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CUDA Week in Review Newsletter
Fri., Nov. 8, 2013, Issue #103 Newsletter Home
Welcome to CUDA: Week In Review, news for the worldwide CUDA, GPGPU and parallel programming community.
CUDA Pro Tip: nvprof is a powerful, light-weight profiler that can profile anything on the CUDA platform, including OpenACC and CUDA Python. Read about it on Parallel Forall.


Diego RiveraCUDA-Accelerated Cancer Detection
This week’s Spotlight focuses on Diego Rivera, a senior software engineer at Hologic. Hologic is a leading developer of diagnostic products and medical imaging systems, with an emphasis on serving the healthcare needs of women. Read the Spotlight.


Tesla K20X = High Performance + Energy Efficiency
The Tesla K20X accelerator offers the best of both worlds – high performance and low power usage, now at a great new price. Learn more from your OEM or Tesla Preferred Partner. Try a Tesla K20X for free through the GPU Test Drive program.

New Accelerator Benchmarks
Read what developers are saying about accelerator performance and programmability.

Headed to Denver for SC13?
NVIDIA is hosting a variety of activities at SC13, including the popular GPU Theater, a brand-new Developer Zone and a must-see interactive demo of real-time data analytics.

Tell Us Your CUDA Story
At SC13, NVIDIA will highlight CUDA stories from around the world. If you are a CUDA developer, tell us how you are using CUDA. Your submission will be considered for display. Please respond here.

GTC 2014 Call for Posters Now Open
GTC 14 Call for Posters is open through Jan. 31. For instructions, visit Call for Posters.

Nsight Visual Studio Update
NVIDIA Nsight Visual Studio Edition 3.2 is now available with Windows 8.1 support and improved DirectCompute profiling.

GPU Computing at Penn
Students in Patrick Cozzi’s graduate CIS 565 course - GPU Programming and Architecture - are learning about GPUs, massively parallel algorithms, real-time rendering, and more. Each student completes several projects during the course, in areas such as cloth simulation, n-body simulation, path tracing and rasterization pipelines. Learn more about computer graphics at Penn.

Upcoming Webinars
Nov. 13: Solutions for Energy Exploration, Data Processing, Bright Computing, R-Associates, NVIDIA
Nov. 20: Improve Performance Using the CUDA Memory Model, Chris Mason, Acceleware
Nov. 21: How to Speed Up Financial Risk Management, Cost Efficiently, Thomas Moser, Misys
Dec. 3: CUDA Tools for Optimal Performance and Productivity, Dan Cyca, Acceleware
Dec. 12: GPU-Accelerated Geospatial Line-of-Sight Calculations, F. Suykens, B. Adams, Luciad

Upcoming Meetups
Nov. 7: Paris
Nov. 20: Colorado (Co-located with SC13)
Dec. 2: Silicon Valley
Dec. 11: Boston


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Subscribe to the Parallel Forall RSS feed Parallel Forall:
CUDACasts Episode #10: Accelerate Python on GPUs, by Mark Ebersole
Subscribe to NVIDIA RSS feed NVIDIA:
How Do You Study Flying Snakes? by George Millington
Four Science "Titans" Riding GPUs to Scientific Glory, by Brian Caulfield
21st Century Spyglass Could Save Next Captain Phillips, by Sumit Gupta


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Want to improve your technical skills? Sign up for Intro to Parallel Programming.
Need CUDA advice? See list of worldwide CUDA trainers and consultants.
Have CUDA questions? Check out NVIDIA DevTalk forums and Stack Overflow.
Require fast access to docs? Visit the CUDA doc library.


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4-Day CUDA Course (Acceleware)
  Nov. 12-15, 2013, Houston, Texas

SC ’13
  Nov. 17-22, 2013, Denver, Colorado

F# in Finance
  Nov. 25, 2013, 6:00 pm, London, UK
Presenter: Daniel Egloff
Organizer: Fountainhead Lab

4-Day CUDA Course – Finance Focus (Acceleware)
  Dec. 10-13, 2013, New York, New York

UK Many-Core Developer Conference (University of Oxford)
  Dec. 16, 2013, Oxford, England
Note: Includes CUDA "masterclass" sessions

Parallel and Distributed Computing in Geoscience and Remote Sensing
  Dec. 23-26, 2013, Seoul, Korea
Note: IEEE Workshop

(To list an event, email:


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Check out our new series of short videos about CUDA.

GPU-Accelerated Apps

See updated list of 240+ GPU-accelerated applications.

GPU Meetups

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

The Best of GTC 2013, Online

GTC 2013 featured over 400 sessions on breakthroughs made with GPUs in science, technology, and industry. Experience it by visiting

GPU Test Drive

Want to try Tesla K20 for free? Sign up here.

CUDA Documentation

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

Online Learning


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 Consulting

Training, programming and project development services are available from CUDA consultants around the world. To be considered for inclusion on list, email:

GPU Computing on Twitter

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



CUDA on the Web

CUDA Spotlights
CUDA Newsletters
GPU Test Drive

NVIDIA Newsletters

Sign up for NVIDIA Newsletters, including Media & Entertainment, GeForce, NVIDIA GRID VDI and Shield.


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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