CUDA: Week in Review
Tues., Mar. 22, 2011, Issue #50 - Newsletter Home
Welcome to CUDA: Week in Review, an online news summary for the worldwide CUDA, GPU computing and parallel programming ecosystem.
GPU–Accelerated Simulators
CUDA 4.0 for Registered Developers
GTC 2011 — Call for Submissions
Considering CUDA–x86?
GPU Computing Test Drive
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CUDA Spotlight
GPU-Accelerated Electromagnetic and Micromagnetic Simulators
Prof. Vitaliy Lomakin (center) with his team at UCSD
This week’s spotlight is on Vitaliy Lomakin, an Associate Professor at the University of California, San Diego (UCSD). Prof. Lomakin works in the field of Computational Electromagnetics and Micromagnetics. This technology is fundamental in the design of components in products like solar cells, antennas and hard drives. In addition, it is utilized in R&D related to human health, from MRI systems to cancer treatments.
NVIDIA: Vitaliy, please tell us about what you and your team are working on.
Vitaliy: My research group develops high-performance electromagnetic simulators, which solve Maxwell’s equations, and micromagnetic simulators, which solve the Landau-Lifshitz-Gilbert equation. These simulators have a significant predictive power - allowing the analysis, design and validation of systems before and during fabrication and testing.
NVIDIA: When did you start using GPUs? How does GPU computing impact your work?
Vitaliy:I first read about GPUs around three years ago and we decided to give it a try. A Ph.D. student in my group, Shaojing Li, took on the project and did superb work. Now the majority of our codes use GPUs.

Our simulators are implemented on GPU-based systems using the CUDA parallel programming model. As a result, they are very efficient in terms of speedups (70-400X, as compared to CPUs) and absolute performance. For example, we developed a micromagnetic solver, referred to as FastMag. On a simple desktop, FastMag can rapidly solve complex problems discretized over hundreds of millions tetrahedral elements. This is enabled by GPU computing.

The advantages of working with CUDA include the ability to handle very large problem sizes; very fast performance; easily obtainable computers; no need for specialized facilities for computers; and low power consumption. It offers a truly high-performance cluster at a cost of a desktop.
  - See the complete interview here

  (Would you like to be featured in the CUDA Spotlight? Email us at
CUDA Developer News
CUDA 4.0 Available to Registered Developers back to the top
The newly-announced CUDA Toolkit 4.0 Release Candidate includes Unified Virtual Addressing, GPU-to-GPU communication and enhanced C++ template libraries. It is available to all CUDA Registered Developers.
- Register:
- More info:

GTC 2011 – Call for Submissions is Open
GTC 2011 will bring together the best and brightest minds in GPU computing for four days of immersion in world-class scientific research and applications. If you would like to present your work, please submit a proposal by May 3:

Considering CUDA-x86?
Take this survey from The Portland Group:

Want to Test Drive GPU Computing?
Check out test drives from Accelereyes:

New Meetup in Seattle
A new HPC & GPU Supercomputing Meetup has been formed in Seattle, Washington:
Replays of the Week
NEW: Each week we highlight sessions from GTC 2010 and SC10. Here are our picks for this week: back to the top
      Faster Simulations of the National Airspace System (GTC10)
      Joseph Rios - NASA

      PGI CUDA C for Multi-core x86 Processors (SC10)
      Michael Wolfe - The Portland Group
Raytrix of Kiel, Germany, develops "computational photography" cameras which use CUDA-accelerated 3D algorithms. The company is seeking CUDA specialists for software optimization and development.
- See:
- Email: Lennart.Wietzke (at)
back to the top
CUDA Calendar
March 2011 back to the top
NEW: CUDA 4.0 Overview - Webinar
March 22, 2011, 7:00 am pacific
March 23, 2011, 9:00 pm pacific
Note: Will Ramey of NVIDIA to present

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

NEW: Meetup: HPC & GPU Supercomputing Group of New York
March 28, 2011, 6:00 pm
Microsoft, 1290 Avenue of the Americas, New York, New York

NEW: HPC & GPU Acceleration in Finance, 3-Day Course - Microsoft
March 28-30, 2011, New York, New York
Note: Hands-on training, cutting-edge information

GPU Computation Using Mathematica and CUDA - Wolfram Research
March 30, 2011, 11:00 am central

NEW: Georgia Tech GPU Coding Challenge
March 31, 2011 (deadline)
Note: Open to Georgia Tech students and professors. Sponsored by Accelereyes.
April 2011

SagivTech 3-Day CUDA Course
April 3-5, 2011 Haifa, Israel

NEW: Meetup: HPC & GPU Supercomputing Group of Silicon Valley
April 4, 2011, 6:00 pm
Carnegie Mellon Silicon Valley, NASA Research Park, Mountain View, Calif.

NEW: CUDA 4.0 Overview - Webinar
April 5, 10:00 am pacific
Note: Will Ramey of NVIDIA to present

NEW: Meetup: HPC & GPU Supercomputing Group of Boston
April 7, 2011, 6:00 pm, Microsoft NERD Center, Cambridge, Mass.

NEW: Many-Core and Reconfigurable Supercomputing Conference (MRSC 2011)
April 11-13, 2011, Bristol, U.K.
Note: CUDA workshop on April 11

NEW: Simulation Developer’s Working Group Meeting
Apr. 12-13, 2011, Las Vegas, Nevada
Note: Doug Traill of NVIDIA to present
May 2011

GPU Computing Overview - Microsoft, NVIDIA
May 3, 2011, 9:00 am-5:00 pm (includes meals), Boston, Mass.

GPU Computing Overview - Microsoft, NVIDIA
May 4, 2011, 9:00 am-5:00 pm (includes meals), New York, New York

Parallel CFD Conference (ParCFD 2011)
May 16-20, 2011, Barcelona
Note: CUDA and GPUs for CFD Applications tutorial by NVIDIA

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

GPU Computing Overview - Microsoft, NVIDIA
May 19, 2011, 9:00 am-5:00 pm (includes meals), San Francisco, Calif.

GPU Computing Overview - Microsoft, NVIDIA
May 20, 2011, 9:00 am-5:00 pm (includes meals), Chicago, Ill.

NAFEMS World Congress: Promoting Adoption of HPC for Engineering Simulation
May 23-26, 2011, Boston, Mass.
Note: May 25 session by Stan Posey, NVIDIA, on GPU Acceleration for Multiphysics Applications
June 2011

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

Intelligent Vehicles Conference - IEEE
June 5-9, 2011, Baden-Baden, Germany
Note: Session by Jeff Ota, NVIDIA, on Parallel Computing in Intelligent Vehicles

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
July – Dec. 2011

2011 World Congress on Engineering (WCE 2011)
July 6-8, 2011, London, England

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

World Congress in C.S., Computer Engineering, Applied Computing (WORLDCOMP’11)
July 18-21, 2011, Las Vegas, Nevada

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

Geospatial Summit
Sept. 13-14, 2011, Herndon, Virginia

NEW: SPIE Conference on High-Performance Computing in Remote Sensing
Sept. 19-22, 2011, Prague, Czech Republic

NEW: GPU Technology Conference (GTC 11)
Oct. 11-14, 2011, San Jose, Calif.

Nov. 12-18, 2011, Seattle, Wash.

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

(To list an event, email:

CUDA Resources
CUDA Registered Developer Program back to the top
– Sign up: (allows access to CUDA Toolkit 4.0 RC)
– List of CUDA-enabled GPUs:
CUDA Libraries Performance Report
– Download:
CUDA Downloads
– Download CUDA:
– 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 21:
– 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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