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CUDA Week in Review Newsletter
Mon., Feb. 4, 2013, Issue #88 Newsletter Home
Welcome to CUDA: WEEK IN REVIEW, a news summary for the worldwide CUDA, GPGPU and parallel programming community.
Register for GTC 2013, the world’s premier CUDA developer conference
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GTC 2013
CUDA Newsletter Reader Survey: We want to hear from you
Please take a minute to fill out our reader survey so we can improve the newsletter in 2013. Thanks!
CUDA Tech Tip: Flush denormals with confidence
It pays to understand numerical requirements of your code. You may be able to get a big performance boost by using the compiler command line option “–ftz=true” if you use operations like sqrtf() and rsqrtf() and you don’st need denormal support. Learn more on Parallel Forall.


Monica Syal GPU-Accelerated Brownout Simulations
This week’s Spotlight is on Monica Syal, an aerospace engineer at Sunnyvale, Calif.-based Advanced Rotorcraft Technology (ART).

Monica's responsibilities include development of a real-time pilot-in-the-loop rotorcraft brownout simulation and mitigation methodology for flight simulator applications. Read our interview with Monica Syal


CUDA 5 Performance Report Now Available
Learn how your application can run faster on a Tesla K20 GPU Accelerator, simply by dropping in a GPU-accelerated library.
   • Download the new CUDA 5 Performance Report (PDF 1.06 MB)
   • Register for CUDA 5 Math Library Performance Overview webinar, Wed., Feb. 6

New: SIMD-in-a-Word Source Code
NVIDIA posted new source code for CUDA Registered Developers which provides “SIMD-within-a-word” functionality, useful for simulation and image processing codes.
   • See the DevTalk Forum announcement
   • Join the CUDA Registered Developers program


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Udacity Parallel Programming Course Launches This Week!
Sign up for Intro to Parallel Programming. Learn more about Udacity.

AccelerEyes Training Courses Announced
AccelerEyes has announced CUDA trainings in the U.S. for 2013. Visit AccelerEyes Training.


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Crane, the well-known banknote and stationery company, seeks a Software and Design Engineer. Experience with AutoCAD, Python, C, C++ and CUDA C preferred.


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New on the NVIDIA blog:
Just Mix Water with GPUs..., by Roy Kim

Subscribe to the Parallel Forall RSS feedNew on the Parallel Forall blog:
Using Shared Memory in CUDA C/C++, by Mark Harris

(Subscribe to the Parallel Forall RSS feed)


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Find a GPU Meetup in your location, or start one up. Upcoming meetings include:
Paris, Feb. 18
Silicon Valley, Feb. 25
New York, Feb. 27
Boston, Feb. 28
Brisbane, Feb. 28


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HPC Advisory Council Stanford Conference
  Feb. 7-8, 2013, Stanford, Calif.
Open to the public
Note: NVIDIA's Sarah Tariq to present on scaling applications on large GPU clusters

Intro to CUDA + OpenACC Course
  Feb. 12-14, 2013, Ukraine, Lviv
Sponsored by Applied Parallel Computing LLC

Winter GPU Computing School (Moscow State University)
  Feb. 20-22, 2013, Moscow, Russia

2-Day CUDA Training (AccelerEyes)
  Feb. 25-26, 2013, Houston, Texas


Intro to CUDA + OpenACC Course
  March 4-5, 2013, Hamburg, Germany
Sponsored by Applied Parallel Computing LLC

2-Day CUDA Training (AccelerEyes)
  March 4-5, 2013, Washington, DC

4-Day CUDA Course - Oil & Gas (Acceleware)
  March 12-15, 2013, Houston, Texas
Instructor: Dr. Kelly Goss

HPC Advisory Council
  March 13-15, 2013, Lugano, Switzerland

GPU Tech Conference (GTC 2013)
  March 18-21, 2013, San Jose, Calif.
Special code for CUDA newsletter readers: GM10CD

2-Day CUDA Training (AccelerEyes)
  March 25-26, 2013, Los Angeles, Calif.


4-Day CUDA Course (Acceleware)
  May 7-10, 2013, San Francisco, Calif.
Instructor: Dr. Kelly Goss

(To list an event, email:


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GPU-Accelerated Apps

List of 200+ popular GPU-accelerated scientific and research applications (PDF 402KB).

GPU Test Drive

Want to try Tesla K20 for free? Sign up here.

CUDA Documentation

The new CUDA documentation site includes release notes, programming guides, manuals and code samples.

CUDA Education

Udacity Course
Coursera Course

NVIDIA Developer Forums

Join us on the NVIDIA DevTalk forums to share your experience and learn from other developers. You can also ask questions on Stack Overflow, using the ‘cuda’ tag.

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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