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CUDA Week in Review Newsletter
Wed., Sept. 17, 2014, Issue #115 Newsletter Home
Welcome to CUDA: Week In Review
News and resources for the worldwide GPU and parallel programming community.


Always set the current device to avoid multithreading bugs. Learn more on the Parallel Forall blog.


Cris Cecka An Interview with Harvard's Cris Cecka
This week's Spotlight features Cris Cecka, a lecturer and research scientist at the Institute for Applied Computational Science (IACS) at Harvard University. His research focuses on computational mathematics, particularly for interdisciplinary applications in science and engineering. Cris teaches CUDA in Harvard's CS205 course, a core requirement for the IACS Master's program. He is also performing research with the Mathematics Department at the Massachusetts Institute of Technology. Read the Spotlight.


Introducing cuDNN for Machine Learning Developers
Machine Learning, a sub-field of Artificial Intelligence, is becoming pervasive. It's at the foundation of applications such as internet search, fraud detection, image tagging and brain mapping, to name a few. The hottest area in Machine Learning is the area of Deep Neural Networks (DNNs). The success of DNNs has been greatly accelerated with GPU computing.

cuDNN Because of the increasing importance of DNNs in both industry and academia, NVIDIA has introduced a new library for deep neural networks called cuDNN. The cuDNN library makes it easy to obtain state-of-the-art performance with DNNs, along with other important benefits. Learn more.

Cancer Research Funding Announced
The NVIDIA Foundation and the National Cancer Institute have kicked off funding opportunities in the fight against cancer. Up to $2 million is available for projects that leverage the power of computation in the search for a cure. Applications are due Oct. 8. Learn more.

Tell Us Your GPU Story
At SC14, NVIDIA will highlight GPU programming/science stories from around the world. If you are a GPU developer or researcher, tell us how you are using GPUs 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. 10.

CUDA 6.5 Available Now
The CUDA 6.5 Production Release is now available to the public. Download CUDA 6.5.

GPU Technology Conference 2015: Call for Submissions
The Call for Submissions for the GPU Technology Conference (March 17-20, 2015) is open until Oct 6.

Global Impact Award: Now Accepting Applications
The NVIDIA Global Impact Award is an annual grant of $150,000 for groundbreaking work using NVIDIA technology to address social and humanitarian problems. Nominations are due Oct. 31.


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Sept. 17: CUDA 6.5 Performance Overview, J. Cohen
Sept. 24: Convolutional Networks: ML for Computer Perception, Y. LeCun, Facebook & NYU
Sept. 25: HOOMD-blue 1.0: MD on GPUs, J. Anderson, J. Glaser, University of Michigan
Oct. 8: Enabling Next Generation Intelligent Applications, M. Zeiler, Clarifai
Oct. 15: Essential CUDA Optimization Techniques, C. Mason, Acceleware


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Subscribe to the Parallel Forall RSS feed Parallel Forall:
Accelerate Machine Learning with the cuDNN Deep Neural Network Library, L. Brown
CUDA Pro Tip: Always Set the Current Device to Avoid Multithreading Bugs, J. Luitjens
Three Versatile OpenACC Interoperability Techniques, J. Larkin
CUDACasts Episode 20: Getting Started with Jetson TK1 and OpenCV, M. Ebersole
Remote Application Development Using NVIDIA Nsight Eclipse Edition, S. Salian

GPUs Power Deep Learning Winners in World Cup of Image Recognition, S. Jones
NVIDIA Foundation, National Cancer Institute to Distribute Up to $2M to Cancer Researchers, L. Austin


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IEEE Cluster 2014
  Sept. 22-26, 2014, Madrid, Spain

CUDA Course (Acceleware)
  Sept. 23-26, 2014, Frankfurt, Germany


OpenACC Hackathon (ORNL)
  Oct. 17-31, 2014, Oak Ridge, Tenn

Oil & Gas Workshop (Univ. of Houston/OpenACC)
  Oct. 20, 2014, Houston, Texas

Computational Biophysics Workshop (UIUC, Georgia Tech)
  Nov. 3-7, 2014, Atlanta, Georgia

  Nov. 16-21, 2014, New Orleans, Louisiana

CUDA Course (Acceleware)
  Dec. 2-5, 2014, New York
(Finance focus)

(To list an event, email:


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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 Documentation

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

Online Learning

Udacity | Coursera | APC Russia

GPU-Accelerated Libraries

Adding GPU acceleration to an application can be as easy as calling a library function. Check out these high-performance libraries from NVIDIA and partners.

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 Test Drive

Want to try Tesla K40 for free? Sign up here.


Check out our new series of short videos about CUDA.

Tell Us Your CUDA Story

If you are a CUDA developer, tell us how you are using CUDA.

GPU-Accelerated Apps

See updated list of 270+ GPU-accelerated applications.

GPU Meetups

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

CUDA Documentation

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

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.

GPU Computing on Twitter

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


PGI Compilers & Tools

CUDA on the Web

CUDA Spotlights
CUDA Newsletters
GPU Test Drive

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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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