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CUDA Week in Review Newsletter
Thurs., Aug. 21, 2014, Issue #114 Newsletter Home
Welcome to CUDA: Week In Review
News and resources for the worldwide GPU and parallel programming community.


Pointer aliasing is an important topic to understand when considering optimizations for your C/C++ code. In this tip we describe a simple way to alter your code so aliasing does not harm CUDA application performance. Read about it on the Parallel Forall blog.


Dr. Michela Taufer GPU-Accelerated Science
This week's Spotlight is on Dr. Michela Taufer of the University of Delaware. Michela heads the Global Computing Lab (GCLab), which focuses on high-performance computing and its application to the sciences.

Michela comments: "My team's work is all about rethinking application algorithms to fit on the GPU architecture in order to get the most out of the GPU's computing power, while preserving the scientific accuracy of the simulations. This has resulted in many exciting achievements!" Read the Spotlight.


CUDA 6.5 Available Now
The CUDA 6.5 Production Release is now available to the public. Highlights include support for 64-bit ARM-based systems and Microsoft Visual Studio 2013 (VC12). 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 now open. If you use GPUs in your work, science or research, consider submitting a proposal to share your accomplishments with a global audience.

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. Researchers, non-profits and universities anywhere in the world may apply. Nominations are due Oct. 31.

CUDA Coding Challenge Launched in India
The NVIDIA team in India has launched a CUDA Coding Challenge, an India-wide contest to encourage parallel programming innovation. The challenge is open through Aug. 31.

New Video: GPUs and MATLAB
In a new video from MathWorks, Dan Doherty describes how MATLAB users can leverage GPUs to accelerate computationally-intensive applications in areas such as image processing, signal processing and computational finance. Dan discusses the GPU-enabled functionality in MATLAB and add-on toolboxes, and demonstrates how to integrate custom CUDA kernels into MATLAB.


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Aug. 26: CUDA 6.5 Overview and Features, U. Kapasi
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. 15: Essential CUDA Optimization Techniques, C. Mason, Acceleware


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Subscribe to the Parallel Forall RSS feed Parallel Forall:
10 Ways CUDA 6.5 Improves Performance and Productivity, M. Harris
Unified Memory: Now for CUDA Fortran Programmers, M. Harris
CUDA Pro Tip: Optimize for Pointer Aliasing, J. Appleyard
Accelerate R Applications with CUDA, P. Zhao
Calling CUDA-accelerated Libraries from MATLAB: A CV Example, J.Knight, MathWorks

NYU Explores Frontier of Data Science, Joins New CUDA Centers, C. Cheij


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Euro-Par 2014
  Aug. 25-29, 2014, Porto, Portugal

CUDA Course (Acceleware)
  Sept. 2-5, 2014, Houston, Texas
(Oil and Gas focus)

GPUs in Databases (ADBIS Workshop)
  Sept. 7, 2014, Ohrid, Republic of Macedonia

GPU Computing for Oil & Gas (EAGE Workshop)
  Sept. 7-10, 2014, Crete, Greece

ICPP-2014 (Conference on Parallel Processing)
  Sept. 9-12, 2014, Minneapolis, Minn

GPU Computing in Physics and Astrophysics
  Sept. 15-17, 2014, Rome, Italy
Presenters include Massimiliano Fatica, NVIDIA

Deep Learning Unbounded: Intelligence as a Service
  Sept. 16, 2014, Stanford, Calif.
Sponsored by VLAB

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.



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CUDA Spotlights
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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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