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Tygodniowy newsletter “CUDA: Week in Review.” – 23.12.2011

 

Fri., Dec. 23, 2011, Issue #67

Click     here for online version

 

CUDA: WEEK IN REVIEW

Welcome to the online newsletter for the worldwide CUDA,         GPGPU and parallel programming ecosystem.

EDITOR’S NOTE
Happy Holidays!
Reader Survey
CUDA TOP STORIES
Thank you to CUDA         Spotlights
Interview Links
 
CONTENTS
EDITOR’S NOTE
CUDA SPOTLIGHT
CUDA CALENDAR
CUDA RESOURCES
Sign         up to be a CUDA Registered Developer
Follow         @GPUComputing on Twitter
See         previous issues of CUDA: Week in Review

 

 

EDITOR’S NOTE

Happy holidays and best       wishes for a joyous and productive new year!

The CUDA: Week in Review newsletter will resume in January 2012.
To help us continue to deliver relevant information to you, please fill out this brief survey: https://www.surveymonkey.com/s/NV-CUDA-News.

Thank you!

 

CUDA SPOTLIGHT

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As the end of the year draws near, we would like to recognize and thank our     CUDA Spotlights:

July –     December 2011

Anders Eklund, Linkoping University: GPU-Accelerated Medical Imaging

Jeffrey Vetter, ORNL & Georgia Tech: GPU-Accelerated Real Science

William Putman, NASA: GPU-Accelerated Climate Simulation

Mehdi Raessi, UMass-Dartmouth: GPU-Accelerated Multi-Phase Flow

Alexander Doronin, Univ. of Otago: GPU-Accelerated Biophotonics

Ross Walker, UC San Diego: GPU-Accelerated Molecular Dynamics

Denis Bastieri, University of Padua: GPU-Accelerated Astronomy

Jesse Rosenzweig, Elemental: GPU-Accelerated Video Processing

Vincent Natoli, Stone Ridge Technology: GPU-Accelerated Science

January –     June 2011

Axel Kohlmeyer, Temple University: GPU-Accelerated Discovery

John Humphrey, EM Photonics: GPU-Accelerated Linear Algebra

Wu-Chun Feng, Virginia Tech: Compute the Cure

Kang Zhang, Johns Hopkins University: Tools For Microsurgeons

Vitaliy Lomakin, UCSD: GPU-Accelerated Electromagnetic Simulators

Ren Wu, HP Labs: GPU-Accelerated Large-Scale Analytics

Stephen Fried, Microway: GPU Computing Momentum

Andre Brodtkorb, SINTEF: Modeling the Real World in Real Time

Andrew Sheppard: GPUs in the Big Apple

Allan Engsig-Karup, DTU: Simulating Waves in Denmark

Joshua Adelman, Univ. of Pittsburgh: Molecular Research + GPUs

2010

Martin Peniak, Univ. of Plymouth: Developing Robots with CUDA

Douglas Miles, PGI: PGI Partnership

Arnaud Mazurier, ERM & Francois Curnier, Digisens: 2.1 Billion Years Ago

Ben Jiang, Nexiwave: Voice Search Accelerated by CUDA

(To suggest a CUDA Spotlight, email cuda_week_in_review@nvidia.com)

 

CUDA Calendar

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- Debugging Workshop for CUDA       4.1 using Allinea DDT (Webinar)

Jan. 10, 2012, 10 am PT
Presenter: David Lecomber, CTO, Allinea Software
https://www2.gotomeeting.com/register/481122818

- GPU Computing with CUDA and PGI Directives – Applied       Parallel Computing

Jan. 16-18, 2012, Munich, Germany
http://cuda-training.eventbrite.com/

- Intro to Bright Cluster Manager – Advanced Clusters Made       Easy (Webinar)

Jan. 19, 2012, 10 am PT
https://www2.gotomeeting.com/register/742292402

- CUDA Programming 1-Day Course – Delft University of       Technology

Feb. 3, 2012, Delft, Netherlands
http://ta.twi.tudelft.nl/users/vuik/gpu.html

- GPU Computing with CUDA and PGI Directives – Applied       Parallel Computing

Feb. 5-8, 2012, Dublin, Ireland
http://cuda-course.eventbrite.com/

- PRACE Winter School at CINECA

Hybrid Programming on Massively Parallel Architectures
Feb. 6-11, 2012, Bologna, Italy
http://www.cineca.it/page/prace-winter-school
http://www.cineca.it/en/page/training-and-courses

- GPGPU5

March 3, 2012, London, England
http://www.ece.neu.edu/GPGPU/GPGPU5/

- SPIE: Defense, Security and Sensing

April 23-27, 2012, Baltimore, Maryland
http://spie.org/x6765.xml

- INPAR 2012

May 13-14, 2012, 2012, San Jose, Calif.
http://www.innovativeparallel.org/

- GPU Technology Conference (GTC 2012)

May 14-17, 2012, San Jose, Calif.
http://www.gputechconf.com/

- Workshop on Emerging Parallel Architectures (WEPA 2012)

June 2-4, Omaha, Nebraska
http://www.staff.uni-mainz.de/schmi033/

(To list an event, email: cuda_week_in_review@nvidia.com)

 

CUDA RESOURCES

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Downloads

– CUDA Toolkit: www.nvidia.com/getcuda
– Parallel Nsight: http://developer.nvidia.com/nvidia-parallel-nsight

Webinars

– CUDA: www.nvidia.com/webinars
– Parallel Nsight: http://developer.nvidia.com/developer-webinars

CUDA     Registered Developer Program

– Sign up: www.nvidia.com/paralleldeveloper

CUDA     GPUs

– List of CUDA-enabled GPUs: http://developer.nvidia.com/cuda-gpus

CUDA     on the Web

– Learn more about CUDA on CUDA Zone: www.nvidia.com/cuda
– See previous issues of CUDA: Week in Review: http://is.gd/cBXbg
– Follow CUDA & GPU Computing on Twitter: www.twitter.com/gpucomputing
– Network with other developers: www.gpucomputing.net
– Stay tuned to GPGPU news and events: www.gpgpu.org
– Check out the NVIDIA Research page: www.nvidia.com/research

CUDA     Recommended Reading

– CUDA books: http://www.nvidia.com/object/cuda_books.html

CUDA     Recommended Viewing

– GTC Express: http://www.gputechconf.com/object/gtc-express-webinar.html
– SC11 presentations: http://www.gputechconf.com/page/gtc-on-demand.html
 

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     as well as APIs such as OpenCL and DirectCompute. Send comments and     suggestions to: cuda_week_in_review@nvidia.com
 
You are receiving this email because you have previously     expressed interest in NVIDIA products and technologies. Click here     to opt in specifically to CUDA: Week in Review.

 

Feel free to forward this email to customers, partners and     colleagues.

Copyright © 2011 NVIDIA Corporation. All rights reserved. 2701 San Tomas     Expressway, Santa Clara, CA 95050.

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Tygodniowy newsletter “CUDA: Week in Review.” – 02.12.2011

 

Fri., Dec. 2, 2011, Issue #66

Click     here for online version

 

CUDA: WEEK IN REVIEW

Welcome to the online newsletter for the worldwide CUDA,         GPGPU and parallel programming ecosystem.

CUDA SPOTLIGHT
Anders Eklund, Linkoping University
CUDA TOP STORIES
New CUDA         Book
SC11 News         Wrap-Up
Accelerate         Apps with Directives
GTC Asia Just         Around the Corner
Help Name         the New ‘CUDA on ARM Dev Kit’
Map the World         of GPU Computing
New CCOEs
CONTENTS
CUDA SPOTLIGHT
CUDA DEVELOPER NEWS
NEW ON THE BLOG
REPLAY OF THE WEEK
CUDA JOBS
GPU MEETUPS
CALLS FOR PAPERS
CUDA CALENDAR
CUDA RESOURCES
Sign         up to be a CUDA Registered Developer
Follow         @GPUComputing on Twitter

 

 

CUDA SPOTLIGHT

GPU-Accelerated Medical       Image Processing
For this week’s Spotlight we interviewed Anders Eklund, a Ph.D.       student at Linkoping University in Sweden. Anders is affiliated with the       University’s Center for Medical Image Science and Visualization (CMIV). Here’s a preview of our conversation:

NVIDIA: Anders, what is your       research focused on?
Anders: I work       with algorithms for medical image processing, such as image registration       and image denoising. My research is especially focused on functional       magnetic resonance imaging (fMRI), where you try to find brain activity       from magnetic resonance images (MRIs) of the brain.

My interests include brain-computer interfaces (BCI) with real-time fMRI,       where the fMRI data is processed in real-time as the subject is in the MR       scanner. A brain-computer interface could help people communicate who are       paralyzed or suffer from Locked-in syndrome.

NVIDIA: How does GPU computing play a role in your work?
Anders: GPU       computing is very important for me and the research group in which I       work, as many of the algorithms that we develop are very computationally       demanding. To be able to develop, evaluate and improve an algorithm, it       really helps if the processing time for one run can be reduced from       minutes to seconds, or from hours to minutes.
NVIDIA: As computing becomes more powerful, what can we look       forward to?
Anders: One       exciting trend within medical imaging is to move the processing of the       data into the surgery room, such that the medical doctors can get       real-time feedback during surgery.
- Read the full interview with Anders Eklund
- See video on 4D Image Denoising
- See video on the Brain-Computer Interface

Editor’s Note: Anders will present on 4D medical image processing at GTC     2012 in May in San Jose, Calif.

(To suggest a CUDA Spotlight, email cuda_week_in_review@nvidia.com)

 

CUDA DEVELOPER NEWS

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New CUDA Book

Congrats to     author Rob Farber on the release of “CUDA Application Design and     Development.” Published by Morgan Kaufmann and available on Amazon,     this book is designed for software developers who want to leverage GPU     programming with CUDA to increase efficiency.
- See: http://amzn.to/rQZrqS

SC11 News Wrap–Up

This year’s     Supercomputing conference (SC11) in Seattle was action-packed. Here is a     roundup of some of the news highlights:
- OpenACC Programming Standard for Parallel Computing     Unveiled
- BSC to Deploy World’s First ARM-Based CPU/GPU Hybrid     Supercomputer
- NVIDIA Tesla GPUs to Accelerate NCSA Blue Waters     Supercomputer

Accelerate Apps Easily with Directives on GPUs

As part of     the recently announced “2X in 4 Weeks” program, Professor Amin     Kayali from the University of Houston accelerated his micromagnetic     simulation code by 20X in less than two days by inserting directives, or     “compiler hints,” into his CPU code. The compiler uses these     directives to map compute-intensive portions of the code to the GPU. Want     to accelerate your code? To help you get started, NVIDIA and PGI are     offering a free 30-day license of the directives-based PGI Accelerator     compiler.
- See: http://www.nvidia.com/object/tesla-2x-4weeks-guaranteed.html?cid=dev#19

GTC Asia Just Around the Corner

The next GPU     Technology Conference (GTC) will be held in Beijing on Dec. 14-15. The     event will be kicked off with a keynote by NVIDIA CEO Jen-Hsun Huang,     followed by a great line-up of speakers from the Chinese Academy of     Sciences, Harvard, HP Labs, Tokyo Institute of Technology, Tsinghua     University and other leading organizations.
- See: http://www.gputechconf.cn/page/home-en.html

Help Name the New ‘CUDA on ARM Dev Kit’

At SC11 we announced plans for an ARM-based GPU computing     development kit to support the growing demand for energy-efficient HPC     initiatives. The kit will feature a quad-core NVIDIA Tegra 3 ARM CPU     accelerated by a discrete NVIDIA GPU. We are very excited about this     technology and are looking for the perfect codename. Call up your creative     juices and submit an idea. If your suggestion is chosen, you will receive a     free Dev Kit when it launches next year!
- See: http://bit.ly/cudaarmnews

 

NEWS     FROM ACADEMIA

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Map the World of GPU Computing

If your     university or research organization has a GPU compute cluster, let the     world know about it by adding it to the new GPU Computing map. For info,     read the blog post by NVIDIA’s Devang Sachdev.
- See: http://bit.ly/sE86d3

New CCOEs

Two new institutions have been named CUDA Centers of     Excellence: The Barcelona Supercomputing Center and Lomonosov Moscow State     University. The CUDA Center of Excellence designation is the highest honor     given to institutions for ground-breaking work leveraging NVIDIA GPUs and     CUDA.
- See: http://bit.ly/vAhZew

 

NEW ON THE BLOG

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Tokyo Tech Nabs Gordon Bell Prize, by Sumit Gupta
Exascale: An Innovator’s Dilemma, by Andy Walsh
GPUs Give Students Edge in SC11 Cluster Competition, by     Andy Walsh
 

REPLAY OF THE WEEK

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NEW: Our pick for this     week is: Why     the Future of HPC Will Be Green (SC11) by Steve Scott,     NVIDIA
- See: http://nvidia.fullviewmedia.com/fb/nv-sc11/tabscontent/archive/313-wed-scott.html
 

CUDA JOBS

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NEW: Cal     Tech is seeking a Computational Scientist to engineer     scientific software to make effective use of accelerators, particularly     GPUs. Initial responsibility will be optimizing codes to exploit a large     new hybrid (CPU/GPU) cluster in the Division of Geological and Planetary     Sciences. Apps include Bayesian models of fault slip during large     earthquakes, inverse models of the Earth’s interior structure, large-scale     remotely sensed image processing and models for use in rapid tsunami early     warning systems.
- See: https://jobs.caltech.edu/applicants/jsp/shared/Welcome_css.jsp     (Note: Search on ‘computational scientist’)

(To submit a job listing, email cuda_week_in_review@nvidia.com)

 

GPU MEETUPS

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The GPU Meetups     offer a great way to learn about GPU computing and meet interesting people     in a relaxed environment:

Silicon Valley GPU Meetup, Mon., Dec. 5, 6:15 pm
New York GPU Meetup, Thurs., Dec. 8, 6:00 pm (Special       topic: The Business of GPUs)
Brisbane GPU Meetup, Australia, Thurs., Dec. 15, 6:00       pm

(Would you like to start a Meetup? Email cuda_week_in_review@nvidia.com)

 

CALLS FOR PAPERS AND POSTERS

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GTC U.S. 2012 (May 14-17)
Poster deadline: Dec. 8
http://www.gputechconf.com/page/participate.html
https://gtc-submissions.confreg.com/
 

CUDA Calendar

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December 2011

 

- AGU (American Geophysical       Union) Meeting

Dec. 5, 2011, San Francisco
Session on High-Res Modeling Using GPU and Many-Core         Architectures
http://sites.agu.org/fallmeeting/scientific-program/session-search/530

- Intro to GPU Programming Workshop — La Maison de la       Simulation

Dec. 5-9, 2011, France
http://www.maisondelasimulation.fr/index.php

- NEW: CUDA Training by Acceleware with Microsoft

Dec. 6-9, 2011, Calgary, Canada
Trainer: Michael Durocher
http://www.acceleware.com/dec6calgary

- NEW: CUDA Training by T-Platforms and Moscow State University

Dec. 12-16, 2011, Moscow
Conducted by Applied Parallel Computing
http://www.t-platforms.com/about-company/cuda.html

- GTC Asia

Dec. 14-15, 2011, Beijing, China
Featuring the latest GPU computing breakthroughs, demos         and presentations.
http://www.gputechconf.cn/page/home-en.html
http://www.gputechconf.cn/home.html

- LibJacket CUDA Library for Maximus — AccelerEyes (Webinar)

Dec. 15, 2011
Learn to integrate computations with visualizations in a         CUDA-based app through simple visualization functions for plotting,         image and volume rendering, and more.
http://bit.ly/rdZ8pHs

2012

- CUDA Programming 1-Day Course       — Delft University of Technology

Feb. 3, 2012, Netherlands
http://ta.twi.tudelft.nl/users/vuik/gpu.html

- NEW: PRACE Winter School at CINECA

Hybrid Programming on Massively Parallel Architectures
Feb. 6-11, 2012, Bologna, Italy
http://www.cineca.it/page/prace-winter-school
http://www.cineca.it/en/page/training-and-courses

(To list an event, email: cuda_week_in_review@nvidia.com)

 

CUDA RESOURCES

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Tesla MD SimCluster

– Want to test drive a GPU? Try the Tesla Molecular       Dynamics SimCluster:
www.nvidia.com/simcluster

Downloads

– CUDA Toolkit: www.nvidia.com/getcuda
– Parallel Nsight: http://developer.nvidia.com/nvidia-parallel-nsight

Webinars

– CUDA: www.nvidia.com/webinars
– Parallel Nsight: http://developer.nvidia.com/developer-webinars

CUDA     Registered Developer Program

– Sign up: www.nvidia.com/paralleldeveloper

CUDA     GPUs

– List of CUDA-enabled GPUs: http://developer.nvidia.com/cuda-gpus

CUDA     on the Web

– See previous issues of CUDA: Week in Review: http://is.gd/cBXbg
– Follow CUDA & GPU Computing on Twitter: www.twitter.com/gpucomputing
– Network with other developers: www.gpucomputing.net
– Stay tuned to GPGPU news and events: www.gpgpu.org
– Learn more about CUDA on CUDA Zone: www.nvidia.com/cuda
– Check out the NVIDIA Research page: www.nvidia.com/research

CUDA     Recommended Reading

– Future of Computing Performance: http://bit.ly/hYqH2H
– Supercomputing for the Masses, Part 21: http://is.gd/Fj56gf
– CUDA books: http://www.nvidia.com/object/cuda_books.html

CUDA     Recommended Viewing

– SC11 presentations: http://www.gputechconf.com/page/gtc-on-demand.html
– The Third Pillar of Science: www.nvidia.com/object/race-for-better-science.html
– GTC 2010 presentations: www.nvidia.com/gtc
 

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 as well as APIs such as OpenCL and     DirectCompute. Send comments and suggestions to: cuda_week_in_review@nvidia.com
 
You are receiving this email because you have previously     expressed interest in NVIDIA products and technologies. Click here     to opt in specifically to CUDA: Week in Review.

Feel free to forward this email to customers, partners and     colleagues.

Copyright © 2011 NVIDIA Corporation. All rights reserved. 2701 San Tomas     Expressway, Santa Clara, CA 95050.

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Tygodniowy newsletter “CUDA: Week in Review.” – 11.11.2011

 

Fri., Nov. 11, 2011, Issue #65

Click     here for online version

 

CUDA: WEEK IN REVIEW

Welcome to the online newsletter for the worldwide CUDA,         GPGPU and parallel programming ecosystem.

CUDA SPOTLIGHT
Dr. Ian Buck, NVIDIA
CUDA TOP STORIES
CUDA 4.1         Release Candidate
2X in         4 Weeks. Guaranteed
Leading         Apps Add GPU Acceleration
New CULA         Sparse from EM Photonics
MSC         Announces MSC Nastran 2012
Chinese         Researchers Simulate H1N1 Virus
New Research         from IDC
CUDA Course         in Egypt from Applied Parallel Computing
GPU         Computing Gems – Jade Edition
GPU@BU         Workshop
CONTENTS
CUDA SPOTLIGHT
CUDA DEVELOPER NEWS
NEW ON THE BLOG
REPLAY OF THE WEEK
CUDA JOBS
GPU MEETUPS
CALLS FOR PAPERS
CUDA CALENDAR
CUDA RESOURCES
Sign         up to be a CUDA Registered Developer
Follow         @GPUComputing on Twitter
 

 

 
CUDA Turns 5!
This week marks the fifth anniversary of the CUDA programming model. To       celebrate the occasion, we caught up with Ian Buck, inventor of CUDA and       NVIDIA’s General Manager for GPU Computing. Here is a preview of the       interview:

NVIDIA: Ian, how did you get       hooked on computing with GPUs?
Ian: During my Ph.D. studies       at Stanford, the trends in programmable graphics hardware were really       exciting to me as well as the opportunity to work on technology that       could influence a wide breadth of sciences, whether it was molecular       dynamics, mechanical engineering or turbulence research. I could see that       GPUs were becoming powerful enough to help people working on the big       questions in science.
NVIDIA: How did you first start using GPUs? Was it as a       programmer or a gamer?
Ian: Let’s just say that       Stanford had a great internet connection, and as a result, we had an       awesome QuakeServer.
NVIDIA: What’s next for GPU computing?
Ian: GPU computing is going       mainstream. And it’s not just about NVIDIA. Just look at the great work       being done with tools, compilers and apps. Ad hoc GPU user groups are       popping up all over the world. A gigantic ecosystem is coming to life.       Today, any kind of meaningful simulation is done with GPUs. This focused       activity will enable us to solve some of the fundamental problems in       science.
NVIDIA: What have you learned along the way, since your days       at Stanford working on Brook to your current role as GM for GPU       Computing?
Ian: First of all, hire great       people. Don’t compromise. The people who use CUDA in industry and       academia are intensely driven. I look for the same drive in the people we       hire to work on CUDA at NVIDIA — intellectual curiosity combined with a       passion to solve cool and interesting problems. Second, don’t       underestimate the value of working on productivity features for developers.       The CUDA technology roadmap is focused on making GPU computing easier.       Anything we can do to make a developer’s life easier is always worth it.
- Read the full interview with Ian Buck

Editor’s Note: Next week, Ian will be at the SC11 conference in Seattle and     would be happy to meet up with current and future CUDA users. If you can’t     attend in person, be sure to check out our Facebook live stream from SC11     at: http://apps.facebook.com/nv-supercomputing/

(To suggest a CUDA Spotlight, email cuda_week_in_review@nvidia.com)

 

CUDA 4.1 Release Candidate

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The CUDA     Toolkit v4.1 release candidate (RC1) is now available to CUDA Registered     Developers. New features include an open source LLVM-based compiler, 1000+     new image processing functions and a redesigned Visual Profiler with     automated performance analysis.
- See: http://developer.nvidia.com/cuda-toolkit-41-rc1

2X in 4 Weeks. Guaranteed.

Double your     application performance with directives and GPUs. Simply insert a few     “hints” into the compiler and it automatically optimizes and     accelerates your code. To help you get started, NVIDIA and PGI are offering     a free 30-day license of the directives-based PGI Accelerator compiler. Not     only that, we are guaranteeing your application will achieve at least a 2X     speedup in 4 weeks or less.
- See: www.nvidia.com/2xin4weeks

Leading Apps Add Multiple GPU Acceleration Support

Four top     applications for materials science and biomolecular modeling – LAMMPS,     GROMACS, GAMESS and QMCPACK – have added support for multiple GPU     acceleration, enabling a reduction in simulation times from days to hours.
- See: http://bit.ly/uqOmu2

New CULA Sparse from EM Photonics

EM Photonics     released the general availability version of CULA Sparse, a collection of     matrix solvers for sparse systems on NVIDIA GPUs. In addition, new     functionality has been added to CULA R13.
- See: www.culatools.com

MSC Software Announces MSC Nastran 2012

MSC Software     announced MSC Nastran 2012, available for download in late November. The     software will be GPU accelerated.
- See: www.mscsoftware.com/About-Us/News/Default.aspx?articleid=1355

Chinese Researchers Simulate H1N1 Virus

Chinese     researchers achieved a breakthrough by creating the world’s first computer     simulation of a whole H1N1 influenza virus at the atomic level. Researchers     at the Institute of Process Engineering of Chinese Academy of Sciences     (CAS-IPE) are using molecular-dynamics simulations as a “computational     microscope” to peer into the structure of the virus. The work is     performed on a supercomputer with 2000+ Tesla GPUs.
- See: http://www.nvidia.com/object/newsroom.html

New Research from IDC

IDC published     a report on “Heterogeneous Computing: A New Paradigm for the Exascale     Era.”
- See: http://blogs.nvidia.com/wp-content/uploads/2011/11/IDC-Exascale-Executive-Brief_Nov2011.pdf

New CUDA Course in Egypt from Applied Parallel Computing

Applied     Parallel Computing will hold an advanced three-day course on GPU computing     and CUDA in Sharm El Sheikh, Egypt, Dec. 13-16.
- See: http://cuda-training.eventbrite.com/

GPU Computing Gems – Jade Edition

The second     volume of Morgan Kaufmann’s GPU Computing Gems series offers insights,     ideas and hands-on skills. The 30 chapters are written to be accessible to     researchers from any industry.
- See: http://www.amazon.com/GPU-Computing-Gems-Jade-Applications/dp/0123859638

GPU@BU Workshop

Boston University held a research symposium and tutorial     this week on GPUs in scientific computing. The event was organized by     Lorena Barba, Richard Brower, Martin Herbordt and Claudio Rebbi.
- See: http://blogs.bu.edu/gpu/gpubu-workshop/

 

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Path to Exascale Computing, by Sumit Gupta
GPU Acceleration Made Easy, by Roy Kim
 

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NEW: Each week we     highlight a session from a GPU     Technology Conference event. Here is our pick for this week: Large-Scale CCTV Face     Recognition (GTC 2010) by Abbas Bigdeli and Ben Lever,     NICTA
- see: http://nvidia.fullviewmedia.com/gtc2010/0923-c-2173.html
 

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NEW: Sportvision     is seeking a Senior Software Engineer with a proven track record working     with computer vision based products. Requirements: Enthusiasm and ability     to participate in solving interesting and complex problems.
- See: http://www.sportvision.com/info/srsoftwareengineer
(To submit a job listing, email cuda_week_in_review@nvidia.com)
 

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The GPU Meetups     offer a great way to learn about GPU computing and meet interesting people     in a relaxed environment.

GPU Meetup of Seattle, Wed., Nov. 16, 7:00 pm       (networking), 7:45 pm (program)
Special       SC11 Meetup! Talks by NVIDIA, Microsoft, LexisNexis. Location: Amazon
GPU Meetup of New Mexico, Wed., Nov. 16, 7:00 pm
Topic:       ROMIO and MPI-IO in Hybrid HPC
GPU Meetup of Brisbane, Nov. 17, 6:00 p.m
GPU Meetup of New York City, Nov. 21, 6:00 pm

(Would you like to start a Meetup? Email cuda_week_in_review@nvidia.com)

 

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GTC U.S. 2012 (May 14-17)
Poster deadline: Dec. 8
http://www.gputechconf.com/page/participate.html
https://gtc-submissions.confreg.com/
 

November 2011

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- Supercomputing 2011 (SC11)

Nov. 12-18, Seattle, Washington
Learn about NVIDIA activities at SC11: http://www.nvidia.com/sc11
For more information on SC11, visit http://sc11.supercomputing.org/
Join the GPU Technology Theater from your desk via the         SC11 Facebook live stream: http://apps.facebook.com/nv-supercomputing/

- GPU Programming for Defense/Intelligence — AccelerEyes       (Webinar)

Nov. 15, 2011
Learn to accelerate common defense and intelligence         algorithms using easy, powerful programming libraries, with Jacket for         use with MATLAB and LibJacket for C/C++/Fortran.
http://bit.ly/rdZ8pH

- Heterogeneous Data-Parallel Programming (Webinar)

Nov. 16, 2011
Presenter: Prof. Satnam Singh, University of Birmingham,         U.K.
https://www2.gotomeeting.com/register/164396834

- NEW: CUDA 4.1 RC1 (Webinar)

Nov. 22, 2011
Presented by NVIDIA
https://www2.gotomeeting.com/register/775971282

- CUDA Training (Basic and Advanced) — CAPS

Nov. 22-24, 2011, Rennes, France
Presented by CAPS
http://t.co/DWe0Zqka
Email: training (at) caps-entreprise.com

- CUDA 4-Day Training Course – Acceleware

Nov. 22-25, 2011, Frankfurt, Germany
Presented by Acceleware with Microsoft
Instructor: Michael Durocher
http://www.acceleware.com//nov22munich

December 2011

- AGU (American Geophysical       Union) Meeting

Dec. 5, 2011, San Francisco
Session on High-Res Modeling Using GPU and Many-Core         Architectures
http://sites.agu.org/fallmeeting/scientific-program/session-search/530

- Intro to GPU Programming Workshop – La Maison de la       Simulation

Dec. 5-9, 2011, France
http://www.maisondelasimulation.fr/index.php

- NEW: Advanced CUDA 3-Day Training Course – Applied Parallel       Computing

Dec. 13-16, Sharm El Sheikh, Egypt
http://cuda-training.eventbrite.com/

- GTC Asia

Dec. 14-15, 2011, Beijing, China
Featuring the latest GPU computing breakthroughs, demos         and presentations.
http://www.gputechconf.cn/home.html

- LibJacket CUDA Library for Maximus — AccelerEyes (Webinar)

Dec. 15, 2011
Learn to integrate computations with visualizations in a         CUDA-based app through simple visualization functions for plotting,         image and volume rendering, and more.
http://bit.ly/rdZ8pHs

2012

- NEW: CUDA Programming 1-Day Course – Delft University of       Technology

Feb. 3, 2012, Netherlands
http://ta.twi.tudelft.nl/users/vuik/gpu.html

(To list an event, email: cuda_week_in_review@nvidia.com)

 

Tesla MD SimCluster

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– Want to test drive a GPU? Try the Tesla Molecular       Dynamics SimCluster:
www.nvidia.com/simcluster

Downloads

– CUDA 4.0: www.nvidia.com/getcuda
– Parallel Nsight: http://developer.nvidia.com/nvidia-parallel-nsight

Webinars

– CUDA: www.nvidia.com/webinars
– Parallel Nsight: http://developer.nvidia.com/developer-webinars

CUDA     Registered Developer Program

– Sign up: www.nvidia.com/paralleldeveloper

CUDA     GPUs

– List of CUDA-enabled GPUs: http://developer.nvidia.com/cuda-gpus

CUDA     on the Web

– See previous issues of CUDA: Week in Review: http://is.gd/cBXbg
– Follow CUDA & GPU Computing on Twitter: www.twitter.com/gpucomputing
– Network with other developers: www.gpucomputing.net
– Stay tuned to GPGPU news and events: www.gpgpu.org
– Learn more about CUDA on CUDA Zone: www.nvidia.com/cuda
– Check out the NVIDIA Research page: www.nvidia.com/research

CUDA     Recommended Reading

– Future of Computing Performance: http://bit.ly/hYqH2H
– Supercomputing for the Masses, Part 21: http://is.gd/Fj56gf
– CUDA books: http://www.nvidia.com/object/cuda_books.html

CUDA     Recommended Viewing

– The Third Pillar of Science: www.nvidia.com/object/race-for-better-science.html
– GTC 2010 presentations: www.nvidia.com/gtc
– SC10 presentations: www.nvidia.com/object/sc10_theater.html
 
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 as well as APIs such as OpenCL and     DirectCompute. Send comments and suggestions to: cuda_week_in_review@nvidia.com
 
You are receiving this email because you have previously     expressed interest in NVIDIA products and technologies. Click here     to opt in specifically to CUDA: Week in Review.

 

Feel free to forward this email to customers, partners and     colleagues.

Copyright © 2011 NVIDIA Corporation. All rights reserved. 2701 San Tomas     Expressway, Santa Clara, CA 95050.

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Tygodniowy newsletter “CUDA: Week in Review.” – 01.11.2011

 

Tue., November 1, 2011, Issue #64

Click     here for online version

 

CUDA: WEEK IN REVIEW
Welcome to the online newsletter for the worldwide CUDA,         GPGPU and parallel programming ecosystem.
CUDA SPOTLIGHT
Dr. Jeffrey Vetter, Oak Ridge National Laboratory
CUDA TOP STORIES
NVIDIA GPU         Tech Theater at SC11
Oak Ridge         National Lab and Titan
GTC         Submission Deadline
Cornell         Launches Red Cloud
Congrats to         Francesco Rossi
Video         for Geo-Spatial Awareness
CONTENTS
CUDA SPOTLIGHT
CUDA DEVELOPER NEWS
NEW ON THE BLOG
REPLAY OF THE WEEK
CUDA JOBS
GPU MEETUPS
CALLS FOR PAPERS
CUDA CALENDAR
CUDA RESOURCES
Sign         up to be a CUDA Registered Developer
Follow         @GPUComputing on Twitter
 

 

 
GPU-Accelerated Real Science
This week’s Spotlight is on Dr. Jeffrey Vetter of Oak Ridge National       Laboratory and Georgia Tech. Here’s an extract from our interview:

NVIDIA: Jeff, what is the focus       of your work?
Jeff: Over the last decade, I       have been investigating hardware and software technologies that will most       likely appear in future supercomputer systems, and which of those       technologies best satisfy specific application workloads. I have worked       on a number of projects: IBM BlueGene/L, Cray X1, Cray XT, FPGAs, GPUs       and other technologies. Our team’s early work has contributed to the       design and deployment of the NSF Keeneland system and the DOE Titan       system.

Not surprisingly, our work over the last several years has primarily       focused on GPUs. Our team is involved in most every aspect of GPUs in       computational science: future architectures, programming systems,       applications development, and education and outreach. For example, we are       partners on NVIDIA’s Echelon research project, which is sponsored by the       DARPA UHPC program with the goal of fitting one PetaFLOPS in one rack and       using less than 57K watts of power….

NVIDIA: What are the key drivers in supercomputing today?
Jeff: From the facility or       data center perspective, the key driver is the energy required for       running large scale supercomputers. This is not just a prediction. Look       at most contemporary supercomputing facilities: they are often limited by       the amount of power that can be physically delivered to the computer in       the building….

On the other hand, applications developers are most concerned about       programmability. The last significant transition for the scientific       computing community was the transition in the 1990s from vector computing       to distributed memory computing with MPI. In order to provide solutions       to these questions, our team is investigating multiple fronts: CUDA,       compiler directives, runtime libraries, frameworks and debugging and       correctness tools. It is an exciting time to be in computer science!

NVIDIA: How does CUDA fit into the modern computing       landscape?
Jeff: CUDA is a phenomenon. In       less than five years, the CUDA programming model has grown from its       initial introduction to wide adoption. It is easy to forget how       challenging it was to program GPUs prior to CUDA. These days, CUDA is so       pervasive that many students get their first introduction to parallel       programming and fine-grained parallelism with CUDA on their laptop GPU….
  - Read the complete interview with Jeff Vetter

  (To suggest a CUDA Spotlight, email cuda_week_in_review@nvidia.com)

 
NVIDIA GPU Technology     Theater at SC11

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Going to SC11 in Seattle? If so, drop by the GPU Technology Theater at the NVIDIA booth (#2719). The     Theater will feature talks from industry experts including Jack Dongarra,     University of Tennessee; Patrick McCormick, Los Alamos National Laboratory;     Richard Brower, Boston University; and Satoshi Matsuoka, Tokyo Institute of     Technology. For the complete speaker lineup, visit the NVIDIA SC11 event page.     The talks will be streamed live via Facebook at http://apps.facebook.com/nv-supercomputing/.

Oak Ridge National Lab to Deploy     Titan
Oak Ridge National Laboratory (ORNL), which operates the world’s premier     open science computing facility for the U.S. Department of Energy, will     deploy a new supercomputer called Titan, based on Tesla GPUs. The system, which is referenced in today’s     CUDA Spotlight with Dr. Jeff Vetter, will be used across fields such as     materials science, energy technology, medical research and more.
- See the VentureBeat interview with NVIDIA’s Steve Scott (8 mins.): http://youtu.be/IkC8YRo9Mts

GTC U.S. Submission     Deadline
If you (or someone you know) is interested in speaking at GTC U.S. (May     2012), proposals must be submitted by Thurs., Nov. 3, 2011. Details can be     found on the GTC website.
- To make a submission, visit: https://gtc-submissions.confreg.com/

Cornell Launches Red Cloud
The Cornell University Center for Advanced Computing (CAC) has launched Red     Cloud, an on-demand research supercomputing service available by     subscription. The basic offering, called “Red Cloud,” is an     Infrastructure as a Service (IaaS) that runs Eucalyptus, the open source     cloud computing platform. The second offering, “Red Cloud with     MATLAB,” is a Software as a Service (SaaS) that runs MATLAB     Distributed Computing Server and features NVIDIA GPUs. Red Cloud services     run on Dell PowerEdge C servers.
- Visit www.cac.cornell.edu/redcloud

Congratulations to Francesco Rossi
Congratulations to Francesco Rossi, University of Bologna, on his recent     master’s thesis titled: “Development of Algorithms for an     Electromagnetic Particle in Cell Code….” While completing his thesis,     Francesco developed Jasmine, a flexible CPU+GPU PIC (particle in cell)     framework to assist in the design of laser-plasma accelerators. Jasmine     runs PIC 3D simulations on multi-GPU clusters, such as CINECA’s     Tesla-powered PLX, gaining large speedups.
- Read more: http://www.roxlabs.com/?page_id=110

Intergraph: Video for     Geo-Spatial Awareness
At the recent GeoINT trade show, Intergraph announced a new release of its     GeoMedia Motion Video Analyst solution with CUDA acceleration. GeoMedia     Motion Video Analyst speeds the process of creating images from full motion     video (FMV). This feature improves the ability of defense analysts to     maintain situational awareness and act quickly on intelligence data.
- For info, see: http://bit.ly/pBjGMX

 

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Webinar: Speed Up MATLAB With NVIDIA GPUs, by Dan     Doherty, MathWorks
NVIDIA Engineering Strike Force, by Brian Kelleher
NVIDIA CEO Wraps Up All Things D Asia Event, by Bob     Sherbin
 

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NEW: Each week we     highlight a session from a GPU Technology Conference     event. Here is our pick for this week: Computer Vision on GPU with OpenCV     (Israel 2011) by Anton Obukhov, NVIDIA
- For info, see: http://bit.ly/r5Qay6
 

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NEW: GE Healthcare     is seeking a software engineer to specify, design and implement software     for a new X-ray acquisition system. Desired characteristics include     experience with GPU/CUDA and imaging software.
- See: http://jobs.gecareers.com/job/Salt-Lake-City-Software-Engineer-II-HC-Job-UT-84101/1284204/
(To submit a job listing, email cuda_week_in_review@nvidia.com)
 

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The GPU Meetups     offer a great way to learn about GPU computing and meet interesting people     in a relaxed environment. Please feel free to attend any of these upcoming     Meetups:

GPU Meetup of Boston, Thurs., Nov. 3 at 6:00 pm
Topic:       HPC and Protein Simulation, Francesco Pontiggia, Brandeis University
GPU Meetup of Silicon Valley, Mon., Nov. 7 at 6:15 pm
Topic:       GPU Programming with Thrust and Copperhead, Bryan Catanzaro, NVIDIA
GPU Meetup of Seattle, Wed., Nov. 16, 7:00 pm       (networking), 7:45 pm (program)
Special       SC11 Meetup! Talks by NVIDIA, Microsoft, LexisNexis. Location: Amazon
GPU Meetup of New Mexico, Wed., Nov. 16, 7:00 pm
Topic:       ROMIO and MPI-IO in Hybrid HPC
GPU Meetup of Brisbane, Nov. 17, 6:00 p.m
GPU Meetup of New York City, Nov. 21, 6:00 pm

(Would you like to start a Meetup? Email cuda_week_in_review@nvidia.com)

 

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GTC Asia 2011 (Dec. 14-15)
Poster deadline: Nov. 3
http://www.gputechconf.cn/en/call-for-posters.html

GTC U.S. 2012     (May 14-17)
Session deadline: Nov. 3
Poster deadline: Dec. 8
http://www.gputechconf.com/page/participate.html
https://gtc-submissions.confreg.com/

 
November 2011

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- NEW: Accelerate Science       to Treatment with the MD SimCluster (Webinar)

Nov. 8, 2011
Sponsored by QLogic, Dell, NVIDIA
http://qlogic.adobeconnect.com/hpcwebinar_nov11/event/registration.html

- NEW: 2-Day “Deep CUDA” Training – NOVATTE

Nov. 9-10, 2011, Singapore
Sponsored by NOVATTE, A*Star and NVIDIA
For info, email to Oxana Plis, op (at) novatte.com

- Supercomputing 2011 (SC11)

Nov. 12-18, Seattle, Washington
Learn about NVIDIA activities at SC11: http://www.nvidia.com/sc11.html
For more information on SC11, visit http://sc11.supercomputing.org/
Join the GPU Technology Theater from your desk via the         SC11 Facebook live stream: http://apps.facebook.com/nv-supercomputing/

- GPU Programming for Defense/Intelligence — AccelerEyes       (Webinar)

Nov. 15, 2011
Learn to accelerate common defense and intelligence         algorithms using easy, powerful programming libraries, with Jacket for         use with MATLAB and LibJacket for C/C++/Fortran.
http://bit.ly/rdZ8pH

- NEW: Heterogeneous Data-Parallel Programming (Webinar)

Nov. 16, 2011
Presenter: Prof. Satnam Singh, University of Birmingham,         U.K.
https://www2.gotomeeting.com/register/164396834

- CUDA Training (Basic and Advanced) — CAPS

Nov. 22-24, 2011, Rennes, France
http://t.co/DWe0Zqka
Email: training (at) caps-entreprise.com

- NEW: CUDA 4-Day Training Course – Acceleware

Nov. 22-25, 2011, Munich, Germany
Presented by Acceleware with Microsoft
Instructor: Michael Durocher
http://www.acceleware.com//nov22munich

December 2011

- AGU (American Geophysical       Union) Meeting

Dec. 5, 2011, San Francisco
Session on High-Res Modeling Using GPU and Many-Core         Architectures
http://sites.agu.org/fallmeeting/scientific-program/session-search/530

- NEW: Intro to GPU Programming Workshop – La Maison de la       Simulation

Dec. 5-9, 2011, France
http://www.maisondelasimulation.fr/index.php

- GTC Asia

Dec. 14-15, 2011, Beijing, China
Featuring the latest GPU computing breakthroughs, demos         and presentations.
http://www.gputechconf.cn/home.html

- LibJacket CUDA Library for Maximus — AccelerEyes (Webinar)

Dec. 15, 2011
Learn to integrate computations with visualizations in a         CUDA-based app through simple visualization functions for plotting,         image and volume rendering, and more.
http://bit.ly/rdZ8pHs

(To list an event, email: cuda_week_in_review@nvidia.com)

 
Tesla MD SimCluster

back to the top

– Want to test drive a GPU? Try the Tesla Molecular       Dynamics SimCluster:
www.nvidia.com/simcluster
Downloads
– CUDA 4.0: www.nvidia.com/getcuda
– Parallel Nsight: http://developer.nvidia.com/nvidia-parallel-nsight
Webinars
– CUDA: www.nvidia.com/webinars
– Parallel Nsight: http://developer.nvidia.com/developer-webinars
CUDA     Registered Developer Program
– Sign up: www.nvidia.com/paralleldeveloper
CUDA     GPUs
– List of CUDA-enabled GPUs: http://developer.nvidia.com/cuda-gpus
CUDA     on the Web
– See previous issues of CUDA: Week in Review: http://is.gd/cBXbg
– Follow CUDA & GPU Computing on Twitter: www.twitter.com/gpucomputing
– Network with other developers: www.gpucomputing.net
– Stay tuned to GPGPU news and events: www.gpgpu.org
– Learn more about CUDA on CUDA Zone: www.nvidia.com/cuda
– Check out the NVIDIA Research page: www.nvidia.com/research
CUDA     Recommended Reading
– Future of Computing Performance: http://bit.ly/hYqH2H
– Supercomputing for the Masses, Part 21: http://is.gd/Fj56gf
– CUDA books: http://www.nvidia.com/object/cuda_books.html
CUDA     Recommended Viewing
– The Third Pillar of Science: www.nvidia.com/object/race-for-better-science.html
– GTC 2010 presentations: www.nvidia.com/gtc
– SC10 presentations: www.nvidia.com/object/sc10_theater.html
 
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 as well as APIs such as OpenCL and     DirectCompute. Send comments and suggestions to: cuda_week_in_review@nvidia.com
 
You are receiving this email because you have previously     expressed interest in NVIDIA products and technologies. Click here     to opt in specifically to CUDA: Week in Review.

Feel free to forward this email to customers, partners and     colleagues.

Copyright © 2011 NVIDIA Corporation. All rights reserved. 2701 San Tomas     Expressway, Santa Clara, CA 95050.

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Tygodniowy newsletter “CUDA: Week in Review.” – 10.10.2011

 

Mon., October 10, 2011, Issue #63

Click     here for online version

 

WELCOME
Welcome to CUDA:         Week in Review, an online news summary for the         worldwide CUDA, GPU computing and parallel programming ecosystem.
CUDA SPOTLIGHT
William Putman, NASA
CUDA TOP STORIES
October         Webinar Lineup
Ecosystem         Update
Awards and         Recognitions
CUDA on the         Web
 
 
CONTENTS
CUDA SPOTLIGHT
CUDA DEVELOPER NEWS
NEW ON THE BLOG
REPLAY OF THE WEEK
CUDA JOBS
GPU MEETUPS
CALLS FOR PAPERS
CUDA CALENDAR
CUDA RESOURCES
Sign         up to be a CUDA Registered Developer
Follow         @GPUComputing on Twitter

 

 
GPU-Accelerated Climate       Simulation
This week’s Spotlight is on William Putman, a NASA research       meteorologist in the Global Modeling and Assimilation Office (GMAO) in       the Earth Sciences Division of Goddard Space Flight Center’s Sciences and       Exploration Directorate. Here’s an extract from our interview:

NVIDIA: Bill, what does your       group do?
Bill: Our research and       development activities aim to maximize the impact of satellite       observations in climate, weather and atmospheric composition prediction       using comprehensive global models and data assimilation.

To achieve this goal, the GMAO develops models and assimilation systems       for the atmosphere, ocean, and land surface, generates products to       support NASA instrument teams and the NASA Earth Science program, and       undertakes scientific research to inform system development pathways.

Within the GMAO we have a group of developers (Dr. Max Suarez, Dr.       Matthew Thompson and myself) tasked with the restructuring of NASA’s       Goddard Earth Observing System atmospheric general circulation model       version 5 (GEOS-5) to take advantage of new accelerator technologies including       GPUs.

NVIDIA: What are the benefits of using CUDA?
Bill: The Portland Group (PGI)       offers us an opportunity to explicitly program for GPUs using CUDA       Fortran and also provides a directive-based accelerator model. GEOS-5 is       primarily written in Fortran, thus the PGI CUDA Fortran syntax allows us       to develop GPU kernels in GEOS-5 using a familiar coding environment.

Like CUDA C, CUDA Fortran allows for low-level management of the       initialization, data transfer, and coding details of a project without       the need to translate legacy Fortran code into C. This aids both in speed       of development and with keeping a readable (to developers) codebase       within GEOS-5 while achieving much the same performance as CUDA C.

  - Read the complete interview here

  (Would you like to be in the CUDA Spotlight? Email     cuda_week_in_review@nvidia.com)

 
Check Out the October     CUDA Webinar Lineup!

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Tues., Oct. 11: PGI Accelerator for C – Simplified GPU     Programming Using Directives
Presented     by Dr. Michael Wolfe, The Portland Group
https://www2.gotomeeting.com/register/623491562

Tues., Oct. 11: CUDA Optimization: Memory Bandwidth Limited Kernels + Live     Q&A
Presented     by Tim Schroeder, NVIDIA
https://www2.gotomeeting.com/register/936728978

Wed., Oct. 12: Intro to Parallel Nsight and Features (Preview of Version     2.1)
Presented     by Shane Evans, NVIDIA
https://www2.gotomeeting.com/register/522390506

Thurs., Oct 20: Overview and Usage of LibJacket CUDA Library
Presented     by James Malcolm, AccelerEyes (with NVIDIA)
https://www2.gotomeeting.com/register/378528682

Thurs., Oct. 27: GPU Computing with MATLAB
Presented     by Sarah Wait Zaranek, MathWorks
http://www.mathworks.com/company/events/webinars/wbnr59816.html

Ecosystem     Update
Rogue Wave Software, provider of cross-platform software development tools,     announced the release of TotalView 8.9.2 with support for CUDA 4.0: http://bit.ly/o6fobN

Awards and Recognitions
The Johns Hopkins University has been named a CUDA Center of Excellence,     recognizing its ground-breaking work leveraging GPU computing. As a CCOE,     Johns Hopkins will utilize equipment and grants provided by NVIDIA to     support a number of research and academic programs, including deployment of     the “Data-Scope,” a GPU-powered, ultra-high throughput     supercomputer to dramatically increase the speed of scientific data     analysis: http://bit.ly/qOiVRI

Boise State University, a CUDA Research Center, received two grants that     build on GPU computing initiatives:
- NOAA Field Research Office collaboration to develop a CUDA Fortran     version of NOAA’s HYSPLIT Air     Dispersion model: http://ready.arl.noaa.gov/HYSPLIT.php
- NSF CAREER Grant for multi-scale modeling of short-term forecasting and     grid integration of wind energy: http://1.usa.gov/p3xWRu

This year’s PRACE (Partnership for Advanced Computing in Europe) Award goes     to a paper titled “Astrophysical Particle Simulations with Large     Custom GPU Clusters on Three Continents.”     Prof. Richard Kenway, Chairman of the PRACE Scientific     Steering Committee, noted that “the work points the way to exploit exascale     technologies for problems at the forefront of science.” http://www.prace-project.eu/news/the-prace-award-winners-2011-announced

CUDA on the Web
A new video on “Volt: Interactive Volume Rendering with CUDA” has     been posted by the Computer Graphics Lab at the Bonn-Rhine-Sieg University     of Applied Sciences. Volt is an interactive direct volume renderer that     takes advantage of GPUs for high quality interactive ray casting.
- http://cg.inf.fh-bonn-rhein-sieg.de/?page_id=2700

The Irish Center for High-End Computing (ICHEC) launched a new website     dedicated to GPU computing. ICHEC’s Director, Prof. James Slevin, said:     “Computer simulation has now reached a level of predictability that     firmly grounds its impact and importance along with theory and     experimentation as the third pillar of science research.”
- http://gpgpu.ichec.ie/

Industrial Mathematics KTN released a new report on “The GPU Computing     Revolution: from Multi-Core CPUs to Many-Core Graphics Processors.”     Produced in collaboration with the London Mathematical Society, it was     written by Simon McIntosh-Smith of the University of Bristol.
- https://connect.innovateuk.org/web/mathsktn/articles/-/blogs/the-gpu-computing-revolution

 
GPUs Storm into Climate Simulations, by Will Park

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Inner Geek – Project GT90 Supercar, by Adam Pintek
 
NEW: Each week we     highlight a session from GTC 2010. Here is our pick for this     week:

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            Rapid     Prototyping using Thrust: High Performance Dosimetry (GTC 10)
Guillaume     Saupin – CEA, France
http://www.gputechconf.com/page/gtc-on-demand.html#2104
 
NEW: AIR, a provider of risk modeling software, is seeking     a Senior Software Engineer in Boston, Mass. Responsibilities include     contributing to development of next-generation HPC-based analytical     framework, algorithms and tooling (using C++,C#, SQL and CUDA).
- Apply online: http://bit.ly/o74ZQe

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              Kudos     to the South Florida GPU Meetup, organized by Adnan Boz, for designing a     clever logo based on a fish swarm. The group recently held its third     Meetup, where Adnan presented on “Thinking in Parallel.”

Feel free to attend upcoming GPU Meetups. The atmosphere is casual and     collaborative. Participants and sponsors are warmly welcomed.

- US
Silicon Valley GPU Meetup – Oct. 10, 6:15 pm
New Mexico GPU Meetup – Oct. 15, 5:00 pm
New York GPU Meetup – Oct. 24, 6:00 pm (Special     joint meeting with
C++ Dev Group)
South Florida GPU Meetup – Oct. 24, 6:30 pm

- Australia
Sydney GPU Meetup – Oct. 13, 6:00 pm
Melbourne GPU Meetup – Oct. 19, 5:30 pm
Brisbane GPU Meetup – Oct. 20, 6:00 pm

 
GTC Asia 2011 (Dec. 14-15)
Poster deadline: Nov. 3
http://www.gputechconf.cn/en/call-for-posters.html

GTC U.S. 2012     (May 14-17)
Session deadline: Nov. 3
Poster deadline: Dec. 8
http://www.gputechconf.com/page/participate.html

Bioinformatics:     BICoB 2012 (March 12-14)
Paper deadline: Oct. 28
http://sce.uhcl.edu/bicob12/

 
October 2011

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- NEW: PGI Accelerator       for C – Simplified GPU Programming Using Directives (Webinar)

Oct. 11, 2011
Presented by Dr. Michael Wolfe, The Portland Group
https://www2.gotomeeting.com/register/623491562

- NEW: CUDA Optimization: Memory Bandwidth Limited Kernels + Live       Q&A (Webinar)

Oct. 11, 2011
Presented by Tim Schroeder, NVIDIA
https://www2.gotomeeting.com/register/936728978

- NEW: Intro to Parallel Nsight and Features (Webinar)

Oct. 12, 2011
Presented by Shane Evans, NVIDIA
https://www2.gotomeeting.com/register/522390506

- CUDA 4-Day Training Course – Acceleware

Oct. 11-14, 2011, Los Angeles, Calif.
Presented by Acceleware with Microsoft
http://acceleware.com/oct11los-angeles

- GPU-Accelerated Derivative Pricing Models — SciComp

Oct. 17, 2011, London, UK
Presented by SciComp, NVIDIA, Dell, Microsoft
http://www.scicomp.com/seminars/2011/signup

- NEW: Overview and Usage of LibJacket CUDA Library – AccelerEyes       (Webinar)

Oct 20, 2011
Presented by James Malcolm, AccelerEyes (with NVIDIA)
https://www2.gotomeeting.com/register/378528682

- GPU Computing with MATLAB (Webinar)

Oct. 27, 2011
Presented by Sarah Wait Zaranek, MathWorks
http://www.mathworks.com/company/events/webinars/wbnr59816.html

November 2011

- CUDA 4-Day Training Course —       Acceleware

Nov. 1-4, 2011, Frankfurt, Germany
Presented by Acceleware with Microsoft
http://acceleware.com/nov1frankfurt

- Supercomputing 2011 (SC11)

Nov. 12-18, Seattle, Washington
http://sc11.supercomputing.org/

- GPU Programming for Defense/Intelligence — AccelerEyes       (Webinar)

Nov. 15, 2011
Learn to accelerate common defense and intelligence algorithms         using easy, powerful programming libraries, with Jacket for use with         MATLAB and LibJacket for C/C++/Fortran.
http://bit.ly/rdZ8pH

- CUDA Training (Basic and Advanced) — CAPS

Nov. 22-24, 2011, Rennes, France
http://t.co/DWe0Zqka
Email: training (at) caps-entreprise.com

December 2011

- AGU (American Geophysical       Union) Meeting

Dec. 5, 2011, San Francisco
Session on High-Res Modeling Using GPU and Many-Core         Architectures
http://sites.agu.org/fallmeeting/scientific-program/session-search/530

- NEW: Intro to GPU Programming Workshop – La Maison de la       Simulation

Dec. 5-9, 2011, France
http://www.maisondelasimulation.fr/index.php

- GTC Asia

Dec. 14-15, 2011, Beijing, China
Featuring the latest GPU computing breakthroughs, demos         and presentations.
http://www.gputechconf.cn/home.html

- LibJacket CUDA Library for Maximus — AccelerEyes (Webinar)

Dec. 15, 2011
Learn to integrate computations with visualizations in a         CUDA-based app through simple visualization functions for plotting,         image and volume rendering, and more.
http://bit.ly/rdZ8pH

(To list an event, email: cuda_week_in_review@nvidia.com)

 
Tesla MD SimCluster

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– Tesla MD SimCluster: www.nvidia.com/simcluster
Downloads
– CUDA 4.0: www.nvidia.com/getcuda
– Parallel Nsight: http://developer.nvidia.com/nvidia-parallel-nsight
Webinars
– CUDA: www.nvidia.com/webinars
– Parallel Nsight: http://developer.nvidia.com/developer-webinars
CUDA     Registered Developer Program
– Sign up: www.nvidia.com/paralleldeveloper
CUDA     GPUs
– List of CUDA-enabled GPUs: http://developer.nvidia.com/cuda-gpus
CUDA     on the Web
– See previous issues of CUDA: Week in Review: http://is.gd/cBXbg
– Follow CUDA & GPU Computing on Twitter: www.twitter.com/gpucomputing
– Network with other developers: www.gpucomputing.net
– Stayed tuned to GPGPU news and events: www.gpgpu.org
– Learn more about CUDA on CUDA Zone: www.nvidia.com/cuda
– Check out the NVIDIA Research page: www.nvidia.com/research
CUDA     Recommended Reading
– Future of Computing Performance: http://bit.ly/hYqH2H
– Supercomputing for the Masses, Part 21: http://is.gd/Fj56gf
– CUDA books: http://www.nvidia.com/object/cuda_books.html
CUDA     Recommended Viewing
– The Third Pillar of Science: www.nvidia.com/object/race-for-better-science.html
– GTC 2010 presentations: www.nvidia.com/gtc
– SC10 presentations: www.nvidia.com/object/sc10_theater.html
 
CUDA is NVIDIA’s parallel computing hardware architecture.     NVIDIA provides a complete toolkit for programming on the CUDA     architecture, supporting standard computing languages such as C, C++ and     Fortran as well as APIs such as OpenCL and DirectCompute. Send comments and     suggestions to: cuda_week_in_review@nvidia.com
 
You are receiving this email because you have previously     expressed interest in NVIDIA products and technologies. Click here     to opt in specifically to CUDA: Week in Review.

Feel free to forward this email to customers, partners and     colleagues.

Copyright © 2011 NVIDIA Corporation. All rights reserved. 2701 San Tomas     Expressway, Santa Clara, CA 95050.

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Tygodniowy newsletter “CUDA: Week in Review.” – 20.09.2011

 

Tue., September 20, 2011, Issue #62

 

WELCOME
Welcome to CUDA:         Week in Review, an online news summary for the         worldwide CUDA, GPU computing and parallel programming ecosystem.
CUDA SPOTLIGHT
Mehdi Raessi, UMass-Dartmouth
CUDA TOP STORIES
Test Drive         Tesla MD SimCluster
New CUDA         Centers Announced
MATLAB         Acceleration on GPUs
HP         Mini-Supercomputer
Running         CUDA on x86
CUDA Jobs:         European Commission
 
CONTENTS
CUDA SPOTLIGHT
CUDA DEVELOPER NEWS
NEW ON THE BLOG
REPLAYS OF THE WEEK
CUDA JOBS
GPU MEETUPS
CALLS FOR PAPERS
CUDA CALENDAR
CUDA RESOURCES
Sign         up to be a CUDA Registered Developer
Follow         @GPUComputing on Twitter

 

 
GPU-Accelerated Multi-Phase Flow Simulations
This week’s spotlight is on Dr. Mehdi Raessi, Assistant Professor       in the Department of Mechanical Engineering at University of       Massachusetts-Dartmouth.
NVIDIA: Mehdi, tell us about your research.
                                                                                                                                                             Mehdi: The       focus of my research is primarily on multi-phase flows and free-surface       flows with phase change. We develop computational algorithms and flow       solvers, and use them to study industrial and research

applications       that involve multi-phase flows.

Examples include materials processing (thermal spray coating and       casting), energy systems (both renewable and conventional), and       environmentally friendly or “green” refrigeration systems.

NVIDIA: What role does GPU computing play in your work?
Mehdi: Our numerical       algorithm for solving the fluid flow equations involves a step in which       we solve a large system of linear equations to compute the pressure       field. That single step can take from 50 to 99.9 percent of the total       simulation time! As we increase the number of grid points in our       simulations, the pressure solution step takes a larger percentage of the       total simulation time.

To speed up this task, my graduate student, Stephen Codyer, ported the       pressure calculations to the GPU. His tests show that the GPU-accelerated       solver can run a 3D simulation with over 28 million grid points 15 times       faster (compared to performing the same calculation on the CPU). My       colleague, Prof. Gaurav Khanna, from our Physics Department, helped us a       lot in this project and shared his extensive experience in GPU computing.

NVIDIA: What future applications can you envision in your       research area?
Mehdi: As we       all know, energy and the environment have become the most pressing issues       in the world. Addressing these issues requires new technology and drastic       changes in the ways that we use our energy resources. After events like       the oil spill in the Gulf of Mexico and the Fukushima Daiichi nuclear       disaster, I think everyone agrees that we should plan to use energy       resources that have low potential to cause catastrophic events.

We have begun projects that are targeting these issues. With       GPU-accelerated computational tools, we are now able to study much larger       problems at a level of detail that was not feasible before. These simulations       can lead to new energy devices that are more efficient and have less       environmental impact. I believe the capability to run faster and faster       simulations with GPUs will one day enable us to predict, respond to and       mitigate catastrophic events.

  - Read the complete interview here

  (Would you like to be in the CUDA Spotlight? Email     cuda_week_in_review@nvidia.com)

 
Test Drive the Tesla     MD SimCluster

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Want to test drive a GPU? Try the new Tesla Molecular     Dynamics SimCluster, which is preconfigured to accelerate AMBER or NAMD.     All you need to do to start a simulation is load your models. To test     drive, visit www.nvidia.com/simcluster or email mdsimcluster (at)     nvidia.com.
New CUDA Centers     Announced
Congrats to all the new CUDA Research Centers and CUDA Teaching Centers,     including Carnegie Mellon/Silicon Valley and the University of Edinburgh.     For the complete list of newcomers, see this recent blog post: http://blogs.nvidia.com/2011/09/new-cuda-research-and-teaching-centers-announced/

MATLAB Acceleration on GPUs
Using MATLAB for GPU computing is ideal for engineers and scientists who     want to take advantage of GPUs without low-level C or Fortran programming.     Register for a free webinar on October 27 to learn how CUDA-enabled GPUs     can help accelerate MATLAB computations: http://bit.ly/ondzzC.
For more info about GPU computing in MATLAB, see this recent MATLAB Digest     article: http://bit.ly/pOiZg6.

Mini-Supercomputer from HP
The new GPU Starter Kit from HP provides a ready-to-use GPU computing     cluster, straight out of the box. It combines eight HP ProLiant SL390 G7     servers (based on 24 Tesla M2070 GPUs) with 16 CPUs. For info, visit www.nvidia.com/docs/IO/43399/NV-Tesla-Starter-Kit.pdf     or email Hpc-sales (at)     hp.com.

Running CUDA on x86
In Dr. Dobb’s newsletter, Rob Farber writes: “Recent developments     allow CUDA programs to transparently compile and run at full speed on x86     architectures. This advance makes CUDA a viable programming model for all     application development, just like OpenMP. The PGI CUDA C/C++ compiler for     x86 (from the Portland Group Inc.) is the reason for this recent change in     mindset.”
- Learn more: http://drdobbs.com/high-performance-computing/231500166

 
NVIDIA Blog
New CUDA Research and Teaching Centers, by Chandra     Cheij
Dive into Windows 8 with NVIDIA, by Stephen Jones
NVIDIA GPUDirect for Video and More, by Greg Estes

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CUDA Zone Blog
GPU Starter Kit Stirs Excitement, by Nadeem Mohammad
 
NEW: Each week we     highlight a session from GTC 2010. Here is our pick for this     week:

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      Using     GPUs for Real-Time Brain-Computer Interfaces (GTC 10)
Adam Wilson – University of Cincinnati
http://nvidia.fullviewmedia.com/gtc2010/0922-c-2122.html
 
NEW: The Joint Research     Centre of the European Commission is seeking a CUDA programmer     with image processing experience to support operational emergency mapping     initiatives. The position is based in Italy. Application deadline is Oct.     3, 2011.
- See: http://ipsc.jrc.ec.europa.eu/jobs.php?idx=72

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Feel free to attend these upcoming GPU Meetups! The atmosphere     is casual and collaborative. Participants and sponsors are warmly welcomed.

- United States
New York GPU Meetup – Sept. 26, 6:00 pm
South Florida GPU Meetup – Sept. 26, 6:30 pm
Boston GPU Meetup – Oct. 6, 6:00 pm
Silicon Valley GPU Meetup – Oct. 10, 6:15 pm
New York GPU Meetup – Oct. 24, 6:00 pm (Special joint     meeting with
C++ Dev Group)

 
SC11: NVIDIA GTC Express Live Theater (Nov. 12-18)
Poster deadline: Sept. 27
http://www.gputechconf.com/page/worldwide-submissions.html

GTC Asia 2011     (Dec. 14-15)
Poster deadline: Oct. 25
http://www.gputechconf.cn/en/call-for-posters.html

GTC U.S. 2012     (May 14-17)
Session deadline: Nov. 3
Poster deadline: Dec. 8
http://www.gputechconf.com/page/participate.html

Mathematics:     SIAM 12 (July 9-13)
Paper and award deadline: Oct. 1
http://www.siam.org/meetings/an12/
http://www.siam.org/prizes/nominations/nom_cse.php

Bioinformatics:     BICoB 2012 (March 12-14)
Paper deadline: Oct. 28
http://sce.uhcl.edu/bicob12/

 
September 2011

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- SEG (Society of Exploration       Geophysicists) Annual Meeting

Sept. 18-23, 2011, San Antonio, Texas
http://www.seg.org/events/annual-meeting/sanantonio2011/am2011techprogram

- CUDA 3-Day Training Course — Tech-X

Sept. 19-21, 2011, Boulder, Colorado
Presented by Tech-X
http://www.txcorp.com/products/GPULib/cuda_training/download.php

- Russian-German HPC School

Sept. 19-30, 2011, Novosibirsk
http://conf.nsc.ru/hpcschool

- SPIE Conference on High-Performance Computing in Remote       Sensing

Sept. 19-22, 2011, Prague, Czech Republic
http://spie.org/rs11

- CUDA Optimization (Webinar)

Sept. 20, 2011
Presented by Timothy Schroeder, NVIDIA
https://www2.gotomeeting.com/register/936728978

- CUDA Optimization (Webinar)

Sept. 27, 2011
Presented by Gernot Ziegler, NVIDIA
https://www2.gotomeeting.com/register/260445946

- GPU-Accelerated Derivative Pricing Models — SciComp

Sept. 27, 2011, New York
Presented by SciComp, NVIDIA, Dell, Microsoft
http://www.scicomp.com/seminars/2011/signup

- NEW: CUDA 4-Day Training Course — Acceleware

Sept. 27-30, 2011, London, UK
Presented by Acceleware with Microsoft
http://acceleware.com/sep27london

October 2011

- CUDA Optimization (Webinar)

Oct. 4, 2011
Presented by Paulius Micikevicius, NVIDIA
https://www2.gotomeeting.com/register/273766338

- NEW: CUDA 4-Day Training Course – Acceleware

Oct. 11-14, 2011, Los Angeles, Calif.
Presented by Acceleware with Microsoft
http://acceleware.com/oct11los-angeles

- GPU-Accelerated Derivative Pricing Models — SciComp

Oct. 17, 2011, London, UK
Presented by SciComp, NVIDIA, Dell, Microsoft
http://www.scicomp.com/seminars/2011/signup

- NEW: GPU Computing with MATLAB (Webinar)

Oct. 27, 2011
Presented by Sarah Wait Zaranek, MathWorks
http://www.mathworks.com/company/events/webinars/wbnr59816.html

November 2011

- NEW: CUDA 4-Day       Training Course — Acceleware

Nov. 17-4, 2011, Frankfurt, Germany
Presented by Acceleware with Microsoft
http://acceleware.com/nov1frankfurt

- Supercomputing 2011 (SC11)

Nov. 12-18, Seattle, Washington
http://sc11.supercomputing.org/

- NEW: GPU Programming for Defense/Intelligence — AccelerEyes       (Webinar)

Nov. 15, 2011
Learn to accelerate common defense and intelligence         algorithms using easy, powerful programming libraries, with Jacket for         use with MATLAB and LibJacket for C/C++/Fortran.
http://bit.ly/rdZ8pH

- NEW: CUDA Training (Basic and Advanced) — CAPS

Nov. 22-24, 2011, Rennes, France
http://t.co/DWe0Zqka
Email: training (at) caps-entreprise.com

December 2011

- NEW: AGU (American       Geophysical Union) Meeting

Dec. 5, 2011, San Francisco
Session on High-Res Modeling Using GPU and Many-Core         Architectures
http://sites.agu.org/fallmeeting/scientific-program/session-search/530

- NEW: GTC Asia

Dec. 14-15, 2011, Beijing, China
Featuring the latest GPU computing breakthroughs, demos         and presentations.
http://www.gputechconf.cn/home.html

- NEW: LibJacket CUDA Library for Maximus — AccelerEyes (Webinar)

Dec. 15, 2011
Learn to integrate computations with visualizations in a         CUDA-based app through simple visualization functions for plotting,         image and volume rendering, and more.
http://bit.ly/rdZ8pH

(To list an event, email: cuda_week_in_review@nvidia.com)

 
Downloads

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– CUDA 4.0: www.nvidia.com/getcuda
– Parallel Nsight: http://developer.nvidia.com/nvidia-parallel-nsight
Webinars
– CUDA: www.nvidia.com/webinars
– Parallel Nsight: http://developer.nvidia.com/developer-webinars
CUDA     Registered Developer Program
– Sign up: www.nvidia.com/paralleldeveloper
CUDA     GPUs
– List of CUDA-enabled GPUs: http://developer.nvidia.com/cuda-gpus
CUDA     on the Web
– See previous issues of CUDA: Week in Review: http://is.gd/cBXbg
– Follow CUDA & GPU Computing on Twitter: www.twitter.com/gpucomputing
– Network with other developers: www.gpucomputing.net
– Stayed tuned to GPGPU news and events: www.gpgpu.org
– Learn more about CUDA on CUDA Zone: www.nvidia.com/cuda
– Check out the NVIDIA Research page: www.nvidia.com/research
CUDA     Recommended Reading
– Future of Computing Performance: http://bit.ly/hYqH2H
– Supercomputing for the Masses, Part 21: http://is.gd/Fj56gf
– CUDA books: http://www.nvidia.com/object/cuda_books.html
CUDA     Recommended Viewing
– The Third Pillar of Science: www.nvidia.com/object/race-for-better-science.html
– GTC 2010 presentations: www.nvidia.com/gtc
– SC10 presentations: www.nvidia.com/object/sc10_theater.html
 
CUDA is NVIDIA’s parallel computing hardware architecture.     NVIDIA provides a complete toolkit for programming on the CUDA     architecture, supporting standard computing languages such as C, C++ and     Fortran as well as APIs such as OpenCL and DirectCompute. Send comments and     suggestions to: cuda_week_in_review@nvidia.com
 
You are receiving this email because you have previously     expressed interest in NVIDIA products and technologies. Click here     to opt in specifically to CUDA: Week in Review.

Feel free to forward this email to customers, partners and     colleagues.

Copyright © 2011 NVIDIA Corporation. All rights reserved. 2701 San Tomas     Expressway, Santa Clara, CA 95050.

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Tygodniowy newsletter “CUDA: Week in Review.” – 30.08.2011

 

Tue., August 30, 2011, Issue #61

Click     here for online version

 

WELCOME
Welcome to CUDA:         Week in Review, an online news summary for the         worldwide CUDA, GPU computing and parallel programming ecosystem.
CUDA SPOTLIGHT
Alexander Doronin, Univ. of Otago
CUDA TOP STORIES
GTC Asia         Announced
GTC Worldwide         Call for Submissions
Project         Maximus Update
GPU         Mini-Supercomputer for Every Scientist
MAGMA v1.0         Supports Tesla GPUs
Gaussian         to Support GPU Acceleration
 
CONTENTS
CUDA SPOTLIGHT
CUDA DEVELOPER NEWS
NEW ON THE BLOG
REPLAYS OF THE WEEK
CUDA JOBS
GPU MEETUPS
CUDA CALENDAR
CUDA RESOURCES
Sign         up to be a CUDA Registered Developer
Follow         @GPUComputing on Twitter

 

 
GPU-Accelerated Biophotonics & Biomedical Optics
This week’s spotlight is on Alexander       Doronin, a PhD candidate in the Biophotonics &       Biomedical Imaging Research Group at the University of Otago in New       Zealand.

His research interests include biophotonics, light-tissue interaction,       Monte Carlo (MC) computational modeling and parallel programming on GPUs       using CUDA.

NVIDIA: Alex, what is biophotonics?
Alex: Biophotonics refers to       the interaction between biology and photonics. Photonics is a science       that deals with the particle properties of light. A number of       revolutionary applications have arisen in the field of photonics as a       result of advancements in high technology and the miniaturization of       solid-state optical/laser devices. A recent trend is the mapping of       photonics technologies to the life sciences and medicine — hence the       term “biophotonics” was coined. It is a fast moving and very       exciting area of research.
NVIDIA: What’s an example of an application that could       benefit from biophotonics?
Alex: One example is cancer       diagnostics. The current, most widely-used methodology for cancer       diagnosis is histological analysis with microscopy. However,       morphological variations (and especially morphological changes associated       with early grades of cancer tissue) are difficult to resolve regarding       what type or sub-type of cancer is present.

In our research, we are investigating the use of circular polarized light       — and the manipulation of the coherent properties of light — to improve       cancer diagnostics. The technique has the potential to revolutionize the       ability to detect cancer at the very early stage.

NVIDIA: Tell us about the online Monte Carlo tool developed       by your group.
Alex: With the       rapid growth of the Internet, rich, browser-based applications have       become more and more popular. Solutions such as Google Apps, Google Docs,       online video sharing and gaming portals have become a large part of our       everyday life.

Leveraging modern, web-based technology, we have created a free online MC       computational tool for researchers in the area of biophotonics and       biomedical optics. On the server side, the tool is accelerated by CUDA       GPUs. On the client side, a lightweight, user-friendly web interface       allows multiple clients to set up optical system parameters, perform       modeling, and download results in a typical journal paper format.

We are currently extending our GPU cluster with additional Tesla M2090s       and are expecting even more performance. The online MC tool is made       available to the worldwide biophotonics community through the       Biophotonics & Biomedical Imaging Research Group, which is headed up       by my supervisor, Dr. Igor Meglinski.

  - Read the complete interview here

  (Would you like to be in the CUDA Spotlight? Email     cuda_week_in_review@nvidia.com)

 
GTC Asia Announced

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NVIDIA announced GTC Asia, the next major event in NVIDIA’s     international series of GPU Technology Conference (GTC) events. GTC Asia     will take place on Dec. 14-15, 2011 at the China National Convention Center     in Beijing. www.gputechconf.cn
GTC Worldwide Call for     Submissions
NVIDIA is now accepting poster proposals for the following events:
- GTC Express Live Theater @ SC11 (Nov. 12-18, 2011)
- GTC Asia 2011 (Dec. 14-15, 2011)
- GTC U.S. 2012 (May 14-17, 2012)
See: http://bit.ly/pLlsph
Project Maximus Update
NVIDIA’s ‘Project Maximus’ is an initiative to build a technology platform     that enables workstation applications to take advantage of multi-GPU     computing. By adding the computational power of a Tesla GPU with the     advanced graphics capability of Quadro, users will be able to experience     the highest level of productivity. Read what AnandTech’s Ryan Smith says     about it: http://bit.ly/rpxoE6

A GPU Mini-Supercomputer for Every     Scientist
The new GPU Starter Kit from HP is a pre-configured system that provides     researchers with a ready-to-use GPU computing cluster, straight out of the     box. It combines eight HP ProLiant SL390 G7 servers (containing 24 Tesla     M2070 GPUs) with 16 CPUs. It is pre-configured with CUDA 4.0. For info,     read Roy Kim’s recent blog on A GPU Mini-Supercomputer for Every Scientist or send an     email to: Hpc-sales@hp.com

MAGMA v1.0 Supports Tesla GPUs
The Innovative Computing Laboratory (ICL) at University of Tennessee has     released MAGMA v1.0 with support for NVIDIA Tesla GPUs. The MAGMA (Matrix     Algebra for GPU and Multicore Architectures) Project aims to create a next     generation of linear algebra libraries on heterogeneous systems. The ICL is     directed by Dr. Jack Dongarra. http://icl.cs.utk.edu/magma/software/index.html

Gaussian to Support     GPU Acceleration
NVIDIA, Gaussian, Inc., and The Portland Group (PGI) will develop a     GPU-accelerated release of Gaussian, the quantum chemistry software app.     Dr. Michael Frisch, president of Gaussian, said: “By coordinating the     development of hardware, compiler technology and application software, the     new app will bring the speed and cost-effectiveness of GPUs to the     challenging problems and applications that Gaussian’s customers need to     address.” http://www.nvidia.com/object/newsroom.html

 
A GPU Mini-Supercomputer for Every Scientist, by Roy     Kim

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NEW: Each week we     highlight sessions from GTC 2010 and ISC 2011. Here are     our picks for this week:

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      Enabling     On Demand Value-At-Risk for Financial Markets (GTC 10)
Matthew Dixon – UC Davis and Jike Chong     – Parasians
http://nvidia.fullviewmedia.com/gtc2010/0923-a7-2098.html

Texture Unit in     3D Volume Reconstruction (ISC 2011)
Karl Schwartz – Siemens AG
http://www.nvidia.com/content/PDF/isc-2011/Schwarz.pdf

 
NEW: Dell     is seeking a systems engineer for its HPC engineering team in Austin, TX.     Experience with GPUs, CUDA and/or OpenCL required. http://bit.ly/nSzOVD

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If you are travelling to any of these locations, feel free to     drop in to a GPU Meetup. Visitors are welcome.

- United States
Boston GPU Meetup – Sept. 1, 6:00 pm
New York GPU Meetup – (Special Meeting) Sept.     8, 6:00 pm
Silicon Valley GPU Meetup – Sept. 12, 6:15 pm
New York GPU Meetup – Sept. 26, 6:00 pm
Boston GPU Meetup – Oct. 6, 6:00 pm

- Australia
Sydney GPU Meetup – Sept. 15, 6:00 pm
Brisbane GPU Meetup – Sept. 15, 6:00 pm

 
August 2011

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- In-Depth CUDA Training       (Presented by Acceleware, with Microsoft)

Aug. 30-Sept. 2, 2011, Chicago, Illinois
http://acceleware.com/aug30chicago

- NEW: ANSYS Regional Conference

Aug. 30, 2011, Chicago, Illinois
http://ansys.com/Conference/Chicago/

- NEW: ANSYS Regional Conference

Aug. 31-Sept. 1, 2011, Houston, Texas
http://ansys.com/Conference/Houston/
September 2011

- Advanced Numerical Methods on GPUs

Mini-symposium at ENUMATH 2011
Sept. 5-9, 2011, Univ. of Leicester, Leicester, UK
http://www2.le.ac.uk/departments/mathematics/research/enumath2011/minisymposia

- NEW: GPU Direct and Unified Virtual Addressing (Webinar)

Sept. 6, 2011
Presented by Timothy Schroeder, NVIDIA
https://www2.gotomeeting.com/register/410023659

- Parallel Processing and Applied Mathematics (PPAM 2011)

Sept. 11-14, 2011, Torun, Poland
Note: Scientific Computing with GPUs tutorial, incl.         session by Tim Schroeder, NVIDIA
http://ppam.pl/tutorials/21

- Geospatial Summit

Sept. 13-14, 2011, Herndon, Virginia
http://cfp.foseinstitute.org/gis2011

- Rapid Problem Solving Using Thrust (Webinar)

Sept. 14, 2011
Presented by Nathan Bell, NVIDIA
Note: Thrust is a library that enables programmers to         develop high-performance applications on CUDA with minimal effort.
http://www.gputechconf.com/object/gtc-express-webinar.html

- CUDA Course (Presented by SagivTech)

Sept. 18-20, 2011, Ramat Gan, Israel
Hands-on sessions and optimization techniques.
http://www.sagivtech.com/24054.html

- SEG (Society of Exploration Geophysicists) Annual Meeting

Sept. 18-23, 2011, San Antonio, Tex.
http://www.seg.org/events/annual-meeting/sanantonio2011/am2011techprogram

- CUDA Course (Presented by Tech-X)

Sept. 19-21, Boulder, Colorado
http://www.txcorp.com/products/GPULib/cuda_training/download.php

- Russian-German HPC School

Sept. 19-30, Novosibirsk
http://conf.nsc.ru/hpcschool

- SPIE Conference on High-Performance Computing in Remote       Sensing

Sept. 19-22, 2011, Prague, Czech Republic
http://spie.org/rs11

- NEW: CUDA Optimization: Memory Bandwidth Limited Kernels       (Webinar)

Sept. 20, 2011
Presented by Timothy Schroeder, NVIDIA
https://www2.gotomeeting.com/register/936728978

- NEW: CUDA Optimization: Instruction Limited Kernels (Webinar)

Sept. 27, 2011
Presented by Gernot Ziegler, NVIDIA
https://www2.gotomeeting.com/register/260445946

- NEW: GPU-Accelerated Derivative Pricing Models

Sept. 27, 2011, New York
Presented by SciComp, NVIDIA, Dell, Microsoft
http://www.scicomp.com/seminars/2011/signup

October 2011

- NEW: CUDA Optimization:       Register Spilling and Local Memory Usage (Webinar)

Oct. 4, 2011
Presented by Paulius Micikevicius, NVIDIA
https://www2.gotomeeting.com/register/273766338

- NEW: GPU-Accelerated Derivative Pricing Models

Presented by SciComp, NVIDIA, Dell, Microsoft
Oct. 17, 2011, London, UK
http://www.scicomp.com/seminars/2011/signup

November 2011

- NEW: Supercomputing       2011 (SC11)

Nov. 12-18, Seattle, Washington
http://sc11.supercomputing.org/

(To list an event, email: cuda_week_in_review@nvidia.com)

 
Downloads

back to the top

– CUDA 4.0: www.nvidia.com/getcuda
– Parallel Nsight: http://developer.nvidia.com/nvidia-parallel-nsight
Webinars
– CUDA: www.nvidia.com/webinars
– Parallel Nsight: http://developer.nvidia.com/developer-webinars
CUDA     Registered Developer Program
– Sign up: www.nvidia.com/paralleldeveloper
CUDA     GPUs
– List of CUDA-enabled GPUs: http://developer.nvidia.com/cuda-gpus
CUDA     on the Web
– See previous issues of CUDA: Week in Review: http://is.gd/cBXbg
– Follow CUDA & GPU Computing on Twitter: www.twitter.com/gpucomputing
– Network with other developers: www.gpucomputing.net
– Stayed tuned to GPGPU news and events: www.gpgpu.org
– Learn more about CUDA on CUDA Zone: www.nvidia.com/cuda
– Check out the NVIDIA Research page: www.nvidia.com/research
CUDA     Recommended Reading
– Future of Computing Performance: http://bit.ly/hYqH2H
– Supercomputing for the Masses, Part 21: http://is.gd/Fj56gf
– CUDA books: http://www.nvidia.com/object/cuda_books.html
CUDA     Recommended Viewing
– The Third Pillar of Science: www.nvidia.com/object/race-for-better-science.html
– GTC 2010 presentations: www.nvidia.com/gtc
– SC10 presentations: www.nvidia.com/object/sc10_theater.html
 
CUDA is NVIDIA’s parallel computing hardware architecture.     NVIDIA provides a complete toolkit for programming on the CUDA architecture,     supporting standard computing languages such as C, C++ and Fortran as well     as APIs such as OpenCL and DirectCompute. Send comments and suggestions to:     cuda_week_in_review@nvidia.com
 
You are receiving this email because you have previously     expressed interest in NVIDIA products and technologies. Click here     to opt in specifically to CUDA: Week in Review.

Feel free to forward this email to customers, partners and     colleagues.

Please note that this message was sent to the following email address: (ccole@nvidia.com)
If you would like to stop receiving emails from NVIDIA, click here to     unsubscribe.

Copyright © 2011 NVIDIA Corporation. All rights reserved. 2701 San Tomas     Expressway, Santa Clara, CA 95050.

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Tygodniowy newsletter “CUDA: Week in Review.” – 22.08.2011

 

Mon., August 22, 2011, Issue #60

Click     here for online version

 

WELCOME
Welcome to CUDA:         Week in Review, an online news summary for the         worldwide CUDA, GPU computing and parallel programming ecosystem.
CUDA SPOTLIGHT
Dr. Ross Walker, UCSD
CUDA TOP STORIES
CUDA Apps         News Roundup
Stanford         Seminars on CUDA
SC 2011 –         Register Today
ANSYS         Regional Conferences
 
CONTENTS
CUDA SPOTLIGHT
CUDA DEVELOPER NEWS
NEW ON THE BLOG
REPLAYS OF THE WEEK
CUDA JOBS
GPU MEETUPS
CUDA CALENDAR
CUDA RESOURCES
Sign         up to be a CUDA Registered Developer
Follow         @GPUComputing on Twitter

 

 
GPU-Accelerated Molecular Dynamics
This week’s spotlight is on Dr.       Ross Walker, assistant research professor with the San       Diego Supercomputer Center (SDSC) at UC San Diego and adjunct assistant       professor in the Department of Chemistry and Biochemistry at UC San       Diego.

Dr. Walker is a lead developer of AMBER (Assisted Model Building with Energy       Refinement), a Molecular Dynamics (MD) software package for the       simulation of biomolecules. A new update of AMBER, focusing on improved       GPU acceleration, was recently made available to the public.

NVIDIA: Ross, tell us about the AMBER news announcement.
Ross: The announcement       concerns a large scale update to the GPU acceleration support in AMBER.       This is something we have been working on for the last nine months with       funding from the National Science Foundation’s Scientific Software       Infrastructure and Innovation program, in close collaboration with       NVIDIA.
NVIDIA: What are potential applications of GPU-accelerated       AMBER?
Ross: The latest update to       GPU-accelerated AMBER provides performance that was previously       unattainable, even with the fastest supercomputers. Thus we are now in a       realm where for the first time we are talking about increasing capability       and not just GPU acceleration. This widens the scope for the types of       scientific questions one can attempt to solve.
NVIDIA: What kind of advantages have you achieved with CUDA?
Ross: I cannot       begin to do justice to the revolution that GPU acceleration through CUDA       is having on Molecular Dynamics. The GPU acceleration of MD through CUDA       is, for the first time, making it possible for scientists to ‘experiment’       computationally. With our latest update, the performance of the code on a       single Tesla M2090 GPU outstrips that achievable on 192 nodes of a Cray       XT5 supercomputer.
NVIDIA: When you think about the future of Molecular       Dynamics, what excites you the most?
Ross: We are       only just beginning to scratch the surface in the types of questions we       can ask with Molecular Dynamics. Traditionally it has been too slow and       computationally expensive to make a significant impact in the drug       discovery process but with GPU acceleration we are now at a point where       the accuracy of MD approaches is no longer limited by the amount of sampling       that can be done.
  - Read the complete interview here

  (Would you like to be in the CUDA Spotlight? Email     cuda_week_in_review@nvidia.com)

 
CUDA Apps Roundup: New     Releases and Updates

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- PGI CUDA Fortran v11.8 – CUDA development tool. www.pgroup.com/cudafortran
- ATL SeqNFind – Genomics toolset for bioinformatics. http://bit.ly/pexBP2
- TidePowerd GPU.NET v2.0 – New features. http://bit.ly/nNwk2m
- AccelerEyes Jacket v1.8 and LibJacket v1.1. http://bit.ly/n7zNl2
- CUDPP release v2.0 – CUDA data-parallel primitives library. http://bit.ly/nsbwx5
- TunaCode CUVI v0.5 – Image processing. http://cuvilib.com
- rCUDA v3.0 – CUDA calls to remote GPUs. http://bit.ly/n5vdV9
- Odeint – C++ library for ordinary differential equations. http://bit.ly/qeNeE3
Stanford     Seminars on High Performance Computing with CUDA
Stanford has posted videos from the Spring 2011 seminar series held at the     Institute for Computational and Mathematical Engineering (ICME). The ICME     is directed by Professor Margot Gerritsen.
- Lecture 1: Intro to HPC with CUDA 1 (Cyril Zeller)
- Lecture 2: Intro to HPC with CUDA 2 (Justin Luitjens)
- Lecture 3: Optimizations 1 – Global Memory (Inderaj Bains)
- Lecture 4: Optimizations 2 – Shared Memory (Steven Rennich)
- Lecture 5: Finite Difference Stencils on Regular Grids (Paulius     Micikevicius)
For videos, see: http://bit.ly/osrgYk
For slides, see: http://bit.ly/pYAEqN

SC 2011 – Register Today
- It’s not too early to register for SC 2011 in Seattle, Washington. The     theme of the conference is Data Intensive Science: http://bit.ly/qRLIcB
- For a trip down memory lane, see proceedings from the inaugural SC     conference in 1989: http://bit.ly/n4SPrC

ANSYS Regional Conferences
ANSYS, developer of CAE (computer-aided engineering) software, is hosting a     series of regional conferences for end-users. The meetings are targeted to     designers, engineers, analysts, managers and executives who are solving     next-generation engineering challenges.
- To register, see: http://www.ansys.com/Conference
- To read more about NVIDIA and ANSYS, see: http://bit.ly/nOXze3

 
GPUs Crunch Data from Square Kilometer-Sized Radio     Telescope, by Heather Mackay

back to the top

 
NEW: Each week we     highlight sessions from GTC 2010 and ISC 2011. Here are     our picks for this week:

back to the top

      Harnessing     the GPU to Accelerate Automotive Development (GTC 10)
Igor Juric and Tomislav Bosko – Dok-Ing
http://nvidia.fullviewmedia.com/gtc2010/0921-d-2304.html

Real-time     Visualization of Medical Images (ISC 2011)
Massimo Bernaschi – University La     Sapienza
http://www.nvidia.com/content/PDF/isc-2011/Bernaschi.pdf

 
NEW: Aptina Imaging is     looking for talented software engineers to join the imaging solutions     development team in San Jose, Calif. Required: Experience with GPGPU,     OpenCL or CUDA; 3+ years of consumer software development in C++.
See: http://bit.ly/pL7CVN

back to the top

 
If you are travelling to any of these locations, feel free to     drop in. Visitors are welcome.

- United States
New York GPU Meetup – Aug. 22, 6:00 pm
South Florida GPU Meetup – Aug. 29, 6:30 pm (Inaugural meeting!)
Denver/Boulder GPU Meetup – Aug. 29, 6:30 pm
Boston GPU Meetup – Sept. 1, 6:00 pm
New York GPU Meetup –     Sept. 8, 6:00 pm (Special meeting)
Silicon Valley GPU Meetup – Sept. 12, 6:15 pm

- Australia
Sydney GPU Meetup – Sept. 15, 6:00 pm

 
August 2011

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- NEW: CUDA Optimization       (Webinar)

Aug. 23, 2011
Presented by Paulius Micikevicius, NVIDIA
Note: First in a new series of optimization webinars
http://www.gputechconf.com/object/gtc-express-webinar.html

- NEW: In-Depth CUDA Training (Presented by Acceleware, with       Microsoft)

Aug. 30-Sept. 2, 2011, Chicago, Illinois
http://acceleware.com/aug30chicago
September 2011

- Advanced Numerical Methods on GPUs

Mini-symposium at ENUMATH 2011
Sept. 5-9, 2011, Univ. of Leicester, Leicester, UK
http://www2.le.ac.uk/departments/mathematics/research/enumath2011/minisymposia

- Parallel Processing and Applied Mathematics (PPAM 2011)

Sept. 11-14, 2011, Torun, Poland
Note: Scientific Computing with GPUs tutorial, incl.         session by Tim Schroeder, NVIDIA
http://ppam.pl/tutorials/21

- Geospatial Summit

Sept. 13-14, 2011, Herndon, Virginia
http://cfp.foseinstitute.org/gis2011

- Rapid Problem Solving Using Thrust (Webinar)

Sept. 14, 2011
Presented by Nathan Bell, NVIDIA
Note: Thrust is a library that enables programmers to         develop high-performance applications on CUDA with minimal effort.
http://www.gputechconf.com/object/gtc-express-webinar.html

- CUDA Course (Presented by SagivTech)

Sept. 18-20, 2011, Ramat Gan, Israel
Hands-on sessions and optimization techniques.
http://www.sagivtech.com/24054.html

- CUDA Course (Presented by Tech-X)

Sept. 19-21, Boulder, Colorado
http://www.txcorp.com/products/GPULib/cuda_training/download.php

- Russian-German HPC School

Sept. 19-30, Novosibirsk
http://conf.nsc.ru/hpcschool

- SPIE Conference on High-Performance Computing in Remote       Sensing

Sept. 19-22, 2011, Prague, Czech Republic
http://spie.org/rs11

- SEG (Society of Exploration Geophysicists) Annual Meeting

Sept. 18-23, 2011, San Antonio, Tex.
http://www.seg.org/events/annual-meeting/sanantonio2011/am2011techprogram

 

(To list an event, email: cuda_week_in_review@nvidia.com)

 
Downloads

back to the top

– CUDA 4.0: www.nvidia.com/getcuda
– Parallel Nsight: http://developer.nvidia.com/nvidia-parallel-nsight
Webinars
– CUDA: www.nvidia.com/webinars
– Parallel Nsight: http://developer.nvidia.com/developer-webinars
CUDA     Registered Developer Program
– Sign up: www.nvidia.com/paralleldeveloper
CUDA     GPUs
– List of CUDA-enabled GPUs: www.nvidia.com/object/cuda_gpus.html
CUDA     on the Web
– See previous issues of CUDA: Week in Review: http://is.gd/cBXbg
– Follow CUDA & GPU Computing on Twitter: www.twitter.com/gpucomputing
– Network with other developers: www.gpucomputing.net
– Stayed tuned to GPGPU news and events: www.gpgpu.org
– Learn more about CUDA on CUDA Zone: www.nvidia.com/cuda
– Check out the NVIDIA Research page: www.nvidia.com/research
CUDA     Recommended Reading
– Future of Computing Performance: http://bit.ly/hYqH2H
– Supercomputing for the Masses, Part 21: http://is.gd/Fj56gf
– CUDA books: http://www.nvidia.com/object/cuda_books.html
CUDA     Recommended Viewing
– The Third Pillar of Science: www.nvidia.com/object/race-for-better-science.html
– GTC 2010 presentations: www.nvidia.com/gtc
– SC10 presentations: www.nvidia.com/object/sc10_theater.html
 
CUDA is NVIDIA’s parallel computing hardware architecture.     NVIDIA provides a complete toolkit for programming on the CUDA     architecture, supporting standard computing languages such as C, C++ and     Fortran as well as APIs such as OpenCL and DirectCompute. Send comments and     suggestions to: cuda_week_in_review@nvidia.com
 
You are receiving this email because you have previously     expressed interest in NVIDIA products and technologies. Click here     to opt in specifically to CUDA: Week in Review.

Feel free to forward this email to customers, partners and     colleagues.

Copyright © 2011 NVIDIA Corporation. All rights reserved. 2701 San Tomas     Expressway, Santa Clara, CA 95050.

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Tygodniowy newsletter “CUDA: Week in Review.” – 12.08.2011

 

Fri., August 12, 2011, Issue #59

Click     here     for online version

 

WELCOME
Welcome to CUDA:         Week in Review, an online news summary for the         worldwide CUDA, GPU computing and parallel programming ecosystem.
CUDA SPOTLIGHT
Dr. Denis Bastieri, University of Padua
CUDA TOP STORIES
Forrester on JP Morgan, NVIDIA
New Video: Intro to CUDA
Upcoming CUDA Webinars
New CUDA Courses
CUDA in Academia
 
CONTENTS
CUDA SPOTLIGHT
CUDA DEVELOPER NEWS
NEW ON THE BLOG
REPLAYS OF THE WEEK
CUDA JOBS
GPU MEETUPS
CUDA CALENDAR
CUDA RESOURCES
Sign         up to be a CUDA         Registered Developer
Follow         @GPUComputing on Twitter

 

GPU-Accelerated Astronomy
This week’s Spotlight is on Denis Bastieri of the University of Padua,       Italy, and co-founder of Mimesis HPC.

Dr. Bastieri leads the NASA Fermi Large Area Telescope (LAT) team for the       National Institute of Nuclear Physics (INFN) in Padua. Here’s a preview       of our interview:

NVIDIA: Denis, tell us about the Fermi Space Telescope.
Denis: The       Fermi mission is part of NASA’s focus on the theme of “Structure and       Evolution of the Universe.” I specifically work with one of the two       instruments aboard the Fermi spacecraft — the Large Area Telescope       (LAT), which observes gamma rays, the electromagnetic radiation with the       highest energy.
NVIDIA: Which organizations are involved in the project?
Denis: Fermi       is a joint project between NASA, the U.S. Department of Energy and academic       and research institutions across France, Germany, Japan, Italy and       Sweden. The spacecraft was built by General Dynamics. Institutions in the       LAT collaboration are listed at http://www-glast.stanford.edu/cgi-bin/collab_inst
NVIDIA: What role does NVIDIA technology play?
Denis: Parallel       computing is the only viable solution when dealing with many different       aspects of astrophysics, and GPUs perform parallel computing at a tenth       of the cost of conventional systems. Proof of the momentum behind GPUs       can be seen in the exponentially growing number of astrophysics papers       with “GPU” listed in the abstract!
NVIDIA: What are the benefits of working with CUDA?
Denis: We       started looking at parallel computing on GPUs back during the time of Cg       (C for Graphics). The subject looked tantalizing: different textures for       positions and velocities and we could model the evolution of a particle       population in an external field. The results were quite promising, but Cg       was not ideal for astrophysical modeling and we were almost going to       dismiss the project entirely.

Then, CUDA was released in late 2006. We found programming in CUDA to be       quite straightforward for any good C programmer. Our students       demonstrated that they could become independent within a semester.

And now, CUDA 4.0 is even better! We utilize the Thrust algorithms       library. We leverage Unified Virtual Address (UVA) to extend GPU memory       capabilities. The CURAND library replaced our own version of a random       number generator. CUDA allows us to fully exploit the performance of our       16 GPU cluster.

NVIDIA: What’s next in the field of astronomy? What are you       most excited about?
Denis: We are       gaining more and more confidence in our modeling of the high-energy gamma       ray emission of the universe. We understand by now what is the contribution       from standard sources: pulsars, known galaxies, etc. But we are not able       to explain all the data we collected! Something is missing and we have to       understand what. Hints of a new population of gamma-ray emitters? The       elusive Dark Matter starting to show up? Quoting Sherlock Holmes:       “Whatever remains, however improbable, must be the truth!”

But this is just the “near” future: developing new, fast       techniques to analyze data and find the improbable. The real future? We       still have to shape it! We want to expand our GPU cluster, hire people,       start new projects; in a word, we want to understand what it takes to       build next-generation observatories. For a taste of what’s to come, keep       an eye on the DARPA/NVIDIA exascale       computing       project!

  - Read the complete interview here

  (Would you like to be in the CUDA Spotlight? Email     cuda_week_in_review@nvidia.com)

Forrester on JP     Morgan Chase, NVIDIA

back     to the top

Analyst Rich Fichera of Forrester recently blogged about the     use of Tesla GPUs in JP Morgan Chase’s Equity Derivatives Group. The bank’s     hybrid GPU/CPU systems achieved a 40X acceleration in risk calculation     times combined with a sizable cost savings. Fichera writes: “If you     are an I&O professional whose users are demanding extreme     computational performance on a constrained space, power and capital budget,     you owe it to yourself and your company to evaluate the newest accelerator     technology. Your competitors are almost certainly doing so.”
- See: http://bit.ly/qvZ496
New Video: Intro to     CUDA
NVIDIA’s Cliff Woolley provides an introduction to CUDA in this new five     minute video posted on GPUGenius: http://bit.ly/nK5wKO

Upcoming CUDA Webinars
- NVIDIA’s Justin Luitjens will discuss CUDA Libraries on Tues., Aug. 16,     including a live Q&A: http://bit.ly/oGTbH5     (CUDA Registered Developer Series)
- NVIDIA’s Nathan Bell will present “Rapid Problem Solving Using     Thrust” on Wed., Sept. 14: http://bit.ly/qaWqLD     (GTC Express Series)

New CUDA Courses
- SagivTech is offering a three-day CUDA course on Sept. 18-20 in Ramat     Gan, Israel. The class will be conducted in a hands-on computer lab: http://www.sagivtech.com/24054.html
- Tech-X Corporation will present a three-day workshop on GPU computing     with CUDA on Sept. 19-21 in Boulder, Colorado: http://www.txcorp.com/products/GPULib/cuda_training/download.php

CUDA in Academia
- Congrats to Francisco Igual, Universitat Jaume I, Spain, on publication     of his Ph.D. thesis on matrix computations and GPUs: http://www3.uji.es/~figual/Tesis/tesis.pdf
- Dr. Manuel Carcenac is teaching a course on CUDA at the European     University of Lefke in North Cyprus: http://bit.ly/qCBJbx
- The Russian-German School on High Performance Computing will hold a     series of courses on Sept. 19-30 in Novosibirsk: http://conf.nsc.ru/hpcschool2011/
- A one-month CUDA programming course is being taught by Ph.D. student Christopher     Cooper at the Universidad Técnica Federico Santa María in Chile: http://bit.ly/oBK54P
- Learn about NVIDIA’s Academic Partnership Program: http://bit.ly/nM1S25

And     the Winners of the NVART Competition Are…,     by Will Park
NVIDIA     Photorealistic Rendering Demo at SIGGRAPH, by Phil     Miller
J.P.     Morgan Achieves 40X Speed-up in Risk Computation,     by George Millington
GPU     Technology Conference: 1000 Strong in Tokyo,     by Victoria Crimmins
An     Inspiring Morning, by Hector Marinez

back     to the top

NEW: Each week we     highlight sessions from GTC 2010     and ISC     2011. Here are our picks for this week:

back     to the top

      GPU     Cluster Computing: Accelerating Scientific Discovery (GTC 10)
John Taylor – CSIRO
http://nvidia.fullviewmedia.com/gtc2010/0923-a2-2301.html

Real-time     Visualization of Medical Images (ISC 2011)
Erik Steen – GE Ultrasound
http://www.nvidia.com/content/PDF/isc-2011/Steen.pdf

NEW: Ion Torrent, a     subsidiary of Life Technologies in South San Francisco, CA, is seeking an     exceptional software engineer with extensive high performance computing     experience, one who is highly creative, loves to code, and wants to build     and ship software for a disruptive technology. Reference REQ# 5549. See: http://www.iontorrent.com     and http://www.lifetechnologies.com/

back     to the top

If you are travelling to any of these locations, feel free to     drop in. Visitors are welcome, especially to the inaugural Meetups in     Washington, DC and South Florida.

- United States
Silicon     Valley GPU Meetup – Aug. 15, 6:15 pm
Wash.     DC GPU Meetup – Aug. 18, 5:30 pm (inaugural meeting!)
Austin     GPU Meetup – Aug. 19, 6:00 pm
New     York GPU Meetup – Aug. 22, 6:00 pm
South     Florida GPU Meetup – Aug. 29, 6:30 pm (inaugural     meeting!)
Boston     GPU Meetup – Sept. 1, 6:00 pm
New     York – Special GPU Meetup – Sept. 8, 6:00 pm     (with head of NV
Research)

- Australia
Brisbane     GPU Meetup – Aug. 18, 6:00 pm
Sydney     GPU Meetup – Sept. 15, 6:00 pm

August 2011

back to the top

 

- Par Lab Boot Camp (Short       Course on Parallel Computing)

Aug. 15-17, 2011, UC Berkeley, Berkeley, California
http://conta.cc/njsSB9

- Proven Algorithmic Techniques for Manycore Processors       (Hands-On Course)

Aug. 15-19, 2011 (at multiple locations via         videoconferencing)
Note: Sponsored by the Virtual School of Computational         Science and Engineering (VSCSE)
www.vscse.org

- NEW: CUDA Libraries (Webinar)

Presented by Justin Luitjens, NVIDIA
Aug. 16, 2011
http://bit.ly/oGTbH5

- NEW: In-Depth CUDA Training (Presented by Acceleware, with       Microsoft)

Aug. 30-Sept. 2, 2011, Chicago, Illinois
http://acceleware.com/aug30chicago
September 2011

- Advanced Numerical Methods on GPUs

Mini-symposium at ENUMATH 2011
Sept. 5-9, 2011, Univ. of Leicester, Leicester, UK
http://www2.le.ac.uk/departments/mathematics/research/enumath2011/minisymposia

- Parallel Processing and Applied Mathematics (PPAM 2011)

Sept. 11-14, 2011, Torun, Poland
Note: Scientific Computing with GPUs tutorial, incl.         session by Tim Schroeder, NVIDIA
http://ppam.pl/tutorials/21

- Geospatial Summit

Sept. 13-14, 2011, Herndon, Virginia
http://cfp.foseinstitute.org/gis2011

- Rapid Problem Solving Using Thrust (Webinar)

Sept. 14, 2011
Presented by Nathan Bell, NVIDIA
Note: Thrust is a library that enables programmers to         develop high-performance applications on CUDA with minimal effort.
http://www.gputechconf.com/object/gtc-express-webinar.html

- NEW: CUDA Course (Presented by SagivTech)

Sept. 18-20, 2011, Ramat Gan, Israel
Hands-on sessions and optimization techniques.
http://www.sagivtech.com/24054.html

- NEW: CUDA Course (Presented by Tech-X)

Sept. 19-21, Boulder, Colorado
http://www.txcorp.com/products/GPULib/cuda_training/download.php

- NEW: Russian-German HPC School

Sept. 19-30, Novosibirsk
http://conf.nsc.ru/hpcschool

- SPIE Conference on High-Performance Computing in Remote       Sensing

Sept. 19-22, 2011, Prague, Czech Republic
http://spie.org/rs11

- SEG (Society of Exploration Geophysicists) Annual Meeting

Sept. 18-23, 2011, San Antonio, Tex.
http://www.seg.org/events/annual-meeting/sanantonio2011/am2011techprogram

 

(To list an event, email: cuda_week_in_review@nvidia.com)

Downloads

back to the top

– CUDA 4.0: www.nvidia.com/getcuda
– Parallel Nsight: http://developer.nvidia.com/nvidia-parallel-nsight
Webinars
– CUDA: http://developer.nvidia.com/gpu-computing-webinars
– Parallel Nsight: http://developer.nvidia.com/developer-webinars
CUDA     Registered Developer Program
– Sign up: www.nvidia.com/paralleldeveloper
CUDA     GPUs
– List of CUDA-enabled GPUs: www.nvidia.com/object/cuda_gpus.html
CUDA     on the Web
– See previous issues of CUDA: Week in Review: http://is.gd/cBXbg
– Follow CUDA & GPU Computing on Twitter: www.twitter.com/gpucomputing
– Network with other developers: www.gpucomputing.net
– Stayed tuned to GPGPU news and events: www.gpgpu.org
– Learn more about CUDA on CUDA Zone: www.nvidia.com/cuda
– Check out the NVIDIA Research page: www.nvidia.com/research
CUDA     Recommended Reading
– Future of Computing Performance: http://bit.ly/hYqH2H
– Supercomputing for the Masses, Part 21: http://is.gd/Fj56gf
– CUDA books: http://www.nvidia.com/object/cuda_books.html
CUDA     Recommended Viewing
– The Third Pillar of Science: www.nvidia.com/object/race-for-better-science.html
– GTC 2010 presentations: www.nvidia.com/gtc
– SC10 presentations: www.nvidia.com/object/sc10_theater.html
CUDA is NVIDIA’s parallel computing hardware architecture.     NVIDIA provides a complete toolkit for programming on the CUDA     architecture, supporting standard computing languages such as C, C++ and     Fortran as well as APIs such as OpenCL and DirectCompute. Send comments and     suggestions to: cuda_week_in_review@nvidia.com
You are receiving this email because you have previously     expressed interest in NVIDIA products and technologies. Click here     to opt in specifically to CUDA: Week in Review.

Feel free to forward this email to customers, partners and     colleagues.

Copyright © 2011 NVIDIA Corporation. All rights reserved. 2701 San Tomas     Expressway, Santa Clara, CA 95050.

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Tygodniowy newsletter “CUDA: Week in Review.” – 21.07.2011

 

Thurs., July 21, 2011, Issue #58

Click     here for online version

 

WELCOME
Welcome to CUDA:         Week in Review, an online news summary for the         worldwide CUDA, GPU computing and parallel programming ecosystem.
CUDA SPOTLIGHT
Jesse Rosenzweig, Elemental Technologies
CUDA TOP STORIES
Stanford:         New CUDA Center of Excellence
PGI CUDA-x86         Shipping
FastROCS         for Drug Discovery
Encryption         with CUDA
GPUs at NASA
 
CONTENTS
CUDA SPOTLIGHT
CUDA DEVELOPER NEWS
NEW ON THE BLOG
REPLAYS OF THE WEEK
CUDA JOBS
GPU MEETUPS
CUDA CALENDAR
CUDA RESOURCES
Sign         up to be a CUDA Registered Developer
Follow         @GPUComputing on Twitter

 

 
GPU-Accelerated Video Processing
This week’s Spotlight is on Jesse Rosenzweig, CTO and co-founder       of Elemental Technologies. Jesse spearheads Elemental’s application       development, quality assurance and R&D groups. Here’s an extract from       our interview:

NVIDIA: Jesse, what is your role at Elemental?
Jesse: I act       as the glue between customers, partners, and our engineering, marketing       and QA teams. In addition, I lead an R&D team that constantly builds       prototypes and scopes out future technologies to integrate into our       products. During Elemental’s early days, I wrote video codec CUDA code       (although I imagine there aren’t many of my lines left now, given the       strength of our CUDA team!).
NVIDIA: How do your products leverage GPU computing?
Jesse: Every       pixel of every frame of a video source into our system is decompressed,       processed and even recompressed using the GPU and our proprietary video       processing pipeline. This allows us to not only get extremely fast       high-quality video processing, but also to offload the CPUs to       accommodate audio processing, security, content wrapping, database       management and content serving while providing a responsive user       interface, even during a heavy system load.
NVIDIA: As CTO, why did you choose to work with GPUs?
Jesse: As       consumers look to view video on every device imaginable, the demand for       video formatting is skyrocketing and scalability is critical. As needed,       we can integrate advanced GPUs with more processors and everything will       run quicker or process in new, more resource-efficient ways.
NVIDIA: Tell us about Elemental Live.
Jesse: Elemental Live is our solution for processing live       video. It allows media companies, such as such as Comcast, Time Warner       Cable, Avail-TVN, ABC News, CBS and others, to deliver real-time content       (live events, sports, satellite feeds, etc.) to TVs, PCs, tablets and       mobile devices using the latest adaptive streaming technologies from       Adobe, Apple and Microsoft.
  - Read the complete interview here

  (Would you like to be in the CUDA Spotlight? Email     cuda_week_in_review@nvidia.com)

 
Stanford Named     CUDA Center of Excellence

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Stanford is now a CUDA Center of Excellence. The Institute     for Computational & Mathematical Engineering (ICME) at the School of     Engineering will spearhead the program in partnership with other     departments, including the Dept. of Computer Science (CS), the Center for     Computational Earth and Environmental Sciences (CEES) and the Dept. of     Mechanical Engineering, Flow Physics Division.
- See: http://bit.ly/qvNBHE
PGI CUDA-x86 Shipping
PGI is shipping its CUDA C/C++ compiler for x86. PGI CUDA-x86 processes     CUDA C and CUDA C++ as a native parallel programming language to run on     multi-core x86. With this release, developers can compile and execute a     variety of CUDA C and CUDA C++ codes to run on x86 today. A 15-day free     trial is available.
- See: www.pgroup.com/cuda-x86

FastROCS for Drug Discovery
FastROCS is now publicly available from OpenEye Scientific Software.     FastROCS is an extremely fast 3D molecular shape comparison program running     on Tesla GPUs. It was developed in collaboration with industry partners     including Abbott Labs and Pfizer.
- See: www.eyesopen.com/fastrocs

Encryption with CUDA
Xoom Data Services announced its CudaCrypt encryption software, which uses     the GPU to process large files like video and engineering plans with     “military-grade” security. CEO Robert Gagnon says: “We move     data from point A to point B and we make sure people can’t steal it in the     middle.”
- See: http://www.prweb.com/releases/2011/6/prweb8594876.htm

GPUs at NASA
SC Online reported that simulations of Earth and space phenomena at NASA’s     Goddard Space Flight Center are getting a boost from GPUs. Early results     demonstrate potential for significant speedups with systems ranging from     one to four GPUs in labs, up to a 64-GPU IBM iDataPlex cluster.
- See: http://bit.ly/pjETOh

GPUs in the Geosciences
A session on “High-Resolution Modeling in the Geosciences Using GPU     and Many-Core Architectures” will be held at the AGU (American     Geophysical Union) meeting in December. Session leaders are Matthew     Knepley, Univ. of Chicago; David Yuen, Univ. of Minnesota; and Adam Schultz,     Oregon State Univ. Session abstracts are due August 4.
- See: http://sites.agu.org/fallmeeting/scientific-program/session-search/530

GPUs in Military & Embedded Apps
CUDA: Week in Review readers are cordially invited to attend a special     webinar on July 26. The presentation will discuss CPU-GPU hardware     deployments in military and embedded applications. The moderator is Jeff     Child, Editor-In-Chief of COTS Journal. He will be joined by Michael     Bowling, President of Trenton Systems and Devang Sachdev of NVIDIA.
- Register: https://www2.gotomeeting.com/register/409656202
- See complete webinar schedule: www.nvidia.com/webinars

 
Drexel Takes Off to Big     Science Frontiers with GPUs, by Devang Sachdev
Cornell Collaboration     Explores GPU Computing + MATLAB, by David     Lifka, Cornell
Joining Forces with     Beijing Genomics Institute, by Kimberly Powell
CUDA Engineer Takes Busman’s Holiday in Turkey, by Ian     Buck
Fight Global Warming with GPU Computing and C++, by     Olivier Giroux

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NEW: Each week we     highlight sessions from GTC 2010 and ISC 2011. Here are     our picks for this week:

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      Using     CUDA to Accelerate Radar Image Processing (GTC 10)
Aaron Rogan – Neva Ridge Technologies
http://nvidia.fullviewmedia.com/gtc2010/0923-k-2003.html

CUDA Fortran     and CUDA Libraries (ISC 2011)
Massimiliano Fatica – NVIDIA
www.nvidia.com/content/PDF/isc-2011/Fatica.pdf

 
NEW: Pacific Biosciences     in Menlo Park, Calif., is seeking a High-Performance Computing Engineer to     be responsible for technical strategy development of an HPC environment     embedded in a DNA sequencing machine. HPC background and CUDA experience     required.
- See: http://bit.ly/q5mYyv

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If you are travelling to any of these locations, feel free to     drop in. Visitors are welcome.
New York Meetup – July 25, 6:00 pm
New Mexico Meetup – July 26, 7:00 pm
Boston Meetup – Aug. 4, 6:00 pm
Silicon Valley Meetup – Aug. 15, 6:15 pm
Wash. DC Meetup – Aug. 18, 4:00 pm (inaugural meeting)
Austin Meetup – Aug. 19, 6:00 pm
 
July 2011

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- GTC Workshop Japan

July 22, 2011, Tokyo
Hosted by NVIDIA, with the Tokyo Institute of Technology
http://www.nv-jp-event.jp/gtc-workshop2011/

- Banking with GPGPUs: Increased Performance, Lowered Costs       (Training Workshop)

July 25-27, 2011, London, UK
Note: Taught by experts from Excelian and Cranfield         University
Contact: james.heath (at) excelian.com
August 2011

- Banking with GPGPUs: Increased Performance, Lowered Costs       (Training Workshop)

Aug. 8-11, 2011, London, UK
Note: Taught by experts from Excelian and Cranfield         University
Contact: james.heath (at) excelian.com

- LAMMPS Users’ Workshop

Aug. 9-11, 2011, Albuquerque, New Mexico
Register: http://lammps.sandia.gov/workshops.html
Learn more about LAMMPS: http://lammps.sandia.gov/index.html

- NEW: Par Lab Boot Camp (Short Course on Parallel Computing)

Aug. 15-17, 2011, UC Berkeley, Berkeley, California
http://conta.cc/njsSB9

- NEW: Proven Algorithmic Techniques for Manycore Processors       (Hands-On Course)

Aug. 15-19, 2011 (at multiple locations via         videoconferencing)
Note: Sponsored by the Virtual School of Computational         Science and Engineering (VSCSE)
www.vscse.org
September 2011

- Advanced Numerical Methods on GPUs

Mini-symposium at ENUMATH 2011
Sept. 5-9, 2011, Univ. of Leicester, Leicester, UK
http://www2.le.ac.uk/departments/mathematics/research/enumath2011/minisymposia

- Parallel Processing and Applied Mathematics (PPAM 2011)

Sept. 11-14, 2011, Torun, Poland
Note: Scientific Computing with GPUs tutorial, incl.         session by Tim Schroeder, NVIDIA
http://ppam.pl/tutorials/21

- Geospatial Summit

Sept. 13-14, 2011, Herndon, Virginia
http://cfp.foseinstitute.org/gis2011

- NEW: Rapid Problem Solving Using Thrust (Webinar)

Sept. 14, 2011
Presented by Nathan Bell, NVIDIA
Note: Thrust is a library that enables programmers to         develop high-performance applications on CUDA with minimal effort.
http://www.gputechconf.com/object/gtc-express-webinar.html

- SPIE Conference on High-Performance Computing in Remote       Sensing

Sept. 19-22, 2011, Prague, Czech Republic
http://spie.org/rs11

- SEG (Society of Exploration Geophysicists) Annual Meeting

Sept. 18-23, 2011, San Antonio, Texas
http://www.seg.org/events/annual-meeting/sanantonio2011/am2011techprogram

 

(To list an event, email: cuda_week_in_review@nvidia.com)

 
Downloads

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– CUDA 4.0: www.nvidia.com/getcuda
– Parallel Nsight: http://developer.nvidia.com/nvidia-parallel-nsight
Webinars
– CUDA: http://developer.nvidia.com/gpu-computing-webinars
– Parallel Nsight: http://developer.nvidia.com/developer-webinars
CUDA     Registered Developer Program
– Sign up: www.nvidia.com/paralleldeveloper
CUDA     GPUs
– List of CUDA-enabled GPUs: www.nvidia.com/object/cuda_gpus.html
CUDA     on the Web
– See previous issues of CUDA: Week in Review: http://is.gd/cBXbg
– Follow CUDA & GPU Computing on Twitter: www.twitter.com/gpucomputing
– Network with other developers: www.gpucomputing.net
– Stayed tuned to GPGPU news and events: www.gpgpu.org
– Learn more about CUDA on CUDA Zone: www.nvidia.com/cuda
– Check out the NVIDIA Research page: www.nvidia.com/research
CUDA     Recommended Reading
– Future of Computing Performance: http://bit.ly/hYqH2H
– Supercomputing for the Masses, Part 21: http://is.gd/Fj56gf
– CUDA books: http://www.nvidia.com/object/cuda_books.html
CUDA     Recommended Viewing
– The Third Pillar of Science: www.nvidia.com/object/race-for-better-science.html
– GTC 2010 presentations: www.nvidia.com/gtc
– SC10 presentations: www.nvidia.com/object/sc10_theater.html
 
CUDA is NVIDIA’s parallel computing hardware architecture.     NVIDIA provides a complete toolkit for programming on the CUDA     architecture, supporting standard computing languages such as C, C++ and     Fortran as well as APIs such as OpenCL and DirectCompute. Send comments and     suggestions to: cuda_week_in_review@nvidia.com
 
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