CUDA: Week in Review
Thurs., July 21, 2011, Issue #58
Welcome to CUDA: Week in Review, an online news summary for the worldwide CUDA, GPU computing and parallel programming ecosystem.
Jesse Rosenzweig, Elemental Technologies
Stanford: New CUDA Center of Excellence
PGI CUDA-x86 Shipping
FastROCS for Drug Discovery
Encryption with CUDA
Sign up to be a CUDA Registered Developer
Follow @GPUComputing on Twitter
CUDA Spotlight
GPU-Accelerated Video Processing
This week’s Spotlight is on Jesse Rosenzweig, CTO and co-founder of Elemental Technologies. Jesse spearheads Elemental’s application development, quality assurance and R&D groups. Here’s an extract from our interview:
NVIDIA: Jesse, what is your role at Elemental?
Jesse: I act as the glue between customers, partners, and our engineering, marketing and QA teams. In addition, I lead an R&D team that constantly builds prototypes and scopes out future technologies to integrate into our products. During Elemental’s early days, I wrote video codec CUDA code (although I imagine there aren’t many of my lines left now, given the strength of our CUDA team!).
NVIDIA: How do your products leverage GPU computing?
Jesse: Every pixel of every frame of a video source into our system is decompressed, processed and even recompressed using the GPU and our proprietary video processing pipeline. This allows us to not only get extremely fast high-quality video processing, but also to offload the CPUs to accommodate audio processing, security, content wrapping, database management and content serving while providing a responsive user interface, even during a heavy system load.
NVIDIA: As CTO, why did you choose to work with GPUs?
Jesse: As consumers look to view video on every device imaginable, the demand for video formatting is skyrocketing and scalability is critical. As needed, we can integrate advanced GPUs with more processors and everything will run quicker or process in new, more resource-efficient ways.
NVIDIA: Tell us about Elemental Live.
Jesse: Elemental Live is our solution for processing live video. It allows media companies, such as such as Comcast, Time Warner Cable, Avail-TVN, ABC News, CBS and others, to deliver real-time content (live events, sports, satellite feeds, etc.) to TVs, PCs, tablets and mobile devices using the latest adaptive streaming technologies from Adobe, Apple and Microsoft.
  - Read the complete interview here

  (Would you like to be in the CUDA Spotlight? Email
CUDA Developer News
Stanford Named CUDA Center of Excellence back to the top
Stanford is now a CUDA Center of Excellence. The Institute for Computational & Mathematical Engineering (ICME) at the School of Engineering will spearhead the program in partnership with other departments, including the Dept. of Computer Science (CS), the Center for Computational Earth and Environmental Sciences (CEES) and the Dept. of Mechanical Engineering, Flow Physics Division.
- See:
PGI CUDA-x86 Shipping
PGI is shipping its CUDA C/C++ compiler for x86. PGI CUDA-x86 processes CUDA C and CUDA C++ as a native parallel programming language to run on multi-core x86. With this release, developers can compile and execute a variety of CUDA C and CUDA C++ codes to run on x86 today. A 15-day free trial is available.
- See:

FastROCS for Drug Discovery
FastROCS is now publicly available from OpenEye Scientific Software. FastROCS is an extremely fast 3D molecular shape comparison program running on Tesla GPUs. It was developed in collaboration with industry partners including Abbott Labs and Pfizer.
- See:

Encryption with CUDA
Xoom Data Services announced its CudaCrypt encryption software, which uses the GPU to process large files like video and engineering plans with "military-grade" security. CEO Robert Gagnon says: "We move data from point A to point B and we make sure people can’t steal it in the middle."
- See:

SC Online reported that simulations of Earth and space phenomena at NASA’s Goddard Space Flight Center are getting a boost from GPUs. Early results demonstrate potential for significant speedups with systems ranging from one to four GPUs in labs, up to a 64-GPU IBM iDataPlex cluster.
- See:

GPUs in the Geosciences
A session on "High-Resolution Modeling in the Geosciences Using GPU and Many-Core Architectures" will be held at the AGU (American Geophysical Union) meeting in December. Session leaders are Matthew Knepley, Univ. of Chicago; David Yuen, Univ. of Minnesota; and Adam Schultz, Oregon State Univ. Session abstracts are due August 4.
- See:

GPUs in Military & Embedded Apps
CUDA: Week in Review readers are cordially invited to attend a special webinar on July 26. The presentation will discuss CPU-GPU hardware deployments in military and embedded applications. The moderator is Jeff Child, Editor-In-Chief of COTS Journal. He will be joined by Michael Bowling, President of Trenton Systems and Devang Sachdev of NVIDIA.
- Register:
- See complete webinar schedule:
New on the NVIDIA Blog
Drexel Takes Off to Big Science Frontiers with GPUs, by Devang Sachdev
Cornell Collaboration Explores GPU Computing + MATLAB, by David Lifka, Cornell
Joining Forces with Beijing Genomics Institute, by Kimberly Powell
CUDA Engineer Takes Busman’s Holiday in Turkey, by Ian Buck
Fight Global Warming with GPU Computing and C++, by Olivier Giroux
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Replays of the Week
NEW: Each week we highlight sessions from GTC 2010 and ISC 2011. Here are our picks for this week: back to the top
      Using CUDA to Accelerate Radar Image Processing (GTC 10)
      Aaron Rogan - Neva Ridge Technologies

      CUDA Fortran and CUDA Libraries (ISC 2011)
      Massimiliano Fatica - NVIDIA
NEW: Pacific Biosciences in Menlo Park, Calif., is seeking a High-Performance Computing Engineer to be responsible for technical strategy development of an HPC environment embedded in a DNA sequencing machine. HPC background and CUDA experience required.
- See:
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If you are travelling to any of these locations, feel free to drop in. Visitors are welcome.
New York Meetup – July 25, 6:00 pm
New Mexico Meetup – July 26, 7:00 pm
Boston Meetup – Aug. 4, 6:00 pm
Silicon Valley Meetup – Aug. 15, 6:15 pm
Wash. DC Meetup – Aug. 18, 4:30 pm (inaugural meeting)
Austin Meetup – Aug. 19, 6:00 pm
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CUDA Calendar
July 2011 back to the top
- GTC Workshop Japan
July 22, 2011, Tokyo
Hosted by NVIDIA, with the Tokyo Institute of Technology

- Banking with GPGPUs: Increased Performance, Lowered Costs (Training Workshop)
July 25-27, 2011, London, UK
Note: Taught by experts from Excelian and Cranfield University
Contact: james.heath (at)
August 2011

- Banking with GPGPUs: Increased Performance, Lowered Costs (Training Workshop)
Aug. 8-11, 2011, London, UK
Note: Taught by experts from Excelian and Cranfield University
Contact: james.heath (at)

- LAMMPS Users’ Workshop
Aug. 9-11, 2011, Albuquerque, New Mexico
Learn more about LAMMPS:

- NEW: Par Lab Boot Camp (Short Course on Parallel Computing)
Aug. 15-17, 2011, UC Berkeley, Berkeley, California

- NEW: Proven Algorithmic Techniques for Manycore Processors (Hands-On Course)
Aug. 15-19, 2011 (at multiple locations via videoconferencing)
Note: Sponsored by the Virtual School of Computational Science and Engineering (VSCSE)

September 2011

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

- 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

- NEW: Rapid Problem Solving Using Thrust (Webinar)
Sept. 14, 2011
Presented by Nathan Bell, NVIDIA
Note: Thrust is a library that enables programmers to develop high-performance applications on CUDA with minimal effort.

- 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.

(To list an event, email:

CUDA Resources
Downloads back to the top
– CUDA 4.0:
– Parallel Nsight:
– Parallel Nsight:
CUDA Registered Developer Program
– Sign up:
– List of CUDA-enabled GPUs:
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
– Future of Computing Performance:
– Supercomputing for the Masses, Part 21:
– CUDA books:
CUDA Recommended Viewing
– The 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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