Designed especially for neurobiologists, FluoRender is an interactive tool for multi-channel fluorescence microscopy data visualization and analysis.
Deep brain stimulation
BrainStimulator is a set of networks that are used in SCIRun to perform simulations of brain stimulation such as transcranial direct current stimulation (tDCS) and magnetic transcranial stimulation (TMS).
Developing software tools for science has always been a central vision of the SCI Institute.

Scientific Computing

Numerical simulation of real-world phenomena provides fertile ground for building interdisciplinary relationships. The SCI Institute has a long tradition of building these relationships in a win-win fashion – a win for the theoretical and algorithmic development of numerical modeling and simulation techniques and a win for the discipline-specific science of interest. High-order and adaptive methods, uncertainty quantification, complexity analysis, and parallelization are just some of the topics being investigated by SCI faculty. These areas of computing are being applied to a wide variety of engineering applications ranging from fluid mechanics and solid mechanics to bioelectricity.


Martin Berzins

Parallel Computing

Mike Kirby

Finite Element Methods
Uncertainty Quantification

Valerio Pascucci

Scientific Data Management

Chris Johnson

Problem Solving Environments

Ross Whitaker


Chuck Hansen


Scientific Computing Project Sites:

Publications in Scientific Computing:

Hexahedral Mesh Generation for Biomedical Models in SCIRun
SCI Institute Technical Report, J.F. Shepherd, C.R. Johnson. No. UUSCI-2007-008, University of Utah, 2007.

A Meshing Pipeline for Biomedical Computing
M. Callahan, M.J. Cole, J.F. Shepherd, J.G. Stinstra, C.R. Johnson. In Engineering with Computers, Special Issue on Computational Bioengineering, pp. (in press). 2007.

NSF Blue Ribbon Panel Report on Simulation Based Engineering Science
J.T. Oden, J. Fish, C.R. Johnson, A. Laub, D. Srolovitz, T. Belytschko, T.J.R. Hughes, D. Keys, L. Petzold, S. Yip. Note: NSF Report, 2006.

Purpose: To explore the emerging discipline of Simulation Simulation-Based Engineering Science, its major components, its importance to the nation, the challenges and barriers to its advancement, and to recommend to the NSF and the broader community concerned with science and engineering in the United States, steps that could be taken to advance development in this discipline.

Towards Stable Coupling Methods for High-Order Discretizations of Fluid-Structure Interaction: Algorithms and Observations
R.M. Kirby, Z. Yosibash, G.E. Karniadakis. In Journal of Computational Physics, Vol. 223, No. 2, pp. 489--518. 2006.

A One-Dimensional Model of the Navier-Stokes
SCI Institute Technical Report, H. Marmanis, C.W. Hamman, R.M. Kirby. No. UUSCI-2006-012, University of Utah, 2006.

Biomedical Computing and Visualization
C.R. Johnson, D.M. Weinstein. In Proceedings of the Twenty-Ninth Australasian Computer Science Conference (ACSC2006): Conferences in Research and Practice in Information Technology (CRPIT), Hobart, Australia, Vol. 48, Edited by Vladimir Estivill-Castro and Gill Dobbie, pp. 3-10. 2006.

Advanced Reaction-Diffusion Models for Texture Synthesis
A.R. Sanderson, R.M. Kirby, C.R. Johnson, L. Yang. In Journal of Graphics Tools, Vol. 11, No. 3, pp. 47--71. 2006.

Parallel and Distributed Model Checking in Eddy
I. Melatti, R. Palmer, G. Sawaya, Y. Yang, R.M. Kirby, G. Gopalakrishnan. In Model Checking Software: Proceedings of the 13th International SPIN Workshop (SPIN 2006), Austria, Vol. 3925/2006, pp. 108--125. 2006.

Involving Undergraduates in Computational Science and Engineering Research: Successes and Challenges
R.M. Kirby, C.R. Johnson, M. Berzins. In Proceedings of Computational Science - ICCS 2006: 6th International Conference, Reading, UK, Lecture Notes in Computer Science, Vol. 3992, May 28-31, 2006.

Aliasing Errors Due to Quadratic Non-Linearities On Triangular Spectral/hp Element Discretisations
R.M. Kirby, S.J. Sherwin. In Journal of Engineering Mathematics, Vol. 56, pp. 273--288. 2006.

Gauss: A Framework for Verifying Scientific Computing Software
R. Palmer, S. Barrus, Y. Yang, G. Gopalakrishnan, R.M. Kirby. In Electronic Notes on Theoretical Computer Science (ENTCS), Vol. 144, No. 3, pp. 95--106. February, 2006.

Problem Solving Environments for DDDAS
C.R. Johnson, S.G. Parker. In Proceedings of the Ninth Copper Mountain Conference on Iterative Methods, Copper Mountain, CO, Note: Minisymposium: Actually Doing Dynamic Data-driven Application Simulations, April, 2006.

Formal Verification of Programs that use MPI One-Sided Communications
S. Pervez, G. Gopalakrishnan, R.M. Kirby, R. Thakur, W. Gropp. In Proceedings of EuroPVM-MPI 2006, Bonn, Germany, September 17-20, 2006.

Dynamic Contaminant Identification in Water
C.C. Douglas, J.C. Harris, M. Iskandarani, C.R. Johnson, R.J. Lodder, S.G. Parker, M.J. Cole, R. Ewing, Y. Efendiev, R. Lazarov, G. Qin. In Proceedings of Computational Science - ICCS 2006: 6th International Conference, Part III, Reading, UK, May 28-31, 2006, Lecture Notes in Computer Science series, Vol. 3993, Edited by Vassil N. Alexandrov and Geert Dick van Albada and Peter M.A. Sloot and Jack J. Dongarra, Springer-Verlag Heidelberg, pp. 393--400. 2006.

Computational Methods and Software for Bioelectric Field Problems
C.R. Johnson. In Biomedical Engineering Handbook, 2nd Edition, Vol. 1, Ch. 23, Edited by J.D. Bronzino, CRC Press, Boca Raton, pp. 1--23. 2006.

Ray-Tracing Polymorphic Multi-Domain Spectral/hp Elements for Isosurface Rendering
B. Nelson, R.M. Kirby. In IEEE Transactions on Visualization and Computer Graphics, Vol. 12, No. 1, pp. 114--125. 2006.

Integrating Component-Based Scientific Computing Software
S.G. Parker, K. Zhang, K. Damevski, C.R. Johnson. In Parallel Processing for Scientific Computing, Edited by M.A. Heroux and P. Raghavan and H.D. Simon, SIAM Press, pp. 271--288. 2006.
ISBN: 0-89871-619-5

Computational Science: Ensuring America's Competitiveness
D. Reed, R. Bajcsy, J.M. Griffiths, J. Dongarra, C.R. Johnson. Note: President's Information Technology Advisory Committee (PITAC), June, 2005.

Influence of Stochastic Organ Conductivity in 2D ECG Forward Modeling: A Stochastic Finite Element Study
S.E. Geneser, S. Choe, R.M. Kirby, R.S. MacLeod. In Proceedings of The Joint Meeting of The 5th International Conference on Bioelectromagnetism and The 5th International Symposium on Noninvasive Functional Source Imaging within the Human Brain and Heart, pp. 5528--5531. 2005.

Selecting the Numerical Flux in Discontinuous Galerkin Methods for Diffusion Problems
R.M. Kirby, G.E. Karniadakis. In Journal of Scientific Computing, Vol. 22/23, pp. 385--411. 2005.