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

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/

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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)

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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

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

Napisany przez e-on w Aktualności dnia 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	back to the top

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

Nov. 8, 2011

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

CUDA: WEEK IN REVIEW

CUDA 4.1 Release Candidate

2X in 4 Weeks. Guaranteed.

Leading Apps Add Multiple GPU Acceleration Support

New CULA Sparse from EM Photonics

MSC Software Announces MSC Nastran 2012

Chinese Researchers Simulate H1N1 Virus

New Research from IDC

New CUDA Course in Egypt from Applied Parallel Computing

GPU Computing Gems – Jade Edition

GPU@BU Workshop

November 2011

December 2011

Tesla MD SimCluster

Downloads

Webinars

CUDA Registered Developer Program

CUDA GPUs

CUDA on the Web

CUDA Recommended Reading

CUDA Recommended Viewing

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

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