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CUDA Week in Review Newsletter
Fri., May 16, 2014, Issue #111 Newsletter Home
Welcome to CUDA: Week In Review
News and resources for the worldwide GPU and parallel programming community.


CUDA 6 introduces a new reciprocal hypotenuse function, rhypot(x,y). This provides fast and robust computations of Givens Rotations. Learn more on the Parallel Forall Blog.


Dr. Ren Wu GPU-Accelerated Deep Learning
Our Spotlight is on Dr. Ren Wu, distinguished scientist at Baidu IDL (Institute of Deep Learning). Dr. Wu is known for his pioneering research in using GPUs to accelerate big data analytics as well as his contribution to large-scale clustering algorithms via the GPU. Read the Spotlight.


Women in GPU Computing: Call for Submissions
This summer, NVIDIA will highlight women around the world who are innovators in GPU computing, including women just starting out in their careers. "It's a good way to remind people that women write code, participate in open-source projects and invent things," comments Lorena Barba, CUDA Fellow and associate professor at George Washington University. "It's important to make the technology world more attractive to female students and show them examples of women who are innovators." Learn more.

CUDA 6 Report
The CUDA 6 Performance Report is now available. To learn more, download the PDF or listen to the podcast of NVIDIA's Will Ramey speaking with Nicole Hemsoth of HPCwire.

Allinea Supports CUDA 6
Allinea Software announced that the new version of its debugging tools, Allinea DDT 4.2.1, now offers full support for CUDA 6. Allinea DDT 4.2.1 allows developers to maximize their use of Unified Memory and other new CUDA performance and usability features.

NVIDIA Developer Forums
Join us on the NVIDIA DevTalk forums to ask questions, share your experiences and learn from other developers. You can also ask questions on Stack Overflow, using the 'cuda' tag.


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May 20: Using GPUs for Big Data, A. O'Connor, Exelis
May 22: C++ on GPUs Using OpenACC and PGI Compilers, M. Wolfe
May 28: Intro to CUDA Programming, C. Mason, Acceleware
June 3: Next Steps for Folding@home, V. Pande, Stanford
June 4: Using GPUs in a Holographic Radar System, P. Wurmsdobler, Aveillant


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May 19: Silicon Valley
May 20: Paris
May 20: Moscow
May 29: Singapore
May 29: Boston


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Subscribe to the Parallel Forall RSS feed Parallel Forall:
Adaptive Parallel Computation with CUDA Dynamic Parallelism, A. Adinetz
CUDACast: CUDA 6 Guided Performance Analysis with Visual Profiler, M. Ebersole
CUDA Pro Tip: Fast and Robust Computation of Givens Rotations, M. Harris
Subscribe to NVIDIA RSS feed NVIDIA:
Parallel Lives: Women in GPU Computing, L. Caplinger


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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

Systems Day at Technion - Israel Institute of Technology
  June 9, 2014, Haifa, Israel
(Includes mobile GPU track, co-organized with SagivTech)

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

4-Day GPU Computing Course (SagivTech)
  June 22-25, 2014, Ramat Gan, Israel

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

HPDC ’14
  June 23-27, 2014, Vancouver, Canada

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


GPU Tech Workshop Taiwan (NVIDIA)
  July 8, 2014, Taipei, Taiwan

GPU Tech Workshop SE Asia (NVIDIA)
  July 10, 2014, Singapore

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

GPU Tech Conference Japan (NVIDIA)
  July 16, 2014, Tokyo, Japan

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

CUDA Programming Course (Oxford University)
  July 21-25, 2014, Oxford, UK
Instructor: Mike Giles

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

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.



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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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