CUDA: Week in Review
Tues., Jan. 25, 2011, Issue #46 - Newsletter Home
Welcome to CUDA: Week in Review, an online news summary for the worldwide CUDA, GPU computing and parallel programming ecosystem.
Simulating Waves in Denmark
This week’s CUDA Spotlight is on Allan P. Engsig-Karup, assistant professor in scientific computing at the Technical University of Denmark (DTU). Allan’s research includes the OceanWave3D model, which he presented at GTC 2010 in San Jose, California. Here are highlights of our interview with him:
NVIDIA: Allan, tell us about your work at DTU.
Allan: I am responsible for teaching and research related to scientific computing. I teach on the order of 200 BSc, MSc and PhD students every year.

My collaborative research is focused on GPUs for applications requiring efficient PDE (partial differential equation) solvers and optimization algorithms, as well as development of performance profiling tools.

A project I am currently involved in, with my colleague Associate Professor Harry Bingham, is the continued development of a tool referred to as OceanWave3D - for simulation of nonlinear and dispersive free surface flow in marine settings.
NVIDIA: How can this research be used in the real world?
Allan: Coastal and ocean engineers need to estimate the flow kinematics and design loads on human-made structures in the ocean, such as ships, oil platforms, offshore windmills and energy devices. [Ed. note: Windmills produce approx. 20% of Denmark's energy requirements].
NVIDIA: What kind of results have you achieved with CUDA?
Allan: Recently, working with one of my MSc students, we achieved impressive scalability results for the parallel GPU implementation of OceanWave3D. These results were achieved by careful redesign of algorithms and implementation on the hardware (using CUDA C), leading to a conservative estimate of at least a 42X speedup compared to an optimized sequential code.

  - Read the full interview with Allan:

  (Would you like to be featured in the CUDA Spotlight? Email us at
CUDA Libraries Performance Report Now Available
This new report covers all the performance improvements in the latest CUDA Toolkit 3.2 release, and compares CUDA parallel math library performance vs. commonly used CPU libraries. Learn about the performance advantages of using the CUDA parallel math libraries for FFT, BLAS, sparse matrix operations and random number generation.
- See:

ANSYS Acceleration on Tesla GPUs
ANSYS' engineering simulation software predicts how product designs will behave and how manufacturing processes will operate in real-world environments. ANSYS is working closely with NVIDIA to develop GPU-accelerated solvers and algorithms.
- To learn more, see:

Note: A seminar on "Performance Benefits of NVIDIA GPUs for ANSYS Mechanical" will be held Thursday, February 17, at noon pacific time:
NEW: Each week we highlight a session from GTC 2010 and SC10. Here are our picks for this week:

    GPU-Accelerated Internet Technologies & Trends (GTC 2010)
    Chris Pedersen - NVIDIA (video - 45 mins.)

    First Look at the World's Fastest Supercomputer (SC10)
    Andy Keane - NVIDIA (pdf)
Microsoft is seeking a Software Development Engineer to help drive the parallel revolution in personal and technical computing. Requirements: 6+ years of software development in C++/C# with experience in commercial product release cycles. Experience with DirectX, data parallelism, CUDA and/or OpenCL is a plus. Location: Redmond, WA; Division: Server & Tools Business.
- See:

Note: In future issues of CUDA: Week in Review, we will highlight people who are seeking careers, internships, academic positions and contract work related to CUDA and parallel programming. To be included, email:
January 2011

Optimizing Financial Modeling/Chicago - Wolfram Research
Jan. 25, 2011, Chicago (Featured Speaker: Dr. Michael Kelly)

Optimizing Financial Modeling/New York - Wolfram Research
Jan. 27, 2011, New York (Featured Speaker: Dr. Michael Kelly)

February - July 2011

Symposium on Principles and Practice of Parallel Programming - ACM
February 12-16, 2011, San Antonio, TX

NEW: Performance Benefits of NVIDIA GPUs for ANSYS Mechanical –

February 17, 2011, noon-1:00 pm pacific
Hosted at Ozen Engineering, 1210 E. Arques Ave #207, Sunnyvale, CA 94085
Note: Pizza will be served

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

Computational Intelligence on Consumer Games and Graphics Hardware (CIGPU)
July 12-16, 2011, Dublin, Ireland (GECCO Workshop)

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

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

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

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

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

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

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

(To list an event, email:

GPU Technology Conference
– Presentations from GTC 2010:
SC10 Conference
– Presentations from SC10:
– List of CUDA-enabled GPUs:
Video Recommendation
– The Third Pillar of Science:
CUDA GPU Computing Forum
– Link to forum:
CUDA and Parallel Nsight Overview
– Blog post and video:
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
– Get developer guides and docs:
CUDA and Academia
– Learn more at
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:
CUDA Recommended Reading
– Read Kudos for CUDA:
– Read Supercomputing for the Masses, Part 20:
– Read CUDA books:
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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