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CUDA Week in Review Newsletter
Fri., April 25, 2014, Issue #110 Newsletter Home
Welcome to CUDA: Week In Review
News and resources for the worldwide GPU and parallel programming community.


CUDA 6 XT library interfaces can automatically scale large matrix multiplies and 2D and 3D FFTs to multiple GPUs. Learn more on the Parallel Forall blog.


Dr. Dan CiresanGPU-Accelerated Deep Neural Networks
This week’s Spotlight is on Dr. Dan Ciresan, a senior researcher at IDSIA in Switzerland and a pioneer in using CUDA for Deep Neural Networks (DNNs). Dan’s methods have won international acclaim on topics such as recognizing handwritten Chinese characters and detecting mitosis in cancer histology images. Read the Spotlight.


The CUDA 6 Production Release is now available for download. This version further simplifies parallel programming with new features such as Unified Memory; Drop-in Libraries; and Multi-GPU Scaling. To learn more, attend these CUDA 6 webinars:

Bioinformatics + CUDA
Interested in bioinformatics? Check out the new NVBIO page on CUDA Zone. NVBIO is a library of reusable components designed by NVIDIA to accelerate bioinformatics applications using CUDA.

INCITE Call for Proposals
Accelerate your science on Titan, world’s #1 supercomputer for open science, by harnessing more than 20 petaflops of parallel processing using GPUs. Open to all across the globe. Get started here.

C-3PO and Machine Learning
Technologist Rob Farber recently taught a course on OpenACC and CUDA to college students at KAUST in Saudi Arabia. In addition, he had the opportunity to introduce parallel programming to high school and middle school students. He used the character C-3PO from Star Wars to represent machine learning and demonstrated how a GPU can learn to read. See more on Rob’s new blog: TechEnablement.


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May 1: CUDA 6 Unified Memory, M. Ebersole
May 7: CUDA 6 Drop-in Performance Optimized Libraries
May 13: Overview of AMBER 14, R. Walker, UCSD, S. Le Grand, Amazon, A. Roitberg, Univ. of Florida
May 14: CUDA 6 Performance Review, J. Cohen
May 22: C++ on GPUs Using OpenACC and PGI Compilers, M. Wolfe
June 3: Next Steps for Folding@home, V. Pande, Stanford


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Subscribe to the Parallel Forall RSS feed Parallel Forall:
Compilation/Linking of CUDA C++ Device Code, T. Scudiero, M. Murphy
5 Powerful New Features in CUDA 6, M. Harris
Subscribe to NVIDIA RSS feed NVIDIA:
How a Team of Engineers Helps the Best Developers Get Even Better, L. Gomes


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4-Day CUDA Course (Acceleware)
  May 6-9, 2014, Calgary, AB, Canada

2-Day Workshop on Computer Vision and GPUs (JGPU14)
  May 8-9 May, 2014, Alicante, Spain

IEEE Int’l Parallel & Distributed Processing Symposium
  May 19-23, 2014, Phoenix, Arizona

PRACE Scientific and Industrial Conference
  May 20-22, 2014, Barcelona Spain

Amber Workshop 2014
  June 2-7, 2014, Barcelona, Spain
Instructors: Ross Walker & Adrian Roitberg

1-Day CUDA Course (Delft University of Technology)
  June 5, 2014, Delft, Netherlands
Instructors: Kees Vuik & Kees Lemmens

Intro to GPGPU Programming (XSEDE)
  June 16-20, 2014
(Virtual course delivered at multiple locations)

ISC ’14
  June 22-26, 2014, Leipzig, Germany

4-Day CUDA Course (Acceleware)
  June 24-27, 2014, San Jose, Calif.

Programming Heterogeneous Systems in Physics (Workshop)
  July 14-15, 2014, Jena, Germany

GPUs and Scientific Applications (University of Alicante)
  July 21-24, 2014, Alicante, Spain

HPCS 2014
  July 21-25, 2014, Bologna, Italy

(To list an event, email:


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Online Learning

Udacity | Coursera | APC Russia

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

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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.



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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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