Welcome to CUDA: WEEK IN REVIEW, a news summary for the worldwide CUDA, GPGPU and parallel programming community. |
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CUDA TECH TIP: Need to measure GPU execution time of CUDA kernels and API calls? The most efficient and accurate run-time method is to use CUDA events. Learn more in this Parallel Forall blog post. |
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CUDA SPOTLIGHT |
GPU-Accelerated Visual Effects
This week’s Spotlight is on Vladimir "Vlado" Koylazov, co-founder and head of software development at Chaos Group, developers of the popular V-Ray and V-Ray RT rendering software for artists and designers. Vlado comments: "The increased speed and interactivity enabled by GPU computing allows our users to work more efficiently than ever before."
Read our interview with Vlado Koylazov. |
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CUDA NEWS |
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GPU THESIS WATCH |
Title: Feasibility Study of the ‘Parareal’ Algorithm
Author: Allan S. Nielsen, Technical University of Denmark
Advisor: Dr. Allan P. Engsig Karup and Dr. Jan S. Hesthaven
Lab: GPUlab, DTU Informatics
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CUDA JOB OF THE WEEK |
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NVIDIA is seeking talented CUDA Library Software Engineers to develop performance application libraries and benchmarks for next generation GPUs. These include CUFFT, CURAND and other numerical libraries. |
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FROM THE BLOGOSPHERE |
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New on the Parallel Forall Blog:
Thinking Parallel, Part II: Tree Traversal on the GPU, by Tero Karras
How to Query Device Properties and Handle Errors in CUDA C/C++, by Mark Harris
How to Query Device Properties and Handle Errors in CUDA Fortran, by Greg Ruetsch |
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GPU MEETUPS |
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Find a GPU Meetup in your location, or start one up. Upcoming meetings include:
New York, Nov. 29
Silicon Valley, Dec. 3
Perth, Dec. 5
Brisbane, Dec. 6
Boston, Dec. 14
Paris, Dec. 18
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CUDA CALENDAR |
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Parallel Computing with GPUs and CUDA for Finance (NVIDIA)
Nov. 29, 2012, 5:30 pm, Baruch College, New York, New York
Note: An Introduction for Financial Services Developers |
Parallel Computing Course (SagivTech)
Dec. 2-5, 2012, Ramat Gan, Israel |
Parallel Computing with GPUs and CUDA for Finance (NVIDIA)
Dec. 3, 2012, 5:30 pm, Microsoft, London, UK
Note: An Introduction for Financial Services Developers |
GPUs in the Cloud
Dec. 3-6, 2012, Taipei, Taiwan |
4-Day CUDA Course, with Finance Focus (Acceleware)
Dec. 4-7, 2012, New York, New York
Instructor: Dr. Kelly Goss, Acceleware |
Many-Core Developer Conference (UKMAC 2012)
Dec. 5, 2012, University of Bristol, UK |
CUDA and OpenACC (HPC@LR)
Dec. 6, 2012, Montpellier, France
Note: HPC@LR is the HPC competency center for Languedoc-Roussillon |
Debugging of CUDA 5 Apps with Allinea DDT (Webinar)
Dec. 5, 2012, 10:00 am pacific
By Ian Lumb, Allinea |
An Unlikely Symbiosis: Gaming and Supercomputing (Webinar)
Dec. 11, 2012, 10:00 am pacific
By Sarah Tariq, NVIDIA |
Best Practices for Deploying and Managing GPU Clusters (Webinar)
Dec. 12, 2012, 10:00 am pacific
By Dale Southard, NVIDIA |
Getting Started with ArrayFire: 30-Minute Jump Start (Webinar)
Dec. 13, 2012, noon pacific
Sponsored by AccelerEyes |
2013
Understanding Parallel Graph Algorithms (Webinar)
Jan. 10, 2013, 9:00 am pacific
By Duane Merrill and Michael Garland, NVIDIA |
GPU Tech Conference (GTC 2013)
(To list an event, email: cuda_week_in_review@nvidia.com) |
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CUDA RESOURCES |
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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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