Designed especially for neurobiologists, FluoRender is an interactive tool for multi-channel fluorescence microscopy data visualization and analysis.
Large scale visualization on the Powerwall.
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.

NVIDIA GPU Center of Excellence H lowres Badge
NVIDIA GPU Center of Excellence

"Often before a great discovery there is the creation of a new tool or a tool that is used in a different way than before. GPUs and the algorithms and software that they use are today's tools and with them we are entering a golden age, where scientific computing is going to truly change the way we do science and medicine."

-Chris Johnson

As a GPU Center of Excellence, the University of Utah is using CUDA technology extensively across three facilities:


Scientific Computing and Imaging (SCI) Institute
The SCI Institute has established itself as an internationally recognized leader in visualization, scientific computing, and image analysis. The overarching research objective of the SCI Institute is to create new scientific computing techniques, tools, and systems that enable solutions to important problems in biomedicine, science, and engineering. For more information:

The School of Computing 
The School of Computing has a long history of distinguished faculty and alumni who have made substantial contributions to research and industry. The CUDA Center will play a key role in the School's new Digital Media Initiative linking Computing with Fine Art and Film and funded by the USTAR Initiative

Center for the Simulation of Accidental Fires and Explosions (CSAFE)
As one of the Department of Energy's five Advanced Simulation and Computing (ASC) centers, Utah runs detailed simulations of high energy devices and hydro-carbon fires, designed to increase the safety of dangerous material transportation and storage.

"The synergy of graphics combined with computational horsepower provided by NVIDIA GPUs and the CUDA programming environment provides incredible opportunities in science, industry and commerce," stated Dr. Steven Parker, adjunct professor of computer science at the University of Utah and principal research scientist at NVIDIA.

"The worlds of scientific computing and computer graphics owe a great deal to the University of Utah and those who have passed through its halls," said David Kirk, chief scientist at NVIDIA. "CUDA technology has the potential to truly transform industries, as we have already seen in fields such as medicine, geophysics and finance. With a school of Utah's caliber incorporating it into their curriculum and across many of its research facilities, I am personally very excited to see what advances can be made."

The GPU Center of Excellence at the University of Utah is using GPU technology to make significant advances in a number of scientific applications, including seismic data processing and visualization, MRI and diffusion tensor image reconstruction, cardiac electrical wave propagation simulation, combustion and fluid dynamics simulation, and several projects in large-scale scientific visualization.


SCI GPU publications

NVIDIA GPU Center of Excellence BW V lowres Badge


A Few Technical Specs

  1. 32x node GP-GPU cluster HP DL320SL Gen8 nodes
  2. Each node has 16 cores, 64GB of RAM with Intel E5-2660 2.20GHz processors.
  3. Each node has 2x Nvidia k20 GPUs and 4 full speed FDR Infiniband connections (2x FDR cards).
  4. System has a total of 128 56Gb/s Infiniband connections.
  5. 8x Mellanox SX6025 FDR switches
  6. 4x Mellanox SX6036 FDR switches

GPU Research and Teaching Efforts

GKLEE - A concolic (concrete + symbolic) verifier plus test generator. Accepted at PPoPP 2012

CS6963: Parallel Programming for GPUs