University of Utah Named CUDA Center of Excellence
The University of Utah last week was named a CUDA Center of Excellence for adopting parallel computing strategies and applying them to research and integrating them into the curriculum.
CUDA is a suite of tools, including a C-compiler and SDK, for developing multi-core and parallel processing applications on Nvidia's GPUs. According to Nvidia, more than 50 universities are currently using CUDA for multi-core and parallel processing programming in some capacity--either in research or as part of the curriculum.
"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," said Chris Johnson, director of the Scientific Computing and Imaging Institute at the University of Utah, in a statement released Thursday. "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."
The Scientific Computing and Imaging Institute is one of three groups on the campus that is using CUDA technology. The others include the School of Computing and the Center for the Simulation of Accidental Fires and Explosions.
Some of the applications to which the University of Utah will apply parallel computing technologies include "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," according to the university.
The University of Utah is the second institution to be named a CUDA Center of Excellence. The University of Illinois at Urbana-Champaign became the first about a month earlier. Those institutions that are accepted as CUDA Centers of Excellence receive funding, equipment donations, and support for setting up a GPU computing cluster.
Further information on CUDA can be found here.
