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| Mon., May 6, 2013, Issue #92 | Newsletter Home |
| Welcome to CUDA: WEEK IN REVIEW, a news summary for the worldwide CUDA, GPGPU and parallel programming community. |
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| CUDA Pro Tip: Did you know you can write flexible kernels with grid-stride loops? Learn more in this Parallel Forall blog post. | |
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CUDA SPOTLIGHT |
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CUDA NEWS |
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CUDA JOB OF THE WEEK |
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| Universidade Federal da Paraiba (UFPB) in Brazil seeks post-doctoral fellow for quantum chemistry and GPU computing, starting immediately. Qualifications include recent PhD in chemistry, physics, math or similar. CUDA experience a plus. Email: gbr@quimica.ufpb(dot)br and santanasidney@quimica.ufpb(dot)br | |||||||||||||||||||||||||||||||||||||
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CUDA EDUCATION |
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| Intro to Parallel Programming: Explore parallel programming for the first time or push your knowledge even further with Intro to Parallel Programming on the Udacity platform. The course runs continuously, meaning you can sign up at any time and work on it at your own pace. The first group of students recently completed the course. Read about the top scorers here. | |||||||||||||||||||||||||||||||||||||
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NEW ON THE BLOGS |
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 Parallel Forall blogHow to Build a GPU-Accelerated Research Cluster, by Pradeep Gupta Write Flexible Kernels with Grid-Stride Loops, by Mark Harris Copperhead: Data Parallel Python, by Brian Catanzaro Finite Difference Methods in CUDA C++, Part 2, by Mark Harris NVIDIA blog Trump Card: Why a Pro Poker Player Bet on CUDA, by Brian Caulfield Better Batting with CUDA, by Brian Caulfield Students, GPUs Sweep Asian Supercomputing Competition, by Roy Kim Thanks to GPUs, Every Movie’s Now a Remake, by Tony Kontzer |
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GPU MEETUPS |
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| Have you been to a Meetup yet? Join one or start your own. Upcoming events: May 8, London - HPC Social May 9, Melbourne, FL - Marketing Tech to Government Customers May 20, New York - GPUs in the Cloud May 20, Silicon Valley - Building GPU Compilers with libNVVM |
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CUDA CALENDAR |
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CUDA RESOURCES |
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ABOUT CUDA |
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| 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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