CUDA Week in Review Newsletter Homepage
Fri., Nov. 30, 2012, Issue #85 Newsletter Home
Welcome to CUDA: WEEK IN REVIEW, a news summary for the worldwide CUDA, GPGPU and parallel programming community.
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.


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.
Vlado Koylazov Chaos Group


Top Video Picks
Check out these timely presentations from the GPU Technology Theater at SC12:

Guest Speakers
Buddy Bland, ORNL: Titan: ORNL’s New Computer System for Science (19 mins)
Travis Oliphant, Continuum Analytics: Compiling Python to the GPU with Numba (20 mins)
John Urbanic, Pittsburgh SC: Bringing Supercomputing to the Masses with OpenACC (23 mins)
Wen-Mei Hwu, Univ. of Illinois: Kepler GPUs in Blue Waters (28 mins)

NVIDIA Speakers
Don Becker: CARMA: Developments in Power Efficient Computing (20 mins)
Bill Dally: The Road to Exascale (22 mins)
Mark Harris: New Features in CUDA 5 (26 mins)
Mark Ebersole: Intro to CUDA C/C++ (28 mins)
Ian Buck: CUDA: Past, Present and Future (30 mins)
Stephen Jones: Inside the Kepler Architecture (32 mins)

CUDA Documentation
Based on your feedback, NVIDIA has launched a brand new CUDA documentation site. It includes release notes, programming guides, manuals and code samples.


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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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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Subscribe to the Parallel Forall RSS feed 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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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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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

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


Understanding Parallel Graph Algorithms (Webinar)
Jan. 10, 2013, 9:00 am pacific
By Duane Merrill and Michael Garland, NVIDIA

GPU Tech Conference (GTC 2013)
March 18-21, 2013, San Jose, Calif.
Call for Posters
Developer Tutorials
Session Samples

(To list an event, email:


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NVIDIA Tesla K20 and K20X

NVIDIA Tesla K20 and K20X GPU Accelerators are now available.

GPU-Accelerated Apps

List of 200+ popular GPU-accelerated scientific and research applications.
Web | PDF

CUDA Education

NEW Coursera Course
NEW Udacity Course
NEW Book: CUDA Programming, by Shane Cook

NVIDIA Developer Forums

The new NVIDIA developer forums are now live. Join the new online community to learn from other developers and share your experience.

CUDA Consulting

Training, programming, and project development services are available from CUDA consultants around the world. To be considered for inclusion on list, email: (with CUDA Consulting in subject line).

GPU Computing on Twitter

For daily updates about GPU computing and parallel programming, follow @gpucomputing on Twitter.


CUDA 5 survey

CUDA on the Web

CUDA Spotlights
CUDA Newsletters
GPU Test Drive


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
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