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CUDA Week in Review Newsletter
Wed., Sept. 25, 2013, Issue #101 Newsletter Home


A news summary for the worldwide CUDA, GPGPU and parallel programming community.
CUDA Pro Tip: Use the NVIDIA Tools Extension (NVTX) library to add detailed CPU run-time data to the NVIDIA profiler timeline. Learn more in the Parallel Forall blog.


Dr. Knut Reinert CUDA-Accelerated Genomics
This week’s Spotlight is on Dr. Knut Reinert, a professor at Freie Universitat in Berlin, Germany. Knut and his team focus on the development of algorithms and data structures for the analysis of biomedical mass data.

Read the interview with Knut | Enroll in Knut’s Oct. 22 webinar


Tell Us Your CUDA Story
At SC13, NVIDIA will highlight CUDA stories from around the world. If you are a CUDA developer, tell us how you are using CUDA in 140 characters or less. Your submission will be considered for display in the NVIDIA booth and/or on the NVIDIA website. Respond here by Oct. 11.

New GPU-Accelerated Apps
Check out the updated list of 240+ GPU-accelerated applications, from research and manufacturing to seismic processing and entertainment.

Fast JPEG Codec from Fastvideo
Russia-based Fastvideo released a new JPEG codec for GPUs. It utilizes CUDA to speed up image compression and decompression. Peak performance reaches 6 GB per second (and higher for images loaded into RAM).

Numerical Computations with GPUs
Volodymyr Kindratenko of the University of Illinois is editing a book titled "Numerical Computations with GPUs." It will contain articles on core numerical methods adapted for GPUs. Researchers are invited to submit their work for consideration for inclusion in the book.

HPC Experiment
The Ubercloud HPC Experiment has extended an open invitation to members of the HPC community: "Join us for the 4th Round of the HPC Experiment, where we will apply the cloud computing service model to workloads on remote cluster computing resources in the areas of HPC, computer aided engineering and the life sciences."

HPCwire: Phi and Kepler Run Monte Carlo Race
HPCwire editor Nicole Hemsoth interviews Jorg Lotze, CTO of Xcelerit about recent benchmarking efforts.

GTC 2014 Call for Submissions
Call for Submissions for the GPU Technology Conference (March 24-27, 2014) is open through Sept. 27.

Compute the Cure
The NVIDIA Foundation is awarding up to $200k to a cancer research project. Applications due Oct. 7.

Upcoming Webinars
Sept. 26: Profile OpenGL 4.2 with NVIDIA Nsight Visual Studio Edition 3.1, Jeff Kiel, NVIDIA
Oct. 9: OpenACC 2.0 vs OpenMP 4.0 Comparison, James Beyer, Cray
Oct. 22: Intro to SeqAn, an Open-Source C++ Template Library, Knut Reinert, FU Berlin


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Subscribe to the Parallel Forall RSS feed Parallel Forall:
CUDACasts Episode #10: Accelerate Python on GPUs, by Mark Ebersole
CUDACasts Episode #9: Explore GPU Device Memory, by Mark Ebersole
NumbaPro: High-Performance Python with CUDA Acceleration, by Mark Harris
Subscribe to NVIDIA RSS feed NVIDIA:
HP, NVIDIA Open GPU Technical Center for European Market, by Jens Neuschafer
GPU Acceleration Coming to Java, Says IBM Exec, by Sumit Gupta


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Thomson Reuters, a leading provider of intelligent information for businesses and professionals, seeks senior software engineer for StarMine Quant Analytics project. CUDA skills a plus.


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Want to improve your technical skills? Sign up for Intro to Parallel Programming.
Need CUDA advice? See list of worldwide CUDA trainers and consultants.
Have CUDA questions? Check out NVIDIA DevTalk forums and Stack Overflow.
Require fast access to docs? Visit the CUDA doc library.


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Profile OpenGL 4.2 and NVIDIA Nsight Visual Studio Edition 3.1 (Webinar)
  Sept. 26, 2013
Presenter: Jeff Kiel, NVIDIA


  Oct. 7-11, 2013, Recife, Pernambuco, Brazil
Instructors: A. Roiberg, R. Walker, S. LeGrand, R. Salomon-Ferrer

2-Day CUDA Training (AccelerEyes)
  Oct. 7-8, 2013, Houston, Texas

GPU Computing and Applications (Nanyang Tech. University)
  Oct. 9, 2013, Nanyang, Singapore

2-Day CUDA Training (AccelerEyes)
  Oct. 21-22, 2013, Atlanta, Georgia

Intro to SeqAn, an Open-Source C++ Template Library (Webinar)
  Oct. 22, 2013
Presenter: Knut Reinert, FU Berlin

SC ’13
  Nov. 17-22, 2013, Denver, Colorado

Parallel and Distributed Computing in Geoscience and Remote Sensing
  Dec. 23-26, 2013, Seoul, Korea
Note: IEEE Workshop

(To list an event, email:


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Check out our new series of short videos about CUDA.

GPU-Accelerated Apps

See updated list of 240+ GPU-accelerated applications.

GPU Meetups

Learn about Meetups in your city, or start one up.

The Best of GTC 2013, Online

GTC 2013 featured over 400 sessions on breakthroughs made with GPUs in science, technology, and industry. Experience it by visiting

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.

Online Learning


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:

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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