Computer Science Research Institute Summer Proceedings 2024

Marissa B. P. Adams, Tiernan A. Casey and Bryan W. Reuter, editors, Computer Science Research Institute Summer Proceedings 2024, The Computer Science Research Institute at Sandia National Laboratories, Albuquerque, NM and Livermore, CA, 2024. Available as Sandia National Laboratories Technical Report SAND2024-16688O.

Individual Articles

• G. H. Brown, E. T. Phipps, H. Kolla, D. L. Bull, and T. S. Ehrmann, Extracting Climate Phenomena: Beyond PCA, in Computer Science Research Institute Summer Proceedings 2024, M. B. P. Adams, T. A. Casey, and B. W. Reuter, eds., Technical Report SAND2024-16688O, Sandia National Laboratories, 2024, pp. 2–13.
• A. de Castro and P. Kuberry, Comparing Stability of Partitioned Heterogeneous Time-Integration Methods Involving Index-2 DAEs Resulting from High-Order Adams-Moulton and Backward Difference Formula Time Integration Schemes, in Computer Science Research Institute Summer Proceedings 2024, M. B. P. Adams, T. A. Casey, and B. W. Reuter, eds., Technical Report SAND2024-16688O, Sandia National Laboratories, 2024, pp. 14–25.
• A. Chin and T. Catanach, Backwards Sequential Monte Carlo for Efficient Bayesian Optimal Experimental Design, in Computer Science Research Institute Summer Proceedings 2024, M. B. P. Adams, T. A. Casey, and B. W. Reuter, eds., Technical Report SAND2024-16688O, Sandia National Laboratories, 2024, pp. 26–37.
• E. Crislip, M. Khalil, and K. Neal, Data Assimilation: Addressing Spurious Correlations and Scalability Issues, in Computer Science Research Institute Summer Proceedings 2024, M. B. P. Adams, T. A. Casey, and B. W. Reuter, eds., Technical Report SAND2024-16688O, Sandia National Laboratories, 2024, pp. 38–49.
• M. Drayton, R. Bandy, and T. Portone, Uncertainty in Reduced Finite-Rate Ablation Models for Reentry Vehicles, in Computer Science Research Institute Summer Proceedings 2024, M. B. P. Adams, T. A. Casey, and B. W. Reuter, eds., Technical Report SAND2024-16688O, Sandia National Laboratories, 2024, pp. 50–57.
• R. de Farias, M. B. P. Adams, and W. J. Rider, Implications of the Two Interacting Blast Wave Verification Problem for Computational Shock Hydrodynamics, in Computer Science Research Institute Summer Proceedings 2024, M. B. P. Adams, T. A. Casey, and B. W. Reuter, eds., Technical Report SAND2024-16688O, Sandia National Laboratories, 2024, pp. 58–66.
• D. Hughes, C. Eldred, and E. C. Cyr, Discrete Exterior Calculus for Hodge-Helmholtz Problem, in Computer Science Research Institute Summer Proceedings 2024, M. B. P. Adams, T. A. Casey, and B. W. Reuter, eds., Technical Report SAND2024-16688O, Sandia National Laboratories, 2024, pp. 67–78.
• E. Huynh, P. Bochev, and P. Kuberry, A DMD-Based Partitioned Scheme for Time-Dependent Coupled Parametric PDEs, in Computer Science Research Institute Summer Proceedings 2024, M. B. P. Adams, T. A. Casey, and B. W. Reuter, eds., Technical Report SAND2024-16688O, Sandia National Laboratories, 2024, pp. 79–97.
• L. F. Maia, R. Baraldi, and D. P. Kouri, An Inexact Weighted Proximal Trust-Region Method, in Computer Science Research Institute Summer Proceedings 2024, M. B. P. Adams, T. A. Casey, and B. W. Reuter, eds., Technical Report SAND2024-16688O, Sandia National Laboratories, 2024, pp. 98–108.
• I. Moore, C. R. Wentland, A. Gruber, and I. Tezaur, Domain Decomposition-Based Coupling of Operator Inference Reduced Order Models via the Schwarz Alternating Method, in Computer Science Research Institute Summer Proceedings 2024, M. B. P. Adams, T. A. Casey, and B. W. Reuter, eds., Technical Report SAND2024-16688O, Sandia National Laboratories, 2024, pp. 109–126.
• R. Pawar and P. Bochev, Operator Inference Based Flux Surrogate Algorithm for Coupled Transmission Problems, in Computer Science Research Institute Summer Proceedings 2024, M. B. P. Adams, T. A. Casey, and B. W. Reuter, eds., Technical Report SAND2024-16688O, Sandia National Laboratories, 2024, pp. 127–143.
• B. Shawcroft, K. M. Shephard, and S. A. Mitchell, TUSQH: Topological Control of Volume-Fraction Meshes Near Small Features and Ugly Geometry, in Computer Science Research Institute Summer Proceedings 2024, M. B. P. Adams, T. A. Casey, and B. W. Reuter, eds., Technical Report SAND2024-16688O, Sandia National Laboratories, 2024, pp. 144–157.
• M. A. Tunnell and E. G. Boman, Parallel Incomplete LU Factorizations Based on Alternating Triangular Solves, in Computer Science Research Institute Summer Proceedings 2024, M. B. P. Adams, T. A. Casey, and B. W. Reuter, eds., Technical Report SAND2024-16688O, Sandia National Laboratories, 2024, pp. 158–171.
• A. Vijaywargiya, S. A. McQuarrie, and A. Gruber, Tensor Parametric Operator Inference with Hamiltonian Structure, in Computer Science Research Institute Summer Proceedings 2024, M. B. P. Adams, T. A. Casey, and B. W. Reuter, eds., Technical Report SAND2024-16688O, Sandia National Laboratories, 2024, pp. 172–194.
• E. Whitesides, J. P. Mendez, J. Ivie, X. Gao, and S. Misra, Simulating Atomic Precision Advanced Manufacturing (APAM) Enhanced BJT, in Computer Science Research Institute Summer Proceedings 2024, M. B. P. Adams, T. A. Casey, and B. W. Reuter, eds., Technical Report SAND2024-16688O, Sandia National Laboratories, 2024, pp. 195–202.
• A. Alvey-Blanco, K. Liegeois, and B. Kelley, Toward Automatic Kernel Fusion for Kokkos Using MLIR, in Computer Science Research Institute Summer Proceedings 2024, M. B. P. Adams, T. A. Casey, and B. W. Reuter, eds., Technical Report SAND2024-16688O, Sandia National Laboratories, 2024, pp. 204–215.
• C. N. Avans, J. Ciesko, C. Pearson, E. D. Suggs, S. L. Olivier, and A. Skjellum, Performance Insights into Supporting Kokkos Views in the Kokkos Comm MPI Library, in Computer Science Research Institute Summer Proceedings 2024, M. B. P. Adams, T. A. Casey, and B. W. Reuter, eds., Technical Report SAND2024-16688O, Sandia National Laboratories, 2024, pp. 216–222.
• N. Bacon, S. Levy, P. Bridges, and K. B. Ferreira, Analysis of Modern Tools for Communication Impacts, in Computer Science Research Institute Summer Proceedings 2024, M. B. P. Adams, T. A. Casey, and B. W. Reuter, eds., Technical Report SAND2024-16688O, Sandia National Laboratories, 2024, pp. 223–231.
• A. Epperly, K. Thompson, and O. Parekh, Sum of Squares Bounds on the Performance of the Quantum Approximate Optimization Algorithm, in Computer Science Research Institute Summer Proceedings 2024, M. B. P. Adams, T. A. Casey, and B. W. Reuter, eds., Technical Report SAND2024-16688O, Sandia National Laboratories, 2024, pp. 232–240.
• A. Krishna and R. Milewicz, Experience Report on Observability and its Effect on Security and Usability in Software Systems, in Computer Science Research Institute Summer Proceedings 2024, M. B. P. Adams, T. A. Casey, and B. W. Reuter, eds., Technical Report SAND2024-16688O, Sandia National Laboratories, 2024, pp. 241–248.
• C. O’Neil, M. D. Porter, and S. K. Seritan, Analyzing Qubit-Runtime Tradeoffs in Parallelizing Unary Iteration, in Computer Science Research Institute Summer Proceedings 2024, M. B. P. Adams, T. A. Casey, and B. W. Reuter, eds., Technical Report SAND2024-16688O, Sandia National Laboratories, 2024, pp. 249–259.
• J. Shawger and M. L. Curry, Storage System Characterization in Virtualized Testbed, in Computer Science Research Institute Summer Proceedings 2024, M. B. P. Adams, T. A. Casey, and B. W. Reuter, eds., Technical Report SAND2024-16688O, Sandia National Laboratories, 2024, pp. 260–269.
• N. D. Siekierski, A. Q. Wilber-Gauthier, and S. K. Seritan, Scalable Application-Oriented Benchmarking of Quantum Computers, in Computer Science Research Institute Summer Proceedings 2024, M. B. P. Adams, T. A. Casey, and B. W. Reuter, eds., Technical Report SAND2024-16688O, Sandia National Laboratories, 2024, pp. 270–276.
• H. Bayat, M. A. Cusentino, and J. M. Goff, Charge Dependent Machine Learned Models for Atomistic Simulations of Divertor Materials, in Computer Science Research Institute Summer Proceedings 2024, M. B. P. Adams, T. A. Casey, and B. W. Reuter, eds., Technical Report SAND2024-16688O, Sandia National Laboratories, 2024, pp. 278–287.
• A. K. Boahen and W. L. Davis IV, In Situ Machine Learning for Intelligent Data Capture and Event Detection, in Computer Science Research Institute Summer Proceedings 2024, M. B. P. Adams, T. A. Casey, and B. W. Reuter, eds., Technical Report SAND2024-16688O, Sandia National Laboratories, 2024, pp. 288–297.
• M. C. Gaitan-Cardenas, C. M. Siefert, and S. W. Tsai, Large Language Model Accuracy on Post-Processed AI-Generated Code, in Computer Science Research Institute Summer Proceedings 2024, M. B. P. Adams, T. A. Casey, and B. W. Reuter, eds., Technical Report SAND2024-16688O, Sandia National Laboratories, 2024, pp. 298–309.
• D. Deighan, J. Actor, and R. Patel, Mixture of Neural Operator Experts for Nontrivial Boundary Conditions and Model Selection, in Computer Science Research Institute Summer Proceedings 2024, M. B. P. Adams, T. A. Casey, and B. W. Reuter, eds., Technical Report SAND2024-16688O, Sandia National Laboratories, 2024, pp. 310–323.
• A. Feeney and S. Rajamanickam, Exploring Machine Learning Surrogates for Molecular Dynamics Simulations, in Computer Science Research Institute Summer Proceedings 2024, M. B. P. Adams, T. A. Casey, and B. W. Reuter, eds., Technical Report SAND2024-16688O, Sandia National Laboratories, 2024, pp. 324–330.
• I. Furrick, M. Wood, and A. Hensley, Designing a Machine-Learned Interatomic Potential for Gold-Promoted Nickel catalysts Utilizing Magnetic Training Data, in Computer Science Research Institute Summer Proceedings 2024, M. B. P. Adams, T. A. Casey, and B. W. Reuter, eds., Technical Report SAND2024-16688O, Sandia National Laboratories, 2024, pp. 331–345.
• M. Gahl, G. W. Chapman, S. Agarwal, F. S. Chance, Event Detection Using Neural Networks Robust to Statistically Similar Distractors, in Computer Science Research Institute Summer Proceedings 2024, M. B. P. Adams, T. A. Casey, and B. W. Reuter, eds., Technical Report SAND2024-16688O, Sandia National Laboratories, 2024, pp. 346–359.
• J. D. Gonzales-Pasion, M. Wood, and A. J. Hensley, Machine Learned Interatomic Potential Development Accelerated via Large-Language Models for Nickel-Gold, in Computer Science Research Institute Summer Proceedings 2024, M. B. P. Adams, T. A. Casey, and B. W. Reuter, eds., Technical Report SAND2024-16688O, Sandia National Laboratories, 2024, pp. 360–369.
• Q. M. Mason and K. Maupin, Decision Tree Machine Learning Model Construction for Particle Simulation, in Computer Science Research Institute Summer Proceedings 2024, M. B. P. Adams, T. A. Casey, and B. W. Reuter, eds., Technical Report SAND2024-16688O, Sandia National Laboratories, 2024, pp. 370–375.
• C. Mullen, E. Salas, J. Goff, Breaking Bad Structure Generation: Methods for Systematic Data-Driven Atomistic Structures for ML Model Training, in Computer Science Research Institute Summer Proceedings 2024, M. B. P. Adams, T. A. Casey, and B. W. Reuter, eds., Technical Report SAND2024-16688O, Sandia National Laboratories, 2024, pp. 376–386.
• P. Mutia and J. Davis, Ollama-Assisted Function Calls in Leap, in Computer Science Research Institute Summer Proceedings 2024, M. B. P. Adams, T. A. Casey, and B. W. Reuter, eds., Technical Report SAND2024-16688O, Sandia National Laboratories, 2024, pp. 387–393.
• K. A. Ohene-Obeng and K. Maupin, Scientific Machine Learning for Surrogate Modeling, in Computer Science Research Institute Summer Proceedings 2024, M. B. P. Adams, T. A. Casey, and B. W. Reuter, eds., Technical Report SAND2024-16688O, Sandia National Laboratories, 2024, pp. 394–408.
• J. C. Páez and R. G. Patel, Quantifying Aleatoric Uncertainty in Operator Learning Using Generative Networks, in Computer Science Research Institute Summer Proceedings 2024, M. B. P. Adams, T. A. Casey, and B. W. Reuter, eds., Technical Report SAND2024-16688O, Sandia National Laboratories, 2024, pp. 409–414.
• D. Rodriguez and M. Perego, Coupled Deep Neural Operators as a Surrogate Model for Ice-Sheet Dynamics, in Computer Science Research Institute Summer Proceedings 2024, M. B. P. Adams, T. A. Casey, and B. W. Reuter, eds., Technical Report SAND2024-16688O, Sandia National Laboratories, 2024, pp. 415–428.