021. “Partitioned Collective Communication.” 2021 Workshop on Exascale MPI (ExaMPI), November. https://doi.org/10.1109/exampi54564.2021.00007.

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Herault, Thomas, Yves Robert, George Bosilca, Robert J. Harrison, Cannada A. Lewis, Edward F. Valeev, and Jack J. Dongarra. 2021. “Distributed-Memory Multi-GPU Block-Sparse Tensor Contraction for Electronic Structure.” 2021 IEEE International Parallel and Distributed Processing Symposium (IPDPS), May. https://doi.org/10.1109/ipdps49936.2021.00062.

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Chen, Serena H., M. Todd Young, John Gounley, Christopher Stanley, and Debsindhu Bhowmik. 2021. “How Distinct Structural Flexibility within SARS-CoV-2 Spike Protein Reveals Potential Therapeutic Targets.” 2021 IEEE International Conference on Big Data (Big Data), December. https://doi.org/10.1109/bigdata52589.2021.9671323.

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Cao, Qinglei, Yu Pei, Kadir Akbudak, George Bosilca, Hatem Ltaief, David Keyes, and Jack Dongarra. 2021. “Leveraging PaRSEC Runtime Support to Tackle Challenging 3D Data-Sparse Matrix Problems.” 2021 IEEE International Parallel and Distributed Processing Symposium (IPDPS), May. https://doi.org/10.1109/ipdps49936.2021.00017.

Brunhart-Lupo, Nicholas, Shashank Yellapantula, Kenny Gruchalla, and Ray Grout. 2021. “Visualization of Jet Impingement and Ignition in a Piston-Cylinder Chamber.” Proceedings of the Twelfth ACM International Conference on Future Energy Systems, June. https://doi.org/10.1145/3447555.3466595.

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Bosilca, George, Aurelien Bouteiller, Thomas Herault, Valentin Le Fevre, Yves Robert, and Jack Dongarra. 2021. “Revisiting Credit Distribution Algorithms for Distributed Termination Detection.” 2021 IEEE International Parallel and Distributed Processing Symposium Workshops (IPDPSW), June. https://doi.org/10.1109/ipdpsw52791.2021.00095.

Barca, Giuseppe M. J., Jorge L. Galvez Vallejo, David L. Poole, Melisa Alkan, Ryan Stocks, Alistair P. Rendell, and Mark S. Gordon. 2021. “Enabling Large-Scale Correlated Electronic Structure Calculations.” Proceedings of the International Conference for High Performance Computing, Networking, Storage and Analysis, November. https://doi.org/10.1145/3458817.3476222.

Bak, Seonmyeong, Oscar Hernandez, Mark Gates, Piotr Luszczek, and Vivek Sarkar. 2021. “Task-Graph Scheduling Extensions for Efficient Synchronization and Communication.” Proceedings of the ACM International Conference on Supercomputing, June. https://doi.org/10.1145/3447818.3461616.

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Ayachit, Utkarsh, Andrew C. Bauer, Ben Boeckel, Berk Geveci, Kenneth Moreland, Patrick O’Leary, and Tom Osika. 2021. “Catalyst Revised: Rethinking the ParaView in Situ Analysis and Visualization API.” High Performance Computing, 484–94. https://doi.org/10.1007/978-3-030-90539-2_33.

Awan, Muaaz Gul, Steven Hofmeyr, Rob Egan, Nan Ding, Aydin Buluc, Jack Deslippe, Leonid Oliker, and Katherine Yelick. 2021. “Accelerating Large Scale de Novo Metagenome Assembly Using GPUs.” Proceedings of the International Conference for High Performance Computing, Networking, Storage and Analysis, November. https://doi.org/10.1145/3458817.3476212.

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Aggarwal, Isha, Aditya Kashi, Pratik Nayak, Cody J. Balos, Carol S. Woodward, and Hartwig Anzt. 2021. “Batched Sparse Iterative Solvers for Computational Chemistry Simulations on GPUs.” 2021 12th Workshop on Latest Advances in Scalable Algorithms for Large-Scale Systems (ScalA), November. https://doi.org/10.1109/scala54577.2021.00010.

Abhyankar, Shrirang, Slaven Peles, Robert Rutherford, and Asher Mancinelli. 2021. “Evaluation of AC Optimal Power Flow on Graphical Processing Units.” 2021 IEEE Power & Energy Society General Meeting (PESGM), July. https://doi.org/10.1109/pesgm46819.2021.9638131.

Penchoff, Deborah A., Edward Valeev, Heike Jagode, Piotr Luszczek, Anthony Danalis, George Bosilca, Robert J. Harrison, Jack Dongarra, and Theresa L. Windus. 2021. “An Introduction to High Performance Computing and Its Intersection with Advances in Modeling Rare Earth Elements and Actinides.” ACS Symposium Series, October, 3–53. https://doi.org/10.1021/bk-2021-1388.ch001.

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Oyama, Yosuke, Naoya Maruyama, Nikoli Dryden, Erin Mccarthy, Peter Harrington, Jan Balewski, Satoshi Matsuoka, Peter Nugent, and Brian Van Essen. 2021. “The Case for Strong Scaling in Deep Learning: Training Large 3D CNNs with Hybrid Parallelism.” IEEE Transactions on Parallel and Distributed Systems, 1–1. https://doi.org/10.1109/tpds.2020.3047974.

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Gao, Shang, Mohammed Alawad, M. Todd Young, John Gounley, Noah Schaefferkoetter, Hong Jun Yoon, Xiao-Cheng Wu, et al. 2021. “Limitations of Transformers on Clinical Text Classification.” IEEE Journal of Biomedical and Health Informatics 25 (9): 3596–3607. https://doi.org/10.1109/jbhi.2021.3062322.

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Austin, Anthony P., Noel Chalmers, and Tim Warburton. 2021. “Initial Guesses for Sequences of Linear Systems in a GPU-Accelerated Incompressible Flow Solver.” SIAM Journal on Scientific Computing 43 (4): C259–89. https://doi.org/10.1137/20m1368677.

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Yu, Xiaodong, Sheng Di, Kai Zhao, Jiannan Tian, Dingwen Tao, Xin Liang, and Franck Cappello. 2022. “Ultrafast Error-Bounded Lossy Compression for Scientific Datasets.” Proceedings of the 31st International Symposium on High-Performance Parallel and Distributed Computing, June. https://doi.org/10.1145/3502181.3531473.

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Raybourn, Elaine M. 2022. “Strategies for Working Remotely: Responding to Pandemic-Driven Change with Cross-Organizational Community Dialog.” Lecture Notes in Computer Science, 407–16. https://doi.org/10.1007/978-3-031-05544-7_30.

Patel, Atmn, and Johannes Doerfert. 2022. “Remote OpenMP Offloading.” High Performance Computing, 315–33. https://doi.org/10.1007/978-3-031-07312-0_16.

O’Neal, Jared, Mohamed Wahib, Anshu Dubey, Klaus Weide, Tom Klosterman, and Johann Rudi. 2022. “Domain-Specific Runtime to Orchestrate Computation on Heterogeneous Platforms.” Lecture Notes in Computer Science, 154–65. https://doi.org/10.1007/978-3-031-06156-1_13.

Huber, Joseph, Melanie Cornelius, Giorgis Georgakoudis, Shilei Tian, Jose M Monsalve Diaz, Kuter Dinel, Barbara Chapman, and Johannes Doerfert. 2022. “Efficient Execution of OpenMP on GPUs.” 2022 IEEE/ACM International Symposium on Code Generation and Optimization (CGO), April. https://doi.org/10.1109/cgo53902.2022.9741290.

Donaghy, John, and Kai Germaschewski. 2022. “Inference and De-Noising of Non-Gaussian Particle Distribution Functions: A Generative Modeling Approach.” Lecture Notes in Computer Science, 338–48. https://doi.org/10.1007/978-3-030-95467-3_25.

Denoyelle, Nicolas, Swann Perarnau, Kamil Iskra, and Balazs Gerofi. 2022. “Rapid Execution Time Estimation for Heterogeneous Memory Systems Through Differential Tracing.” High Performance Computing, 256–74. https://doi.org/10.1007/978-3-031-07312-0_13.

Cai, Qiheng, Junyi Cheng, Yang Chen, Marcus Wagner, Christopher Daley, Dossay Oryspayev, Stefan Tirkas, Sophie Redd, and Scott Parker. 2022. “GPU Offloading of a Large-Scale Gyrokinetic Particle-in-Cell Fortran Code on Summit: From OpenACC to OpenMP.” Lecture Notes in Computer Science, 133–48. https://doi.org/10.1007/978-3-030-97759-7_7.

Bez, Jean Luca, Ahmad Maroof Karimi, Arnab K. Paul, Bing Xie, Suren Byna, Philip Carns, Sarp Oral, Feiyi Wang, and Jesse Hanley. 2022. “Access Patterns and Performance Behaviors of Multi-Layer Supercomputer I/O Subsystems under Production Load.” Proceedings of the 31st International Symposium on High-Performance Parallel and Distributed Computing, June. https://doi.org/10.1145/3502181.3531461.

Anderson, Jonathon, Yumeng Liu, and John Mellor-Crummey. 2022. “Preparing for Performance Analysis at Exascale.” Proceedings of the 36th ACM International Conference on Supercomputing, June. https://doi.org/10.1145/3524059.3532397.

Aliaga, José I., Hartwig Anzt, Thomas Grützmacher, Enrique S. Quintana‐Ortí, and Andrés E. Tomás. 2021. “Compression and Load Balancing for Efficient Sparse Matrix‐vector Product on Multicore Processors and Graphics Processing Units.” Concurrency and Computation: Practice and Experience 34 (14). https://doi.org/10.1002/cpe.6515.

Sane, Sudhanshu, and Hank Childs. 2022. “Exploratory Time-Dependent Flow Visualization via In Situ Extracted Lagrangian Representations.” In Situ Visualization for Computational Science, 91–109. https://doi.org/10.1007/978-3-030-81627-8_5.

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Zhang, Qian, Hang Deng, Yanhui Dong, Sergi Molins, Xiao Li, and Carl Steefel. 2022. “Investigation of Coupled Processes in Fractures and the Bordering Matrix via a Micro‐Continuum Reactive Transport Model.” Water Resources Research 58 (2). https://doi.org/10.1029/2021wr030578.

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Lin, Guangxing, Christopher R. Jones, L. Ruby Leung, Zhe Feng, and Mikhail Ovchinnikov. 2021. “Mesoscale Convective Systems in a Superparameterized E3SM Simulation at High Resolution.” Journal of Advances in Modeling Earth Systems 14 (1). https://doi.org/10.1029/2021ms002660.

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Bernholdt, David, Swen Boehm, George Bosilca, Manjunath Gorentla Venkata, Ryan Grant, Thomas Naughton, III, Howard Pritchard, Martin Schulz, and Geoffroy Vallee. 2018. “A Survey of MPI Usage in the U.S. Exascale Computing Project.” Office of Scientific and Technical Information (OSTI). https://doi.org/10.2172/1462877.

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Rodgers, Arthur J., Arben Pitarka, and David B. McCallen. 2019. “The Effect of Fault Geometry and Minimum Shear Wavespeed on 3D Ground-Motion Simulations for an Mw 6.5 Hayward Fault Scenario Earthquake, San Francisco Bay Area, Northern California.” Bulletin of the Seismological Society of America 109 (4): 1265–81. https://doi.org/10.1785/0120180290.

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Wang, Xinlei, Yuxing Qiu, Stuart R. Slattery, Yu Fang, Minchen Li, Song-Chun Zhu, Yixin Zhu, Min Tang, Dinesh Manocha, and Chenfanfu Jiang. 2020. “A Massively Parallel and Scalable Multi-GPU Material Point Method.” ACM Transactions on Graphics 39 (4). https://doi.org/10.1145/3386569.3392442.

Abdelfattah, Ahmad, Stanimire Tomov, and Jack Dongarra. 2020. “Matrix Multiplication on Batches of Small Matrices in Half and Half-Complex Precisions.” Journal of Parallel and Distributed Computing 145 (November): 188–201. https://doi.org/10.1016/j.jpdc.2020.07.001.

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