Scientific Computing

Simulation plays a major role in nearly every area of science and engineering—from data analysis to physical models. Our faculty design, build, and analyze the behavior of numerical algorithms to ensure that numerical methods are accurate and that implementations are efficient.

We design and analyze the accuracy of methods, developing numerical approximations to partial differential equations with advanced finite element methods and integral equations. We also develop solvers for these problems, including techniques based on numerical linear algebra, iterative subspace methods, and multigrid methods. Our research explores the efficiency of these methods on a range of architectures and environments, from high-concurrency nodes, such as GPUs, to large-scale supercomputing systems. We explore parallel scalability and analyze performance in computing kernels from graph algorithms to sparse linear algebra.

Faculty & Affiliate Faculty

Parallel Algorithms and Libraries, Parallel Graph Algorithms, Performance Modeling

Computational Inverse Problems, Image Reconstruction, Wave Physics Modeling in Imaging

High-Order Numerical Methods for Partial Differential Equations, Scalable Parallel Algorithms, Iterative Solvers, Parallel Computing, Spectral Element Methods, Computational Fluid Dynamics

High Performance Scientific Computing, Scalable Numerical Algorithms for PDEs, Numerical Software, Performance Analysis

Simulation Software, Numerical Libraries and Algorithms 

Resilience and Fault-Tolerance, Many-Task Computing, Parallel and Distributed Computing, Sustainable and Open Science Software

Integral Equation Methods for PDEs, High-Order Finite Element Methods for Hyperbolic PDEs, Tools and Languages for High-Performance Computing, Time Integration 

Extreme-Scale Computing and Analytics, Performance Evaluation, Reliability and Resiliency of Large Scale Systems, Data and Storage Techniques, Performance Variability

Numerical Analysis, Scientific Computing, Large-Scale Simulation, Multigrid and Iterative Methods, Finite Element Methods

Parallel Computing, Compilers, Parallel Libraries, High Performance Computing, Parallel Architecture, Exascale Computing

Large-Scale Parallel Systems, Algorithms, Libraries 

Numerical Linear Algebra, Tensor Computations, Parallel Algorithms, Quantum Chemistry, Quantum Simulation

Adjunct Faculty

Determinism in High-Performance and Distributed Computing, Check-Pointing, Fault Prediction 

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