Research Highlights

Following is a list of selected highlights from the FASTMath Institutes.

2022:

• Surrogate Modeling via Functional Tensor Networks in Arbitrary Formats

• Using ParMOO to Drive Materials Design

• Uncertainty Quantification for Fusion Plasma-Surface Interactions

• Dynamic AMR for a Relativistic Electron Drift-Kinetic Solver and Scalable PETSc-p4est Implementation and Implicit Time Stepping

• Parallel Unstructured Mesh Infrastructure for PIC (PUMIPic) and its integration into Tokamak Edge Plasma (XGCm) and Impurity Transport (GITRm) Codes

• MFEM Facilitates the Design of More Robust Tokamak RF Antennas: High-order Methods on Adaptive Unstructured Meshes (updated)

• A New Algebraic Multigrid Solver for Semi-structured Linear Systems

• Fast and Flexible Monolithic AMG Framework for Multiphysics PDE Systems

2021:

• Bidirectional Data Movement In Situ Accelerates Time to Insight

• Dynamic Load Balancing for Particle-in-Cell Codes: EnGPar

• Computational Tools for Exascale Fusion Simulations

• Portable Structure Preserving Kinetic Methods for Fusion Plasmas

• Scalable Implicit, Adaptive MFEM-based Solver for Reduced Resistive MHD

• MFEM Miniapps Enhance Tokamak Simulations

• Scalable Preconditioners for Tokamak Applications in MFEM

• MFEM Facilitates the Design of More Robust Tokamak RF Antennas: High-order Methods on Adaptive Unstructured Meshes

• Hierarchical Partitioning for Distributed Multi-GPU Platforms

• Parallel Unstructured Mesh Infrastructure for PIC (PUMIPic) and its Integration into Tokamak Edge Plasma (XGCm) and Impurity Transport (GITRm) Codes

• Multiscale/Multirate Modeling of ITG/ETG Tokamak Turbulence

• New Multirate Time Integrators Enable Greater Efficiency in Multiscale Problems

• Fast and Flexible Monolithic AMG Framework for Multiphysics PDE Systems

• Batched All GPU Controlled Solvers for Many Small Systems

• Low-complexity Sparse Direct Solvers for Wave Equations

• New Low Synchronization Methods Speed Up Anderson Accelerated Nonlinear Solvers

• SuperLU: Sparse Triangular Solve on multi-GPUs

• Solving Neural Ordinary Differential Equations with PETSc

• Learning Stiff Hamiltonian Systems from Data

• Anderson Accelerated Solvers for Faster Fusion Simulations

• Improving Dense Block Structure in Sparse Matrix Factorization

• New Algebraic Multigrid Solver for Semi-structured Problems

• Solving Eigenvalue Problem with Localized Eigenvectors using Reinforcement Learning

• Enhancing Scalability of a Matrix-Free Tensor Eigensolver for Studying Many-Body Localization

• Bilevel and Robust Optimization for Automated Tuning of HEP Event Generators

• Optimal Design of Electro-Magnetic Cloaks using Fast Solvers for Mixed-Integer PDE-Constrained Optimization

• Differentiable ODE Solvers for PDE-constrained Optimization and Scientific Machine Learning

• Training Neural Networks Under Physics Constraints: Approximating the Fokker-Planck-Landau Collision Operator for XGC

• TAD: Targeted Adaptive Design

• Uncertainty Quantification for Impurity Transport Model

• Batch Greedy Algorithms and Guarantees for Optimal Experimental Design

• Multifidelity Uncertainty Quantification for Tokamak Disruption Simulation (TDS)

• Haar-Like Wavelets on Clustered Point Clouds

• Parameter Estimation from Observational Data using ML Method

• Capturing Euclidean Metric Structure with Randomized Trees

• Data Analytics of Streaming Scientific Data

• Performance Optimization for Large-scale Eigenvalue Computation [FASTMath-RAPIDS collaboration]

• Source Code and Algorithm Optimizations Speed Up Nuclear Physics Simulations [FASTMath-RAPIDS collaboration]

• Bidirectional Data Movement In Situ Accelerates Design Space Optimization [FASTMath-RAPIDS collaboration]

• MGARD Data Compression Tool: v1 Release [FASTMath-RAPIDS collaboration]

• Machine Learning-Based Inversion of Nuclear Responses [FASTMath-RAPIDS collaboration]

• Optimal Design and Control with Machine-Learning Surrogates [FASTMath-RAPIDS collaboration]

• FASTMath-RAPIDS Interaction: Coupling Fusion Codes via ADIOS2 and EFFIS 2.0 [FASTMath-RAPIDS collaboration]

• CTTS-FASTMath-RAPIDS Partnership [FASTMath-RAPIDS collaboration]