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CUDA Week in Review Newsletter
Fri., May 24, 2013, Issue #93 Newsletter Home
Welcome to CUDA: WEEK IN REVIEW, a news summary for the worldwide CUDA, GPGPU and parallel programming community.
CUDA Pro Tip: New resources for advanced developers! CUB open-source library | Modern GPU project


Dylan Jackson GPU-Accelerated IRIS Model Fitting
This week’s Spotlight is on Dylan Jackson of MIT Lincoln Lab. His master’s project at Boston University explored the application of GPU computing to the LED-based IRIS (Interferometric Reflectance Imaging Sensor) system.

Read our interview with Dylan Jackson.


Nsight Visual Studio Edition 3.0 Released
NVIDIA Nsight Visual Studio Edition 3.0 is now publicly available. New features include the ability to debug OpenGL applications and support for the Kepler GK110 architecture in Tesla K20 and GeForce GTX TITAN.

New CUDA Centers
Institutions from 11 countries have joined the roster of CUDA Research Centers and CUDA Teaching Centers, bringing the total to 273 in 42 nations. Work performed at the Centers includes 3D genome sequencing; graphics and numeric programming; and systems for heterogeneous nodes and clusters.

INCITE Call for Proposals
Accelerate your research on Titan, the world’s #1 supercomputer for science, by harnessing more than 20 petaflops of parallel processing using GPUs. The INCITE program is open to US- and non-US-based researchers and organizations needing large allocations of computer time and data storage to pursue transformational advances in science and engineering. Find out more.

Upcoming Workshops and Webinars
May 23-24: CUDA Workshop for Defense/Intelligence, Herndon, Virginia. Sponsored by NVIDIA, HP and Acceleware. Designed for programmers in the defense industry who want to develop skills in application design and optimization to fully leverage parallel computing.

May 28-29: CUDA Training by AccelerEyes, Atlanta, Georgia. Workshop on writing and optimizing applications for GPU acceleration. Includes use of laptop with CUDA-capable GPU; choice of Linux or Windows OS; manual and programming exercises; certificate of completion.

June 11: OpenCV: Accelerated Computer Vision using GPUs (webinar). Learn from Shalini Gupta of NVIDIA how the powerful OpenCV library has been accelerated with CUDA.

June 12: Accelerating Existing Monte Carlo Code (webinar). Hicham Lahlou, CEO and co-founder of Xcelerit, will discuss real-world applications of GPUs in risk management.


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The U.S. Air Force Research Lab seeks post-doc research candidates to work on optimal code development on real-time HPC GPU clusters for CFD, computational electromagnetics (radar), and infrared/laser/atmospheric transmission and signature modeling. Candidates will work with Air Force and DoD contractor researchers to transform legacy codes to exploit NVIDIA Kepler and Crossfield RDMA backplane capabilities for real-time HPC cluster hypersonic vehicle modeling. Open to U.S. citizens and permanent residents. Research Associateship Programs Overview | Position Description


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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.


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Have you been to a Meetup yet? Join one or start your own. Upcoming events:
Sydney, Australia, May 27. Topic: Erlang Programming Language and GPU Computing
Melbourne, Australia, May 30. Topic: Kepler K20 and GeForce Titan; GPUs and 3D printing
Boulder, Colorado, May 30. Topic: Python on an NVIDIA GPU (by Mark Ebersole)
Rome, Italy, June 21. Topic: GPU Computing


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2-Day CUDA Workshop for Defense/Intelligence (NVIDIA, HP, Acceleware)
  May 23-24, 2013, Herndon, Virginia

2-Day CUDA Training (AccelerEyes)
  May 28-29, 2013, Atlanta, Georgia


Intro to CUDA Programming (PRACE, BSC)
  June 3-7, 2013, Barcelona, Spain

Rencontre des Chimistes Theoriciens du Grand-Est
  June 7-8, 2013, Reims, France

2-Day CUDA Training (AccelerEyes)
  June 10-11, 2013, Baltimore-Washington, DC

CUDA Workshop (Istanbul Technical University)
  June 10-12, 2013, Istanbul, Turkey

OpenCV: Accelerated Computer Vision using GPUs (GTC Express Webinar)
  June 11, 2013
Presenter: Shalini Gupta, NVIDIA

Accelerating Existing Monte Carlo Code: CVA, CCR Examples (GTC Express Webinar)
  June 12, 2013
Presenter: Hicham Lahlou, Xcelerit

CUDA and OpenACC Training at UAM (Universidad Autonoma de Madrid)
  June 12-13, 2013, Madrid, Spain

International Supercomputing Conference (ISC)
  June 16-20, 2013, Leipzig, Germany
Hands-On CUDA tutorial by NVIDIA, June 16, 9:00 am
Hands-On OpenACC tutorial by NVIDIA, June 16, 2:00 pm

GPU Accelerated XenDesktop for Designers and Engineers (GTC Express Webinar)
  June 20, 2013

4-Day CUDA Course (Acceleware)
  June 25-28, 2013, Calgary, AB, Canada
Instructor: Dr. Kelly Goss


HPC@LR Sumer School (University of Montpellier 2)
  July 3-5, 2013, Montpellier, France

PUMPS Summer School
  July 8-12, 2013, Barcelona, Spain
Co-Directors: Mateo Valero (BSC, UPC) and Wen-mei Hwu (University of Illinois)

GPU Summer School (University of Alicante)
  July 22-24, 2013 Alicante, Spain

4-Day CUDA Course (Acceleware)
  July 29-August 1, 2013, San Jose, Calif
Instructor: Dr. Kelly Goss

GPU Technology Conference Japan
  July 30, 2013, Tokyo, Japan

(To list an event, email:


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Webinar Replay

GROMACS and Kepler GPUs, by Erik Lindahl, Stockholm University (1:16:47)

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 Online Courses

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 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 to
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