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"CUDA, now included in all NVIDIA products, lets programmers use the parallel computing capabilities of a GPU, which involves divvying up work among 128 brains, or "cores," to get a job done faster. By contrast, a standard x86 microprocessor typically has two or four cores." |
| -- Riva Richmond, Journalist, Wall Street Journal | |
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"Companies and research institutions are finding that graphics processors can handle other kinds of work 10 to 150 times faster than standard processors by breaking up large problems into smaller tasks and reassembling the results later." |
| -- Ashlee Vance, Journalist, The New York Times | |
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"NVIDIA is about much more than high-powered video games. With CUDA, NVIDIA touches industries like energy exploration and medical scanning." |
| -- Charlie Rose, Broadcast journalist, PBS Television's The Charlie Rose Show | |
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"Computing with NVIDIA's CUDA GPUs has the potential to advance fundamentally important areas of science - such as decoding the intricate structure of the human brain, discovering the origins of the universe, and studying the quantum chemistry of molecules." |
| -- Hanspeter Pfister, Gordon McKay Prof. of the Practice of Computer Science in Harvard's School of Engineering and Applied Sciences & Director of Visual Computing at the Harvard Initiative in Innovative" Computing, Harvard University | |
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"CUDA is a platform that could save the world or my life someday. It's providing people who otherwise couldn't afford or get access to supercomputing resources the critical capability to get their work done. The kind of work ranges from medical to environmental research, and the result could be the safety of the human race. I'm big on living, so CUDA is a technology I expect great things from." |
| -- Rob Enderle, Principal Analyst, The Enderle Group | |
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"Many of the molecular structures we analyze are so large that they can take weeks of processing time to run the calculations required for their physical simulation. NVIDIA's GPU computing technology has given us a 100-fold increase in some of our programs." |
| -- John Stone, Theoretical and Computational Biophysics, University of Illinois, Urbana-Champaign | |
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"CUDA enabled us - and will continuously allow us - to build one of the world’s fastest supercomputers. CUDA offers a tremendous boost to our scientists and engineers." |
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-- Dr. Satoshi Matsuoka, Professor, Global Scientific Information and Computing Center, Tokyo Institute of Technology |
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"GPUs have evolved to the point where many real-world applications are easily implemented on them and run significantly faster than on multi-core systems. Future computing architectures will be hybrid systems with parallel-core GPUs working in tandem with multi-core CPUs." |
| -- Jack Dongarra, Professor and Director of the Innovative Computing Laboratory, University of Tennessee | |
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"CUDA C and Fortran are the most widely used programming languages for GPU programming today" |
| -- Michael Feldman, Journalist, HPCWire | |
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"Nvidia obviously has the pole position when it comes to offloading HPC work from CPUs to GPU coprocessors, thanks in no small part to the development and adoption of the CUDA programming environment that spans CPUs and GPUs." |
| -- Timothy Prickett Morgan, Journalist, The Register | |
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"In a nutshell, NVIDIA's CUDA architecture provides developers with a way to efficiently program NVIDIA GPUs using a very easy-to-read, C-like syntax. Since its launch in 2006, CUDA has become incredibly popular for a wide spectrum of supercomputing applications, from finance to oil and gas." |
| -- Jon Stokes, Journalist, Ars Technica | |
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