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Taiwan 2008 CUDA Course Programming Massively Parallel Processors: the CUDA experience Lecture 9 Discussions and Con

David Kirk/NVIDIA and Wen-mei W. HwuTaiwan, June 30-July 2, 2008. Discussions. All attendees please share yourname, affiliationresearch domain or projectmotivation for learning CUDAplans for CUDA related researchquestions, concerns, and thoughts. David Kirk/NVIDIA and Wen-mei W. HwuTaiwan

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Taiwan 2008 CUDA Course Programming Massively Parallel Processors: the CUDA experience Lecture 9 Discussions and Con

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    1. © David Kirk/NVIDIA and Wen-mei W. Hwu Taiwan, June 30-July 2, 2008 Taiwan 2008 CUDA Course Programming Massively Parallel Processors: the CUDA experience Lecture 9 Discussions and Conclusions

    2. © David Kirk/NVIDIA and Wen-mei W. Hwu Taiwan, June 30-July 2, 2008 Discussions All attendees please share your name, affiliation research domain or project motivation for learning CUDA plans for CUDA related research questions, concerns, and thoughts

    3. © David Kirk/NVIDIA and Wen-mei W. Hwu Taiwan, June 30-July 2, 2008 A Great Opportunity for Many GPU parallel computing allows Drastic reduction in “time to discovery” 1st principle-based simulation at meaningful scale New, 3rd paradigm for research: computational experimentation The “democratization” of power to discover $2,000/Teraflop SPFP in personal computers today $5,000,000/Petaflops DPFP in clusters in two years HW cost will no longer be the main barrier for big science You will make the difference! Join the international CUDA research, education and development community Mention Petascale, ECE498AL, and IACAT Mention Petascale, ECE498AL, and IACAT

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