Welcome to CUDA: WEEK IN REVIEW, an online news summary for the worldwide CUDA, GPGPU and parallel programming ecosystem. |
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SPECIAL ISSUE: One Week Countdown to the GPU Technology Conference! |
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GTC FACTS |
What: GTC is a worldwide event for scientists, engineers, researchers and developers who use GPU computing to tackle computational challenges. Featuring over 300 sessions, it presents a broad spectrum of relevant information in a welcoming and collaborative environment.
When: May 14-17, 2012
Where: San Jose, Calif.
Why: Learn. Explore. Network. |
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GTC QUICK LINKS |
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GTC KEYNOTE SPEAKERS |
The keynote line-up includes:
Jen-Hsun Huang, CEO, NVIDIA, May 15
Iain Couzin, Princeton University, May 16
Robert Boehme and Wes Faler, Part-Time Scientists, May 17 |
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GTC CO-LOCATED EVENTS |
InPar 2012, May 13-14
Silicon Valley GPU Meetup, May 15
Emerging Companies Summit, May 16
Los Alamos Natl. Lab Accelerated HPC Symposium, May 16 - 17
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GTC SESSION SAMPLES |
GPU-Accelerated Science on Titan: Tapping into the World’s Preeminent GPU Supercomputer to Achieve Better Science
Jack Wells, Ph.D. (Director of Science, Oak Ridge Leadership Computing Facility, Oak Ridge National Laboratory)
Two-Petaflops Stencil Application with Stereoscopic 3D Visualization - Gordon Bell Prize 2011
Takayuki Aoki (Professor, Tokyo Institute of Technology)
Inside Kepler
Stephen Jones (CUDA Developer, NVIDIA), Lars Nyland (Senior Architect, NVIDIA)
CUDA 5 and Beyond
Mark Harris (Chief Technologist, GPU Computing, NVIDIA)
GPU Accelerated Bioinformatics Research at BGI
BingQiang Wang (Head of High Performance Computing, BGI) |
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GTC PROMO CODES |
Academic/government code for 40% off: GA40CF
GTC Alum code for 15% off: GMALUM15
CUDA Newsletter code for 10% off: GM10CD |
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GTC ALUM COMMENTS |
The tuning strategy sessions and algorithm sessions were excellent, and being able to talk with principle NVIDIA engineers was great. I found the conference very worthwhile. - Bob Arendt, Rincon Research Corp.
I went to GTC for the technical presentations and to connect to other people involved with GPUs. In those respects my experience was excellent. - Domokos Vermes, Worcester Polytechnic Institute
The wide variety of presentation subject matter, even wider variety of attendee backgrounds, cutting edge hardware, and cutting edge software made this all supremely entertaining. - Eric Carlson, University of Alabama
This is the best organized and executed conference I attend. Every year I’ve made a lot of important contacts for new directions for my research. - Peter Lu, Harvard University |
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We look forward to seeing you at GTC 2012 in San Jose! |
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CUDA CALENDAR |
back to the top
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- Innovations for Financial Analytics (Murex)
- Better Chemistry through Quantum Mechanics
- INPAR 2012
- GPU Technology Conference (GTC 2012)
- Intro to GPGPU and CUDA (CINECA)
- Workshop on Emerging Parallel Architectures (WEPA 2012)
- International Mathematica Symposium (University College, London)
- ISC '12
- Micromethods in Protein Chemistry
- International Congress of Quantum Chemistry
- Parallel Computing Summer School (CINECA)
- Computational Chemistry (Gordon Research Conferences)
- Summer School of Advanced Computing (CASPUR)
(To list an event, email: cuda_week_in_review@nvidia.com) |
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CUDA RESOURCES |
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CUDA on the Web |
– Learn more about CUDA on CUDA Zone: www.nvidia.com/cudazone
– See previous issues of CUDA: Week in Review: http://is.gd/cBXbg
– Follow CUDA & GPU Computing on Twitter: www.twitter.com/gpucomputing
– Network with other developers: www.gpucomputing.net
– Stay tuned to GPGPU news and events: www.gpgpu.org
– Check out the NVIDIA Research page: www.nvidia.com/research |
CUDA Recommended Reading |
– CUDA books: http://developer.nvidia.com/cuda-books |
CUDA Recommended Viewing |
– GTC Express: http://www.gputechconf.com/object/gtc-express-webinar.html |
– SC11 presentations: http://www.gputechconf.com/page/gtc-on-demand.html |
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ABOUT CUDA |
CUDA® is a parallel computing platform and programming model invented by NVIDIA. It enables dramatic increases in computing performance by harnessing the power of the graphics processing unit (GPU). NVIDIA provides a complete toolkit for programming on the CUDA architecture, supporting standard computing languages such as C, C++ and Fortran. Send comments and suggestions on the newsletter to: cuda_week_in_review@nvidia.com
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