CUDA: Week in Review
Friday, February 5, 2010, Issue #7 - Newsletter Home  
Welcome to this week’s issue of "CUDA: Week in Review." Questions or suggestions? Email us at
Call for Participation: “GPU Computing Gems”
NVIDIA and Professor Wen-mei Hwu of the University of Illinois, Urbana-Champaign are accepting article submissions for "GPU Computing Gems," a contribution-based book that will focus on practical techniques for GPU computing. This is a continuation of the popular "GPU Gems" series. More info:
National Science Foundation Grant for GPU Computing
Northeastern University and Mass General Hospital were awarded a $1.3 million grant from the National Science Foundation to develop a software platform based on GPUs for biomedical imaging applications. The new software libraries will enable radiologists to more quickly assess tissue images, which will allow clinicians to perform image-guided biopsies earlier than can be done now… Professor Dave Kaeli, who leads Northeastern’s parallel software development team, comments: "The implications for a patient’s mental health as well as cost of care for patients are huge." Kaeli’s team is developing the software on GPU-based systems, with CUDA and OpenCL. See:

Siemens Healthcare Uses CUDA for 3D Ultrasounds of Babies in Utero
In the latest issue of VentureBeat, tech writer Dean Takahashi discusses a cool new application from Siemens Healthcare which was demoed this week at "CUDA Day" in San Francisco: "Siemens is using CUDA technology to create 3D ultrasounds of babies in utero and other medical applications… Physicians can see how a baby is doing in much better visual detail than a 2D ultrasound can deliver." See Dean’s video interview with Roee Lazebnik, director of product development for radiology and ob/gyn, Siemens Healthcare:
New on CUDA Zone: Massively-Parallel Simulation of Biochemical Systems
In this paper, a computational approach for massively parallel simulation of biological molecular networks was developed leveraging the computing power of modern graphics cards. The implementation on a GeForce GTX 280 was over 59 times faster than on a Xeon 2.66Ghz processor. Citation: J. Ackermann, P. Baecher, T. Franzel, M. Goesele, K. Hamacher; Technische Universitat Darmstadt. See it here:
Submit Your Work
Have a CUDA-related paper or research? Show it on CUDA Zone. Submission form:
CUDA Education
Workshop at Stanford
Molecular Dynamics Workshop Series, 3/01/10-3/02/10, at Stanford University. Intended for people interested in running MD simulations on GPUs and/or developing new MD algorithms that can be implemented and accelerated on GPUs. Registration is required and spaces are limited. For more info:
Call for Papers
Many-Core/Reconfigurable Supercomputing Conference, Rome. Papers due: 2/12/10. See:

Dependable Multi-Core Computing Workshop, Caen, France. Papers due 2/15/10. See:
CUDA and GPU Computing Courses
Over 300 universities are teaching CUDA and GPU Computing courses. See the list:
Parallel Processing Textbook
"Programming Massively Parallel Processors: A Hands-on Approach" is co-written by Dr. David B. Kirk, NVIDIA Fellow, and Professor Wen-mei Hwu of the University of Illinois, Urbana-Champaign. The book utilizes CUDA C as well as OpenCL.  For more info, go to Elsevier or Amazon.
Upcoming  Webinars
GPU Computing using CUDA C - An Introduction
2/08/10, 9 pm pacific:

GPU Computing using CUDA C - Advanced 1
2/15/10, 9 pm pacific:

GPU Computing using CUDA C - Advanced 2
2/22/10, 9 pm pacific:

GPU Computing and OpenCL - An Introduction
3/19/10, 10 am pacific:

GPU Computing and OpenCL - Advanced 1
3/26/10, 10 am pacific:
GPU Development Environment Update
NVIDIA’s new GPU development environment, codenamed Nexus, has been officially christened "NVIDIA Parallel Nsight."  Register at for access to the Beta program.
CUDA Toolkit
Download the CUDA Toolkit 3.0 Beta here:
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– Stayed tuned to GPGPU news and events:
– Learn more about CUDA on CUDA Zone:
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