Johns Hopkins Joins 12 Other Institutions as NVIDIA CUDA Center of Excellence
Press Release from NVIDIA
SANTA CLARA, Calif. — Oct. 3, 2011 — NVIDIA today announced that it has named The Johns Hopkins University a CUDA Center of Excellence, recognizing its ground-breaking work leveraging NVIDIA GPUs and NVIDIA CUDA technology to drive education and research programs across a range of scientific disciplines.
The CUDA Center of Excellence program rewards and fosters collaboration with leading institutions that are at the forefront of parallel computing research. Johns Hopkins joins an elite network of 12 institutions around the world that are advancing awareness of parallel computing, and empowering academics and scientists to conduct world-changing research.
University researchers have pioneered the field of data-intensive computing, addressing a key bottleneck to transformative scientific discovery – researchers’ inability to analyze in a timely manner the massive amounts of complex data generated by instruments and simulations. They are leveraging the tremendous processing power of GPUs to dramatically speed up data analysis across multiple fields, including astrophysics, fluid dynamics, genomics, life sciences, medical imaging, and numerical simulation, among others.
“Modern scientific computing is amazingly diverse, with scientists assembling novel systems by combining commodity components in unusual ways,” said Alex Szalay, Alumni Centennial Professor of Physics and Astronomy at The Johns Hopkins University. “Our collaboration with NVIDIA will open up new directions in data-intensive scientific computing. We are working to enable researchers to dramatically increase the pace of scientific discovery by focusing on ways to on quickly and cost-effectively stream petabytes of data into an array of a hundred GPUs for processing at supercomputer rates.”
Johns Hopkins has integrated CUDA technology and GPU computing curriculum into multiple disciplines across the schools of science and engineering. In addition, it is developing a new e-Science curriculum to educate students across all campus disciplines in modern parallel computing techniques.
As a CUDA Center of Excellence, Johns Hopkins will utilize GPU computing equipment and grants provided by NVIDIA to support a number of research and academic programs, including:
· Deployment of the “Data-Scope,” a GPU-powered, ultra-high throughput supercomputer to dramatically increase the speed of scientific data analysis
· Exploration of innovative astronomy algorithms, potentially leading to major new discoveries
· Extreme-scale numerical simulations of the universe, which can help reveal how galaxies were formed
· Massive processing and remote visualization of medical images, designed to improve the quality of healthcare
· Expand multi‐scale, multi‐physics efforts to handle very large environmental simulations, like ocean circulation models
· Real‐time planning of radiation oncology treatments with ray tracing on GPUs to individualize and improve treatments of cancer patients
· Explore future extreme data intensive architectures, with low‐power computing
Other CUDA Centers of Excellence include: Georgia Tech, Harvard University, Institute of Process Engineering at the Chinese Academy of Sciences, National Taiwan University, Stanford University, Tokyo Tech (Japan), Tsinghua University (China), University of Cambridge (England), University of Illinois at Urbana-Champaign, University of Maryland, University of Tennessee, and University of Utah. For more information on the NVIDIA CUDA Center of Excellence program, visit: http://research.nvidia.com/content/cuda-centers-excellence.
SANTA CLARA, Calif. — Oct. 3, 2011 — NVIDIA today announced that it has named The Johns Hopkins University a CUDA Center of Excellence, recognizing its ground-breaking work leveraging NVIDIA GPUs and NVIDIA CUDA technology to drive education and research programs across a range of scientific disciplines.
The CUDA Center of Excellence program rewards and fosters collaboration with leading institutions that are at the forefront of parallel computing research. Johns Hopkins joins an elite network of 12 institutions around the world that are advancing awareness of parallel computing, and empowering academics and scientists to conduct world-changing research.
University researchers have pioneered the field of data-intensive computing, addressing a key bottleneck to transformative scientific discovery – researchers’ inability to analyze in a timely manner the massive amounts of complex data generated by instruments and simulations. They are leveraging the tremendous processing power of GPUs to dramatically speed up data analysis across multiple fields, including astrophysics, fluid dynamics, genomics, life sciences, medical imaging, and numerical simulation, among others.
“Modern scientific computing is amazingly diverse, with scientists assembling novel systems by combining commodity components in unusual ways,” said Alex Szalay, Alumni Centennial Professor of Physics and Astronomy at The Johns Hopkins University. “Our collaboration with NVIDIA will open up new directions in data-intensive scientific computing. We are working to enable researchers to dramatically increase the pace of scientific discovery by focusing on ways to on quickly and cost-effectively stream petabytes of data into an array of a hundred GPUs for processing at supercomputer rates.”
Johns Hopkins has integrated CUDA technology and GPU computing curriculum into multiple disciplines across the schools of science and engineering. In addition, it is developing a new e-Science curriculum to educate students across all campus disciplines in modern parallel computing techniques.
As a CUDA Center of Excellence, Johns Hopkins will utilize GPU computing equipment and grants provided by NVIDIA to support a number of research and academic programs, including:
· Deployment of the “Data-Scope,” a GPU-powered, ultra-high throughput supercomputer to dramatically increase the speed of scientific data analysis
· Exploration of innovative astronomy algorithms, potentially leading to major new discoveries
· Extreme-scale numerical simulations of the universe, which can help reveal how galaxies were formed
· Massive processing and remote visualization of medical images, designed to improve the quality of healthcare
· Expand multi‐scale, multi‐physics efforts to handle very large environmental simulations, like ocean circulation models
· Real‐time planning of radiation oncology treatments with ray tracing on GPUs to individualize and improve treatments of cancer patients
· Explore future extreme data intensive architectures, with low‐power computing
Other CUDA Centers of Excellence include: Georgia Tech, Harvard University, Institute of Process Engineering at the Chinese Academy of Sciences, National Taiwan University, Stanford University, Tokyo Tech (Japan), Tsinghua University (China), University of Cambridge (England), University of Illinois at Urbana-Champaign, University of Maryland, University of Tennessee, and University of Utah. For more information on the NVIDIA CUDA Center of Excellence program, visit: http://research.nvidia.com/content/cuda-centers-excellence.
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