Scientific Computing

scientific computingSimulation 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

Affiliate Faculty

Daniel S. Katz, NCSA resilience and fault-tolerance, many-task computing, parallel and distributed computing, sustainable and open science software

Adjunct Faculty

Frank Cappello,
Argonne National Lab
determinism in high-performance and distributed computing, check-pointing, fault prediction 

Related Scientific Computing Research Efforts and Groups

Scientific Computing Research News

Computer Science Investitures

CS set to honor four distinguished faculty with named chairs and professorships

November 14, 2016   One of the highest honors the campus can bestow, named chairs and professorships acknowledge outstanding faculty research, service, and education accomplishments.
A collection of simulation results using NekCEM/Nek5000

CS @ ILLINOIS professor receives R&D 100 Award for simulation software

November 10, 2016   Paul Fischer and his Argonne research collaborator received one of the "Oscars of Invention" for open-source simulation software package that delivers highly accurate solutions for a wide range of scientific applications.

From Computational Genomics To Precision Medicine

October 29, 2016   Precision medicine—using an individual’s specific genetic profile to help prevent, diagnose, and treat disease—seems to be just on the horizon. Read how CS @ ILLINOIS researchers are bringing it closer to a reality.
CS Professor Bill Gropp

Gropp Recognized for Major Contributions to High Performance Computing

October 6, 2016   CS Professor Bill Gropp has been named the recipient of the 2016 ACM/IEEE Computer Society Ken Kennedy Award.
Bill Gropp

Bill Gropp to Receive Ken Kennedy Award

October 5, 2016  

insideHPC - CS Professor William D. Gropp has been named the winner of the 2016 ACM/IEEE-CS Ken Kennedy Award, "for highly influential contributions to the programmability of high performance parallel and distributed computers."  Additional Coverage: HPCwire