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, instrumenting 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.
CS Faculty and Their Research Interests
|Paul Fischer||numerical PDEs, spectral element methods, computational fluid dynamics, parallel and high-performance algorithms, iterative methods|
|William Gropp||high performance scientific computing, scalable numerical algorithms for PDEs, large-scale parallel software|
|Michael T. Heath||numerical analysis and scientific computing, numerical linear algebra and optimization|
|Laxmikant Kale||simulation software, numerical libraries and algorithms|
|Andreas Kloeckner||integral equation methods for PDEs, high-order finite element methods for hyperbolic PDEs, tools and languages for high-performance computing, time integration|
|William Kramer||extreme-scale computing and analytics, performance evaluation, data and storage techniques|
|Luke Olson||numerical analysis, scientific computing, large-scale simulation|
|Marc Snir||large-scale parallel systems, algorithms, and libraries|
|Edgar Solomonik||communication complexity|
|Robert Brunner, Astronomy||computational astrophysics|
|Daniel S. Katz, NCSA||resilience and fault-tolerance, many-task computing, parallel and distributed computing, sustainable and open science software|
Argonne National Lab
|determinism in high-performance and distributed computing, check-pointing, fault prediction|
Related Scientific Computing Research Efforts and Groups
- Blue Waters in the National Center for Supercomputing Applications
- Center for Exascale Simulation of Plasma-Coupled Combustion
- Computational Science and Engineering
- National Center for Supercomputing Applications (NCSA)
- Parallel Computing Institute (PCI)
- Scientific Computing at Illinois
- Theoretical and Computational Biophysics Group
Scientific Computing Research News
HPCWire -- National Center For Supercomputing Applications Director and Thomas M. Siebel Chair in Computer Science William Gropp has been named a Fellow of the American Association for the Advancement of Science (AAAS).
New Scientist -- The roadmap for exascale hardware is fairly well laid out. Software and algorithms to run across potentially billions of cores may be trickier. “Every generation of supercomputers leaves some users behind,” says William Gropp, CS professor and director of the National Center for Supercomputing Applications. “That’s been a constant problem and I think we’re going to see it again.” (behind paywall)
Pasadena Now -- The National Science Foundation and the U.S. Department of Energy have announced new funding awards for quantum-related research. Co-PIs include Illinois CS Assistant Professor Edgar Solomonik.
Popular Science -- “The machines are all over subscribed,” Bill Gropp, Illinois CS Professor and director of the National Center for Supercomputing Applications, says as work starts for what will be the next, fastest supercomputer, Frontera. Illinois' Blue Waters has been used to do things like model an enormous EF-5 tornado and to produce maps of Alaska.