CUDA: Week in Review
Mon., April 4, 2011, Issue #51 - Newsletter Home
Welcome to CUDA: Week in Review, an online news summary for the worldwide CUDA, GPU computing and parallel programming ecosystem.
GPU–Accelerated Large Scale Analytics
Congrats to Ross Walker!
CUDA and Financial Modeling
Jacket for MATLAB v1.7
PGI 2011 v11.3
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CUDA Spotlight
GPU-Accelerated Large-Scale Analytics
This week’s spotlight is on Dr. Ren Wu, Senior Research Scientist at HP Labs in Palo Alto, Calif., and Principal Investigator of the CUDA Research Center at HP Labs. Dr. Wu works in the area of large-scale analytics and business intelligence. Here is an extract from our interview:
NVIDIA: Ren, tell us about potential applications of GPU-accelerated large-scale data analytics.
Ren: There are many different and exciting scenarios, including trend analysis of social media, large-scale predictive models, automatic data correlation, and statistical analysis in sensor data streams. And the GPU is not limited to accelerating large-scale analytics only; it can be used for accelerating analytics on any scale. I expect to see many more GPU-accelerated cloud services in the near future.
NVIDIA: What kind of advantages have you achieved with CUDA?
Ren: We’ve looked at various core primitives in analytics. Per chip comparison, typically we’ve achieved about a 5-20X performance advantage by using CUDA GPUs over a pure CPU approach. For a typical workstation with two CPUs and two Tesla boards, this ratio is also pretty much maintained. Same goes for the servers, even though it can vary more, depending on the server’s configuration.

Personally, I think that the CUDA programming model is a very nice framework--well balanced on abstraction and expressing power, enough control for algorithm designers, and supported by hardware with exceptional performance (compared to other alternatives).

  - Read the complete interview here

  (Would you like to be featured in the CUDA Spotlight? Email us at
CUDA Developer News
Congrats to Ross Walker! back to the top
Dr. Ross Walker of the San Diego Supercomputing Center was awarded the HP Outstanding Junior Faculty Award in Computational Chemistry for his work in accelerating the popular molecular dynamics code AMBER on GPUs. Ross is an NVIDIA CUDA Fellow.
- See:
Ross Walker
CUDA and Financial Modeling
Wolfram Research and NVIDIA hosted an "Optimizing Financial Modeling" seminar. In this YouTube video, NVIDIA’s John Ashley explains how parallel programming with CUDA is changing financial computation (25 mins).
- See:

Jacket for MATLAB v1.7
A new version of Accelereyes’ Jacket is available. Jacket accelerates MATLAB code.
- See:

PGI 2011 v11.3
New features in PGI 2011 include PGI Accelerator and CUDA Fortran support for 64-bit MacOS.
- See:

GTC 2011 – Call for Submissions is Open
Submit your proposals by May 3.
- See:

CUDA 4.0
The CUDA Toolkit 4.0 RC is available to CUDA Registered Developers.
- Register:
- More info:
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
      Languages, Tools and APIs for GPU Computing (GTC10)
      Will Ramey - NVIDIA

      Using GPUs to Run Next-Gen Weather Models (SC10)
      Mark Govett - NOAA
The School of Computer Science at the University of Birmingham will award a Microsoft PhD Scholarship on the topic "Structural Foundations for Heterogeneous Computation." Applicants must have honors degree or equivalent in C.S., Mathematics or Computer Engineering. Position is open for UK and EU applicants, but strong candidates from outside the EU may be considered. The Scholar will work under the supervision of Dr. Dan R. Ghica from University of Birmingham. On behalf of Microsoft Research, the Scholar will be also supervised by Prof. Satnam Singh.
- Dan R. Ghica’s page:
- Satnam Singh’s page:

back to the top
-CUDA 4.0 Overview - Webinar
          Tuesday, April 5, 10:00 am pacific
          Presented by Will Ramey, NVIDIA

-NEW: Live Q&A on CUDA-gdb and memcheck - Webinar
          Wednesday, April 13, 2011, 10:00 - 11:00 a.m. pacific
          Presented by senior engineering team, NVIDIA

-NEW: Bright Cluster Manager/Advanced Clusters Made
          Easy - Webinar

          Thursday, April 21, 2011, 9:00-10:00 am pacific

back to the top
CUDA Calendar
April 2011 back to the top
SagivTech 3-Day CUDA Course
April 3-5, 2011 Haifa, Israel

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

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

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

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

NEW: Fluid-Structure Interaction 2011: Workshop on the Advances in
         Computational Methods

April 27-29, 2011, Singapore
Note: Session by Srinivas Kodiyalam, NVIDIA, on April 29
May 2011

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

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

-Parallel CFD Conference (ParCFD 2011)
May 16-20, 2011, Barcelona, Spain
Note: Tutorial by Tom Reed, NVIDIA, on May 16

-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, Chicago, Ill.

-NAFEMS World Congress: Promoting Adoption of HPC for Engineering Simulation
May 23-26, 2011, Boston, Mass.
Note: Session by Stan Posey, NVIDIA, on May 25

-NEW: LS-DYNA 8th European Users Conference
May 23-24, 2011, Strasbourg, France
Note: Paper and talk by Stan Posey and Srinivas Kodiyalam, NVIDIA
June 2011

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

-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

-NEW: Advanced Numerical Methods on GPUs
Mini-symposium at ENUMATH 2011
Sept. 5-9, Univ. of Leicester, Leicester, UK

-NEW: 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

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

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

-SEG (Society of Exploration Geophysicists) Annual Meeting
Sept 18-23, 2011, San Antonio, Tex.
(Deadline for abstracts: April 6, 2011)

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

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

(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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