SCIENTIFIC COMPUTING AND IMAGING INSTITUTE University of Utah Scientific Computing and Imaging Institute The SCI research group was founded in tute recruited Dongbin Xiu. Dongbin is one many of the above computational techniques 1994 by Drs. Chris Johnson and Rob Ma- of the most recognized names and highly within their own particular scientific and cLeod along with five graduate students. In cited researchers in the area of uncertainty engineering sub-specialties, such as fluid 1996, they became the Center for Scientific quantification, and has made a wonderful dynamics, biomechanics, electrophysiology, Computing and Imaging and in 2000, the addition to the Institute. 2014 saw the addi- bioelectric fields, parallel computing, inverse SCI Institute. The Scientific Computing and tion of Christopher Butson. Dr. Butson is the problems, and neuroimaging. Imaging (SCI) Institute is now one of eight Director of Neuromodulation Research and permanent research institutes at the Univer- an Associate Professor in the departments A particular hallmark of SCI Institute re- sity of Utah and home to over 200 faculty, of Biomedical Engineering and Neurology search is the development of innovative students, and staff. The 16 tenure-track fac- & Neurosurgery. In 2015 we added Alexan- and robust software packages, including the ulty are drawn primarily from the School of der Lex (information visualization) and Akil SCIRun scientific problem solving environ- Computing, Department of Bioengineering, Narayan (mathematics) to our faculty team. ment, Seg3D, ImageVis3D, VisTrails, ViSUS, Department of Mathematics, and Depart- and map3d. All these packages are broadly ment of Electrical and Computer Engineer- Over the past decade, the SCI Institute has available to the scientific community under ing, and virtually all faculty have adjunct established itself as an internationally recog- open source licensing and supported by web appointments in other, largely medical, de- nized leader in visualization, scientific com- pages, documentation, and users groups. partments. Recent growth in the SCI Insti- puting, and image analysis applied to a broad tute has come in part from the award in 2007 range of application domains. The overarch- The SCI Institute either directs or is associ- from the state of Utah of a USTAR (Utah ing research objective is to conduct applica- ated with several national research centers: Science and Technology Advanced Re- tion-driven research in the creation of new the NIH Center for Integrative Biomedical search) cluster in Imaging Technology. This scientific computing techniques, tools, and Computing (CIBC), the DoE Scalable Data allowed the Institute to recruit three new systems. An important application focus of Management, Analysis, and Visualization faculty in image analysis: Professors Guido the Institute continues to be biomedicine, (SDAV), the NIH National Alliance for Gerig, Tom Fletcher, Tolga Tasdizen. During however, SCI Institute researchers also ad- Medical Image Computing (NA-MIC), the this same time period, they were also able to dress challenging computational problems DoE Scientific Data Management Center, recruit Professor Valerio Pascucci in visu- in a variety of application domains such as the NIH Center for Computational Biology, alization. In 2011, USTAR funding allowed manufacturing, defense, and energy. SCI In- and the DoE Center for the Simulation of two more: Orly Alter who specializes in ge- stitute research interests generally fall into Accidental Fires and Explosions (C-SAFE). nomic signal processing and Miriah Meyer, the areas of: scientific visualization, scientific In July, 2008, SCI was chosen as one of three who’s novel biological visualization tools are computing and numerics, image processing NVIDIA Centers of Excellence in the U.S. revolutionizing the way scientists view and and analysis, and scientific software environ- (University of Illinois and Harvard Universi- understand their data. In 2012, the SCI Insti- ments. SCI Institute researchers also apply ty are the other two NVIDIA Centers). 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 nu- merical 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. ElVis: A System for the Accurate and Inter- active Visualization of High-Order Finite Element Solutions. Shown here is the pres- sure field on the ONERA M6 Wing. The Uintah Computational Framework is being extended to model various ener- Parametric study of a contained explosive View of the pressure field of a rotating can- gy technologies from traditional air-fired detonation. ister moving through an incompressible coal, oxy-fired coal/natural gas, fluidized fluid. A color map of the field, along with bed coal combustion and coal gasification contours of constant pressure, have been to more exotic coal technologies such as applied to the cylinder and the cut-plane. chemical looping and under ground ther- mal treatment. Material Point Method simulation of con- Simulating the stress points during a foam tainer heat up with global illumination. compaction study. The Carbon-Capture Multidisciplinary Simulation Center (CCMSC) is demon- strating exascale computing with V&V/UQ to more rapidly deploy a new technology Examples of two chemical mixing simu- for providing low cost, low emission elec- lations within the Uintah Computational Automatic mesh refinement on the ball tric power generation to meet the growing Framework. shockwave simulation. energy needs of the U.S. Biomedical Computing Biomedical computing combines the diagnostic and investigative aspects of biology and medical science with the power and prob- lem-solving capabilities of modern computing. Computers are used to accelerate research learning, simulate patient behavior and visu- alize complex biological models. Finite element predictions of shoulder cap- sule strain Interactive exploration of large tractogra- phy and EEG data for source localization We have developed software to interactive- ly explore novel locations for implantable cardiac defibrillators (ICDs) in children, allowing logical placement of electrodes rather than clinical trial and error. Osseointegration simulation. Electric Field (top) and Current Density (bottom) distri- butions at the bone-implant interface. Inverse EEG - localizing the source of an epileptic seizure. Interactive simulation of electrode place- SCI researchers are exploring patterns of ment in deep brain stimulation (DBS). SCI DNA copy-number alterations in personal- has deployed an interactive visualization ized diagnostic and prognostic tests. These system (ImageVis3D Mobile) for experi- patterns will be used in personalized diag- mental use in DBS planning. Transcranial DC (electrical) Stimulation of nostic and prognostic pathology laboratory standard and high density electrodes. tests. Scientific Visualization Scientific visualization, sometimes referred to as visual data analysis, uses the graphical representation of data as a means of gaining understanding and insight into the data. Scientific visualization research at SCI has focused on applications spanning computational fluid dynamics, medical imaging and analysis, and fire simulations. Research involves novel algorithm development to building tools and systems that assist in the comprehension of massive amounts of scientific data. In helping researchers to comprehend spatial and tem- poral relationships between data, interactive techniques provide better cues than noninteractive techniques; therefore, much of scientific visualization research focuses on better methods for visualization and rendering at interactive rates. A visualization of a topological analysis and volume visualization of one time step in a large-scale combustion simulation. Ray Tracing and Volume Rendering Large A visualization of the brain using transfer Molecular Data. Shown is a small carbon functions that express the risk associated nanosphere (90K atoms) with volumetric with classification. lighting and shadows. FluoRender is an interactive tool for multi-channel fluorescence microscopy data visualization and analysis. It has been designed especially for neurobiologists. Tokamak fusion visualization. Here we see the magnetic island chain that dominates the inner core of the simulation. Visualizing the magnetic fields of our sun. Creating anatomical models from fluores- cence microscopy. Exploring large data with ImageVis3D. Multi-surface volume rendering. Image Analysis SCI’s imaging work addresses fundamental questions in 2D and 3D image processing, including filtering, segmentation, surface recon- struction, and shape analysis. In low-level image processing, this effort has produce new nonparametric methods for modeling image statistics, which have resulted in better algorithms for denoising and reconstruction. Work with particle systems has led to new methods for visualizing and analyzing 3D surfaces. Our work in image processing also includes applications of advanced