Computer Science Research Institute Summer Proceedings 2023

Stefan K. Seritan and Bryan W. Reuter, editors, Computer Science Research Institute Summer Proceedings 2023, The Computer Science Research Institute at Sandia National Laboratories, Albuquerque, NM and Livermore, CA, 2023. Available as Sandia National Laboratories Technical Report SAND2023-13916R.

Individual Articles

• E. Agyei-Kodie and G. Harper, Clustering and Structure-Detecting R-Adaptivity for Extreme-Scale Finite Element Simulations, in Computer Science Research Institute Summer Proceedings 2023, S.K. Seritan and B.W. Reuter, eds., Technical Report SAND2023-13916R, Sandia National Laboratories, 2023, pp. 2–15.
• R. Bandy, M. Sands, and T. Portone, Quantifying Uncertainties in Ablation Models for Hypersonic Flight Simulation, in Computer Science Research Institute Summer Proceedings 2023, S.K. Seritan and B.W. Reuter, eds., Technical Report SAND2023-13916R, Sandia National Laboratories, 2023, pp. 16–29.
• M. Chiwere, P.A. Bosler, and G.B. Wright, Fluid Dynamics on a Rotating Sphere with Double Fourier Series and Lagrangian Advections, in Computer Science Research Institute Summer Proceedings 2023, S.K. Seritan and B.W. Reuter, eds., Technical Report SAND2023-13916R, Sandia National Laboratories, 2023, pp. 30–41.
• N. Etienne, G. Harper, and C. Siefert, Enhancing Linear Solvers Through Advanced Matrix Clustering Techniques, in Computer Science Research Institute Summer Proceedings 2023, S.K. Seritan and B.W. Reuter, eds., Technical Report SAND2023-13916R, Sandia National Laboratories, 2023, pp. 42–53.
• E. Hawkins, P. Bochev, and P. Kuberry, An Optimization-Based Approach for Coupling Projection-Based Reduced Order Models, in Computer Science Research Institute Summer Proceedings 2023, S.K. Seritan and B.W. Reuter, eds., Technical Report SAND2023-13916R, Sandia National Laboratories, 2023, pp. 54–69.
• A.J. Higgins, E.G. Boman, D.B. Szyld, and I. Yamazaki, Randomized Householder-Cholesky QR Factorization with Multi-Sketching, in Computer Science Research Institute Summer Proceedings 2023, S.K. Seritan and B.W. Reuter, eds., Technical Report SAND2023-13916R, Sandia National Laboratories, 2023, pp. 70–78.
• N. Neuberger, B.G. van Bloemen Waanders, and A. Alexanderian, Computational Aspects of Optimal Experiment Design for Large-Scale Bayesian Linear Inverse Problems, in Computer Science Research Institute Summer Proceedings 2023, S.K. Seritan and B.W. Reuter, eds., Technical Report SAND2023-13916R, Sandia National Laboratories, 2023, pp. 79–93.
• H. Rosso, T. Portone, and R. White, Grouped Sensitivity Analysis for Geologic Disposal Safety Assessment, in Computer Science Research Institute Summer Proceedings 2023, S.K. Seritan and B.W. Reuter, eds., Technical Report SAND2023-13916R, Sandia National Laboratories, 2023, pp. 94–108.
• D. Sharp and B.G. van Bloemen Waanders, Magnetohydrodynamics: Formulation, Optimization, and Uncertainty Quantification, in Computer Science Research Institute Summer Proceedings 2023, S.K. Seritan and B.W. Reuter, eds., Technical Report SAND2023-13916R, Sandia National Laboratories, 2023, pp. 109–120.
• H. Switzer, J. Loe, and E.G. Boman, Implementing a Randomized Eigensolver in Anasazi and Its Application to Spectral Graph Partitioning, in Computer Science Research Institute Summer Proceedings 2023, S.K. Seritan and B.W. Reuter, eds., Technical Report SAND2023-13916R, Sandia National Laboratories, 2023, pp. 121–134.
• A. Voronin, R.S. Tuminaro, L.N. Olson, and S. MacLachlan, Adaptive Relaxation Methods Based on Patch Reuse for Evolving Linear Systems, in Computer Science Research Institute Summer Proceedings 2023, S.K. Seritan and B.W. Reuter, eds., Technical Report SAND2023-13916R, Sandia National Laboratories, 2023, pp. 135–146.
• S. Angelo Toribio, R. Milewicz, J. Teves, J. Willenbring, and J. Frye, Experience Report on Additional Features to ECMF Back-End Pipeline and Environment Container Build Program, in Computer Science Research Institute Summer Proceedings 2023, S.K. Seritan and B.W. Reuter, eds., Technical Report SAND2023-13916R, Sandia National Laboratories, 2023, pp. 148–157.
• L. Cooper and K. Pedretti, Optimization of Sparse Matrix-Vector Multiplication on a RISC-V GPU, in Computer Science Research Institute Summer Proceedings 2023, S.K. Seritan and B.W. Reuter, eds., Technical Report SAND2023-13916R, Sandia National Laboratories, 2023, pp. 158–163.
• G. Dube and K. Pedretti, Evaluating RISC-V SIMD Vector “V” Extension Support with Chipyard and FireSim, in Computer Science Research Institute Summer Proceedings 2023, S.K. Seritan and B.W. Reuter, eds., Technical Report SAND2023-13916R, Sandia National Laboratories, 2023, pp. 164–171.
• S. Grayson and R. Milewicz, Evaluating System-Level Provenance Tools for Practical Use, in Computer Science Research Institute Summer Proceedings 2023, S.K. Seritan and B.W. Reuter, eds., Technical Report SAND2023-13916R, Sandia National Laboratories, 2023, pp. 172–181.
• B. Holman, J. Kallaugher, and O. Parekh, The Space-Constrained Quantum Query Complexity of Boolean Functions, in Computer Science Research Institute Summer Proceedings 2023, S.K. Seritan and B.W. Reuter, eds., Technical Report SAND2023-13916R, Sandia National Laboratories, 2023, pp. 182–192.
• A. Johansson and S. Moore, Performance Portable Rigid Body Dynamics, in Computer Science Research Institute Summer Proceedings 2023, S.K. Seritan and B.W. Reuter, eds., Technical Report SAND2023-13916R, Sandia National Laboratories, 2023, pp. 193–201.
• A. Khan, B. Kelley, K. Liegeois, and S. Rajamanickam, Generating Kokkos Code from Sparse Tensor Algebra in Python using MLIR, in Computer Science Research Institute Summer Proceedings 2023, S.K. Seritan and B.W. Reuter, eds., Technical Report SAND2023-13916R, Sandia National Laboratories, 2023, pp. 202–209.
• D. Mishler, J. Ciesko, S. Olivier, and G. Bosilca, Is RMA the Way? Performance Insights Into Device-Initiated RMA using Kokkos Remote Spaces, in Computer Science Research Institute Summer Proceedings 2023, S.K. Seritan and B.W. Reuter, eds., Technical Report SAND2023-13916R, Sandia National Laboratories, 2023, pp. 210–217.
• J. Shawger and M.L. Curry, Offloading Job-Local Filesystems in High-Performance Computing Environments, in Computer Science Research Institute Summer Proceedings 2023, S.K. Seritan and B.W. Reuter, eds., Technical Report SAND2023-13916R, Sandia National Laboratories, 2023, pp. 218–230.
• S. Surti and T. Proctor, A Simple Statistical Model for Randomized Benchmarking Data, in Computer Science Research Institute Summer Proceedings 2023, S.K. Seritan and B.W. Reuter, eds., Technical Report SAND2023-13916R, Sandia National Laboratories, 2023, pp. 231–243.
• A.Q. Wilber-Gauthier and S.K. Seritan, Scalable Benchmarking of Quantum Chemistry Algorithms using Circuit Mirroring, in Computer Science Research Institute Summer Proceedings 2023, S.K. Seritan and B.W. Reuter, eds., Technical Report SAND2023-13916R, Sandia National Laboratories, 2023, pp. 244–254.
• J. Yirka, J. Kallaugher, and O. Parekh, Are Hard Quantum Problems Also Hard Classically?, in Computer Science Research Institute Summer Proceedings 2023, S.K. Seritan and B.W. Reuter, eds., Technical Report SAND2023-13916R, Sandia National Laboratories, 2023, pp. 255–265.
• B. Dalman and M. Barone, An Unsupervised Learning Sensor Fusion Approach for Classification of Turbulent Flow Data, in Computer Science Research Institute Summer Proceedings 2023, S.K. Seritan and B.W. Reuter, eds., Technical Report SAND2023-13916R, Sandia National Laboratories, 2023, pp. 267–277.
• O. Davis, G. Geraci, and M. Motamed, Multi-Fidelity Surrogate Modeling with Fourier Features Networks, in Computer Science Research Institute Summer Proceedings 2023, S.K. Seritan and B.W. Reuter, eds., Technical Report SAND2023-13916R, Sandia National Laboratories, 2023, pp. 278–293.
• I. Furrick, M. Wood, and A. Hensley, Developing a Machine-Learned Interatomic Potential for Nickel-Platinum Catalysts, in Computer Science Research Institute Summer Proceedings 2023, S.K. Seritan and B.W. Reuter, eds., Technical Report SAND2023-13916R, Sandia National Laboratories, 2023, pp. 294–302.
• E. Huynh, T. Meissner, P. Bochev, and P. Kuberry, A Preliminary Study for Obtaining Inverse Sobolev-Type Inequalities for Tanh Neural Networks, in Computer Science Research Institute Summer Proceedings 2023, S.K. Seritan and B.W. Reuter, eds., Technical Report SAND2023-13916R, Sandia National Laboratories, 2023, pp. 303–321.
• E. Islas Quinones and K.A. Maupin, Uncertainty Quantification of Model Form Error Through Surrogate Models, in Computer Science Research Institute Summer Proceedings 2023, S.K. Seritan and B.W. Reuter, eds., Technical Report SAND2023-13916R, Sandia National Laboratories, 2023, pp. 323–335.
• R. Pawar, P. Bochev, and J. Owen, A Neural ODE Based Flux Surrogate Algorithm for Coupled Transmission Problems, in Computer Science Research Institute Summer Proceedings 2023, S.K. Seritan and B.W. Reuter, eds., Technical Report SAND2023-13916R, Sandia National Laboratories, 2023, pp. 336–352.
• K. Polifrone, H. Bayat, J.M. Goff, and W. Xu, Machine Learned Interatomic Potentials for Grain Boundary Segregation in Alloys, in Computer Science Research Institute Summer Proceedings 2023, S.K. Seritan and B.W. Reuter, eds., Technical Report SAND2023-13916R, Sandia National Laboratories, 2023, pp. 353–364.
• T. Meissner, E. Huynh, P. Kuberry, and P. Bochev, A Deep Least-Squares Method for the Stokes Equations, in Computer Science Research Institute Summer Proceedings 2023, S.K. Seritan and B.W. Reuter, eds., Technical Report SAND2023-13916R, Sandia National Laboratories, 2023, pp. 365–375.
• C. Mullen and E.L. Sikorski, The Effects of Organizing Training Data for Machine Learned Potentials, in Computer Science Research Institute Summer Proceedings 2023, S.K. Seritan and B.W. Reuter, eds., Technical Report SAND2023-13916R, Sandia National Laboratories, 2023, pp. 376–381.
• J.N. Ngangmeni and K.A. Maupin, Identification of Model Form Error: A Random Beginning, in Computer Science Research Institute Summer Proceedings 2023, S.K. Seritan and B.W. Reuter, eds., Technical Report SAND2023-13916R, Sandia National Laboratories, 2023, pp. 382–388.
• W. Snyder, I. Tezaur, and C.R. Wentland, Domain Decomposition-Based Couping of Physics-Informed Neural Networks via the Schwarz Alternating Method, in Computer Science Research Institute Summer Proceedings 2023, S.K. Seritan and B.W. Reuter, eds., Technical Report SAND2023-13916R, Sandia National Laboratories, 2023, pp. 389–410.
• V.A. Vera Cruz and E.L. Sikorski, Machine-Learned Potential Development for Hafnium Ceramics in Extreme Conditions, in Computer Science Research Institute Summer Proceedings 2023, S.K. Seritan and B.W. Reuter, eds., Technical Report SAND2023-13916R, Sandia National Laboratories, 2023, pp. 411–421.
• C.J. Villatoro, G. Geraci, and D.E. Schiavazzi, On Coordinate Encoding in Multi-Fidelity Neural Emulators, in Computer Science Research Institute Summer Proceedings 2023, S.K. Seritan and B.W. Reuter, eds., Technical Report SAND2023-13916R, Sandia National Laboratories, 2023, pp. 422–432.