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.

SCI Publications

2005


 D.E. DeMarle, C.P. Gribble, S. Boulos, S.G. Parker. “Memory Sharing for Interactive Ray Tracing on Clusters,” In Parallel Computing, Vol. 31, No. 2, pp. 221--242. 2005.


D.M. Weinstein, S.G. Parker, J. Simpson, K. Zimmerman, G.M. Jones. “Visualization in the SCIRun Problem-Solving Environment,” In The Visualization Handbook, Edited by C.D. Hansen and C.R. Johnson, Elsevier, pp. 615--632. 2005.
ISBN: 0-12-387582-X

2004


 M. Cole, F.B. Sachse, D.M. Weinstein, S.G. Parker, R.M. Kirby. “A Software Framework for Solving Problems of Bioelectricity Applying High-Order Finite Elements,” In Proceedings of the IEEE Engineering in Medicine and Biology Society 26th Annual International Conference, Vol. 1, pp. 821--824. 2004.


D.E. DeMarle, C.P. Gribble, S.G. Parker. “Memory-Savvy Distributed Interactive Ray Tracing,” In Proceedings of The 6th Eurographics Symposium on Parallel Graphics and Visualization, Edited by Dirk Bartz and Bruno Raffin and Han-Wei Shen, 2004.


C. Gribble, S.G. Parker, C.D. Hansen. “Interactive Volume Rendering of Large Datasets Using the Silicon Graphics Onyx4 Visualization System,” No. UUCS-04-003, University of Utah School of Computing, January 27th, 2004.


C.R. Johnson, R.S. MacLeod, S.G. Parker, D.M. Weinstein. “Biomedical Computing and Visualization Software Environments,” In Comm. ACM, Vol. 47, No. 11, pp. 64--71. 2004.


R.S. Macleod, D.M. Weinstein, J.D. de St. Germain, D.H. Brooks, C.R. Johnson, S.G. Parker. “SCIRun/BioPSE: Integrated Problem Solving Environment for Bioelectric Field Problems and Visualization,” In Proceedings of the Int. Symp. on Biomed. Imag., Arlington, Va, pp. 640--643. April, 2004.


K. Zhang, K. Damevski, V. Venkatachalapathy, S.G. Parker. “SCIRun2: A CCA Framework for High Performance Computing,” In Proceedings of The 9th International Workshop on High-Level Parallel Programming Models and Supportive Environments, April, 2004.

2003


 M. Cole, S.G. Parker. “Dynamic Compilation of C++ Template Code,” In Scientific Programming, Vol. 11, IOS Press, pp. 321--327. 2003.


K. Damevski, S.G. Parker. “Parallel Remote Method Invocation and M-by-N Data Redistribution,” In Proceedings of the 4th Los Alamos Computer Science Institute Symposium, pp. (published on CD). 2003.


D.E. DeMarle, S.G. Parker, M. Hartner, C. Gribble, C.D. Hansen. “Distributed Interactive Ray Tracing for Large Volume Visualization,” In IEEE Symposium on Parallel Visualization and Graphics, Seattle, Wa., pp. 87--94. October, 2003.


J.D. de St. Germain, S.G. Parker. “Software Integration in an Academic Environment,” In Software Quality Forum (SQF), Arlington, Virginia, pp. (published on CD). March, 2003.


J.D. de St. Germain, A. Morris, S.G. Parker, A.D. Malony, S. Shende. “Performance Analysis Integration in the Uintah Software Development Cycle,” In International Journal of Parallel Programming, Vol. 31, No. 1, pp. 35--53. 2003.

ABSTRACT

The increasing complexity of high-performance computing environments and programming methodologies presents challenges for empirical performance evaluation. Evolving parallel and distributed systems require performance technology that can be flexibly configured to observe different events and associated performance data of interest. It must also be possible to integrate performance evaluation techniques with the programming paradigms and software engineering methods. This is particularly important for tracking performance on parallel software projects involving many code teams over many stages of development. This paper describes the integration of the TAU and XPARE tools in the Uintah Computational Framework (UCF). Discussed is the use of performance mapping techniques to associate low-level performance data to higher levels of abstraction in UCF and the use of performance regression testing to provide a historical portfolio of the evolution of application performance. A scalability study shows the benefits of integrating performance technology in building large-scale parallel applications.

Keywords: uintah


 C.P. Gribble, S.G. Parker. “A Survey of the Itanium Architecture from a Programmer's Perspective,” SCI Institute Technical Report, No. UUSCI-2003-003, University of Utah, August, 2003.


S.G. Parker. “C-SAFE Uses Linux HPCC in Fire Research,” In Syllabus, Technology for Higher Education, Vol. 16, No. 7, Feburary, 2003.

2002


 J.D. de St. Germain, A. Morris, S.G. Parker, A.D. Malony, S. Shende. “Integrating Performance Analysis in the Uintah Software Development Cycle,” In Proceedings of The 4th International Symposium on High Performance Computing, pp. 190--206. May 15-17, 2002.


C.R. Johnson, S.G. Parker, D. Weinstein, S. Heffernan. “Component-Based Problem Solving Environments for Large-Scale Scientific Computing,” In J. Conc. & Comp.: Prac. & Exper., Vol. 14, pp. 1337--1349. 2002.


W. Martin, E. Reinhard, P. Shirly, S.G. Parker, W. Thompson. “Temporally Coherent Interactive Ray Tracing,” In Journal of Graphics Tools, Vol. 7, No. 2, pp. 41--48. 2002.


S.G. Parker. “Interactive Ray Tracing on a Supercomputer,” In In Practical Parallel Rendering, Edited by A. Chalmers and E. Reinhard, 2002.


S.G. Parker. “A Component-Based Architecture for Parallel Multi-physics PDE Simulation,” In Proceedings of the International Conference on Computational Science (ICCS) 2002, Vol. 2331, pp. 719--734. 2002.