Welcome to CUDA: Week In Review
News and resources for the worldwide GPU and parallel programming community. |
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CUDA PRO TIP |
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. |
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CUDA SPOTLIGHT |
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. |
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CUDA NEWS |
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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UPCOMING GPU WEBINARS |
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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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NEW ON THE BLOG |
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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
NVIDIA:
NYU Explores Frontier of Data Science, Joins New CUDA Centers, C. Cheij
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CUDA CALENDAR |
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AUGUST-SEPTEMBER
Euro-Par 2014
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Aug. 25-29, 2014, Porto, Portugal |
CUDA Course (Acceleware)
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Sept. 2-5, 2014, Houston, Texas
(Oil and Gas focus) |
GPUs in Databases (ADBIS Workshop)
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Sept. 7, 2014, Ohrid, Republic of Macedonia |
GPU Computing for Oil & Gas (EAGE Workshop)
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Sept. 7-10, 2014, Crete, Greece |
ICPP-2014 (Conference on Parallel Processing)
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Sept. 9-12, 2014, Minneapolis, Minn |
GPU Computing in Physics and Astrophysics
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Sept. 15-17, 2014, Rome, Italy
Presenters include Massimiliano Fatica, NVIDIA |
Deep Learning Unbounded: Intelligence as a Service
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Sept. 16, 2014, Stanford, Calif.
Sponsored by VLAB |
IEEE Cluster 2014
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Sept. 22-26, 2014, Madrid, Spain |
CUDA Course (Acceleware)
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Sept. 23-26, 2014, Frankfurt, Germany |
OCTOBER-DECEMBER
OpenACC Hackathon (ORNL)
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Oct. 17-31, 2014, Oak Ridge, Tenn |
Oil & Gas Workshop (Univ. of Houston/OpenACC)
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Oct. 20, 2014, Houston, Texas |
Computational Biophysics Workshop (UIUC, Georgia Tech)
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Nov. 3-7, 2014, Atlanta, Georgia |
SC14
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Nov. 16-21, 2014, New Orleans, Louisiana |
CUDA Course (Acceleware)
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Dec. 2-5, 2014, New York
(Finance focus) |
(To list an event, email: cuda_week_in_review@nvidia.com) |
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CUDA RESOURCES |
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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: cuda_week_in_review@nvidia.com. |
GPU Test Drive |
Want to try Tesla K40 for free? Sign up here. |
CUDACasts |
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. |
Downloads |
CUDA
Nsight |
CUDA on the Web |
CUDA Spotlights
CUDA Newsletters
CUDA Zone
GPU Test Drive
GPUComputing.net
GPGPU.org
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NVIDIA Newsletters |
Sign up for NVIDIA Newsletters, including Media & Entertainment, GeForce, NVIDIA GRID VDI and Shield.
Please fill out our reader survey so we can improve in 2014. Thanks! |
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ABOUT CUDA |
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 cuda_week_in_review@nvidia.com
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Copyright © 2014 NVIDIA Corporation. All rights reserved. 2701 San Tomas Expressway, Santa Clara, CA 95050. |
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