Following is a list of selected highlights from the FASTMath Institute.
2025:
Uncertainty Quantification of Neural Network Models via Langevin Sampling
Embedded Nonlocal Operator Regression (ENOR): Quantifying Model Error in Learning Nonlocal Operators
Surrogate Modeling of MHD Flows for Liquid Metal Fusion Blankets
Efficient Eigenvalue Computation for Nuclear Structure Calculations
Inexact Subspace Projection Methods for Tensor Eigenvalue Problems
Disentangling Latent Spaces in AI/ML Generative Models for Scientific Datasets
ShyLU node: On-node Scalable Solvers and Preconditioners Recent Progress and Current Performance
Stellarator Geometry, Meshing and Code Coupling Technologies
GPU Acceleration of Monte Carlo Tallies on Unstructured Meshes in OpenMC
Parallel Unstructured Mesh Infrastructure for Particle Simulations
MFEM Facilitates the Design of More Robust Fusion System RF Antennas
Theoretical Training Guaranties for Stochastic Neural Networks (SNN)
Adaptive replication cuts oracle queries in noisy optimization
Multi-fidelity methods for quantifying uncertainty in sea-level projections
2023:
Dispersion Enhanced Sequential Batch Sampling For Adaptive Contour Estimation
Scaling Iterative Eigenvalue Solvers on GPU-Based Supercomputers
Advanced PDE-constrained Optimization Capability for Ice Sheet Calibration
Structure Preserving, HPC Landau Collision Operator for Runaway Electron Mitigation
Multiobjective Optimization Methods for the LCLS-II Photoinjector
Multirate Methods for Coupled Compressible Navier-Stokes Systems
Structure-Aware Methods for Expensive Derivative-Free Nonsmooth Composite Optimization
Bayesian Calibration for Xenon Diffusion in UO2 Nuclear Fuel
Batched All GPU Solvers for Many Small System Solves in PETSc
A New Algebraic Multigrid Solver for Semi-Structured Linear Systems
Recent Algorithm Development in SuperLU_DIST Sparse Direct Solver for SciDAC Applications
2021:
Bidirectional Data Movement In Situ Accelerates Time to Insight
Portable Structure Preserving Kinetic Methods for Fusion Plasmas
Scalable Implicit, Adaptive MFEM-based Solver for Reduced Resistive MHD
Hierarchical Partitioning for Distributed Multi-GPU Platforms
New Multirate Time Integrators Enable Greater Efficiency in Multiscale Problems
Fast and Flexible Monolithic AMG Framework for Multiphysics PDE Systems
New Low Synchronization Methods Speed Up Anderson Accelerated Nonlinear Solvers
Improving Dense Block Structure in Sparse Matrix Factorization
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
Differentiable ODE Solvers for PDE-constrained Optimization and Scientific Machine Learning
Batch Greedy Algorithms and Guarantees for Optimal Experimental Design
Multifidelity Uncertainty Quantification for Tokamak Disruption Simulation (TDS)
Parameter Estimation from Observational Data using ML Method
Performance Optimization for Large-scale Eigenvalue Computation [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]
CTTS-FASTMath-RAPIDS Partnership [FASTMath-RAPIDS collaboration]