CUDA: Week in Review
Thurs., Feb. 17, 2011, Issue #48 - Newsletter Home
Welcome to CUDA: Week in Review, an online news summary for the worldwide CUDA, GPU computing and parallel programming ecosystem.
CUDA Spotlight
    Interview with Andre R. Brodtkorb, SINTEF
CUDA Developer News
    GTC 2011 — Save The Date!
CUDA Calendar
    GPUs for ANSYS Mechanical
CUDA Spotlight
CUDA Developer News
Replays of the Week
CUDA Calendar
CUDA Resources
Twitter Follow @GPUComputing on Twitter
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NVIDIA online profiles See list of NVIDIA
online profiles
CUDA Spotlight
Modeling the Real World in Real Time
This week’s spotlight is on Andre R. Brodtkorb. Andre is a scientist at SINTEF, a research organization in Norway, where he works on GPU acceleration and algorithm design. He also teaches GPU-related courses at the Norwegian School of Information Technology. His research interests include GPU/heterogeneous computing, simulation of partial differential equations (PDEs) and real-time visualization.
NVIDIA: Andre, please tell us a bit about yourself.
Andre: I first started working with GPUs in 2005, when you could only use graphics APIs like OpenGL. At the University of Oslo, I wrote my master’s thesis on "A MATLAB Interface to the GPU," which was, to my knowledge, one of the first times the GPU was used with MATLAB.

Since then, I have been working on a lot of different applications of GPUs and parallel processing, including direct visualization and video surveillance. I recently completed my Ph.D. thesis - "Scientific Computing on Heterogeneous Architectures" - in which shallow water simulations played a central part. Shallow water simulations are extremely important in everything from tsunami warnings to simulation of storm surges and dam breaks, where processing speed is a critical factor.
NVIDIA: How does GPU computing play a role in your research?
Andre: At SINTEF, I work on a range of application areas that have strict demands for computational speed, typically real-time or faster-than-real-time. The GPU is a key piece of the puzzle to achieve these goals. Shallow water simulations, for example, can be used for both creating emergency action plans and for real-time simulation of an ongoing event. In both cases, you want high-quality results as fast as possible. A conventional CPU-based system is often not good enough, because it typically sacrifices quality. Using the GPU, on the other hand, you get high-quality results faster-than-real-time, providing a far better basis for important decisions.
  - Read full interview in the NVIDIA blog:
  - See Andre's GTC 2010 presentation:
  - Watch YouTube video:
  - For more info:

  (Would you like to be featured in the CUDA Spotlight? Email us at

CUDA Developer News
GTC 2011 — Save the Date! back to the top
GTC 2011 will take place October 11-14 in San Jose, California — bringing together scientists, researchers, engineers and developers for a week of innovation, learning and networking. Los Alamos National Laboratory’s Accelerated High Performance Computing (HPC) Symposium will be co-located with GTC 2011.
- For more info, see:

New Book: GPU Computing Gems
The first volume in a new series of books on parallel computing is now available. Edited by Professor Wen-mei Hwu of the University of Illinois and developed by Morgan Kaufmann in collaboration with NVIDIA, GPU Computing Gems offers practical techniques and real-world examples.
- For more info, see:
  (Use code CUDA1 for 20% off through February 2011)

CUDA at the Academy Awards
All five movies nominated for an Oscar in the Visual Effects category were created by studios using NVIDIA Quadro professional graphics solutions. The nominees are Inception (studio: DNeg), Iron Man 2 (studios: DNeg and ILM), Harry Potter and the Deathly Hallows: Part 1 (studio: DNeg), Hereafter (studio: Scanline VFX) and Alice in Wonderland (studio: Sony Pictures Imageworks/SPI). The winner will be announced at the 83rd annual Academy Award ceremony on February 27, 2011.
- See the list:

Meet the Thalesians
The Thalesians are a think tank of professionals with an interest in finance, mathematics, computer science and synergetics. The group is named after Greek philosopher Thales of Miletus, a mathematician who is known as an early user of financial options. Originally based in London, the Thalesians are now expanding to New York. CUDA developers and enthusiasts are invited to attend the inaugural talk in New York by Dr. Gerald Hanweck, Jr., CEO of Hanweck Associates, on Wed., February 23. The topic is "Monte Carlo Methods in CUDA."
- Learn more about the Thalesians:
- Join group and register for event:
Replays of the Week
NEW: Each week we highlight sessions from GTC 2010 and SC10. Here are our picks for this week, both by Jon Cohen, a member of the NVIDIA Research team: back to the top
      Solving PDEs on Regular Grids with OpenCurrent (GTC 2010)
      Jon Cohen - NVIDIA (pdf)

      GPU Computing for Computational Science (SC10)
      Jon Cohen - NVIDIA (pdf)
NVIDIA is seeking product managers, technical marketing managers, product marketers and CUDA developers for the Tesla GPU computing business, which develops high-performance computing solutions to help scientists and engineers solve problems they could not solve before. The massively-parallel CUDA architecture has seen one of the fastest processor architecture adoptions in computing history. Coupling the power of CUDA with Project Denver, the upcoming CPU product line, NVIDIA is fundamentally transforming the computer. Location: Santa Clara, California.
- See: (search on "CUDA")
back to the top
CUDA Calendar
February – March 2011 back to the top
Performance Benefits of NVIDIA GPUs for ANSYS Mechanical –

February 17, 2011, noon-1:00 pm pacific, Sunnyvale, California
Hosted at Ozen Engineering, 1210 E. Arques Ave #207
Note: Pizza will be served

Monte Carlo Methods in CUDA - The Thalesians
February 23, 6:30 pm, New York, New York
Playwright Tavern, Theatre District
Presentation by Dr. Gerald Hanweck, Jr., CEO of Hanweck Associates

HPC & GPU Supercomputing Group of New York Meetup
March 2, 2011, 6:00 pm, New York, New York
Hosted at Microsoft, 1290 Avenue of the Americas

HPC & GPU Supercomputing Group of Boston Meetup
March 3, 2011, 6:00 pm, Cambridge, Massachusetts
Hosted at Microsoft NERD Center, 1 Memorial Drive

Workshop on General Purpose Processing on GPUs (with ASPLOS XVI)
March 5, 2011, Newport Beach, California

GPU Computing Using Mathematica and CUDA - Webinar
March 11, 2011, noon central time
March 14, 2011, 5:00 pm central time
March 16, 2011, 9:00 am central time

GPU Computing Session, German Physical Society Conference
March 13-18, 2011, Dresden, Germany

ASIM Workshop 2011 - ASIM and Technische Universitat Munchen (TUM)
March 14-16, 2011, Leibniz, Germany
Theme: Trends in Computational Science & Engineering: Foundations of Modeling & Simulation

SagivTech 3-Day CUDA Course
March 27-29, Ramat Gan, Israel
April – July 2011

SagivTech 3-Day CUDA Course
April 3-5, Haifa, Israel

Workshop on High Performance Computational Biology - IEEE
May 16, 2011, Anchorage, Alaska
Note: Held with International Parallel & Distributed Processing Symposium

25th International Conference on Supercomputing
June 1-4, 2011, Tucson, Arizona

Intelligent Vehicles Conference - IEEE
June 5-9, 2011, Baden-Baden, Germany

Internat'l. Supercomputing Conference (ISC)
June 19-23, 2011, Hamburg, Germany

Internat'l. Conference on Computer Systems and Applications
June 27-30, 2011, Sharm El-Sheikh, Egypt

Genetic and Evolutionary Computation Conference (GECCO)
July 12-16, 2011 Dublin, Ireland

World Congress in C.S., Computer Engineering, Applied Computing

(Call for papers: March 10, 2011)
July 18-21, 2011, Las Vegas, Nevada

Application Accelerators in High Performance Computing (SAAHPC 2011)
Call for papers: May 6, 2011
Event: July 19-21, 2011, Univ. of Tennessee, Knoxville, Tennessee

– CUDA Training from EMPhotonics:
– CUDA Training from Acceleware:
– CUDA Certification:
– GPU Computing Webinars:

(To list an event, email:

CUDA Resources
CUDA Registered Developer Program back to the top
– Sign up:
CUDA GPU Computing Forum
– Link to forum:
– List of CUDA-enabled GPUs:
CUDA Libraries Performance Report
– Download:
CUDA Downloads
– Download CUDA Toolkit 3.2:
– Download OpenCL v1.1 pre-release drivers and SDK code samples (Log in or
   apply for an account
– Download Parallel Nsight:
– Get developer guides and docs:
CUDA on the Web
– See previous issues of CUDA: Week in Review:
– Follow CUDA & GPU Computing on Twitter:
– Network with other developers:
– Stayed tuned to GPGPU news and events:
– Learn more about CUDA on CUDA Zone:
– Check out the NVIDIA Research page:
CUDA Recommended Reading
– Kudos for CUDA:
– Supercomputing for the Masses, Part 20:
– CUDA books:
CUDA Recommended Viewing
– Third Pillar of Science:
– GTC 2010 presentations:
– SC10 presentations:
About CUDA
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:

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