CUDA: Week in Review
Friday, March 19, 2010, Issue #13 - Newsletter Home  
Welcome to this week’s issue of "CUDA: Week in Review," a weekly newsletter for the worldwide CUDA and GPU Computing community. Contact us at:
New CUDA Toolkit 3.0 – Ready for Fermi
Today NVIDIA released version 3.0 of the CUDA Toolkit, providing developers with tools to prepare for the upcoming Fermi-based GPUs. CUDA Toolkit v3.0 supports a full range of languages and APIs including CUDA C, CUDA C++, OpenCL, DirectCompute, and PGI CUDA Fortran.
- Read more:
- Download CUDA Toolkit 3.0:
CUDA and Machine Vision
Canada-based Dalsa is a leader in machine vision systems. It supplies components for inspection of flat panel displays, electronic circuit assemblies, semiconductor wafers, document scanning, medical applications, and general machine vision. Dalsa’s products are in effect the "eyes" that provide quality assurance and feedback for a significant share of the world’s automated manufacturing operations. Porting products to run on CUDA enables Dalsa’s customers to utilize NVIDIA GPUs to process more image streams with higher resolution, higher bit depth, and higher frame rates. This improves quality and yield while reducing costs. For more info, see: (click on "Nitrous" tab) (click on "Nitrous" pie slice)
New on CUDA Zone: PARRET
Submission extract: "PARRET (PARallel REstore Tools) is a Python programming language package for image deblurring on GPUs. By making use of the parallelism on the CUDA architecture, the deblurring time is greatly reduced. Besides image deblurring, PARRET can be used to solve linear equations…. Our previous Python package is PYRET (PYthon REstoreTools). PYRET (pronounced ’pirate’) and PARRET (pronounced ’parrot’) can work separately, but together they make a good team." Author: Ying Wei (Daniel) Fan, Emory University. See:
Submit Your Work
Have a CUDA-related paper or research? Show it on CUDA Zone:
Global Investment Bank in New York City seeks a developer for high performance computational software on GPUs. Required skills include experience in CUDA programming and porting complex data and task parallel applications to GPGPUs.
- See posting here:
- See more CUDA/GPU computing jobs here:
CUDA Education
New CUDA Course in Russia
Mr. Sergey Chadov is teaching a CUDA course at Ivanovo State Power University in Russia. The material is based on a course also taught at Moscow State University on the architecture and programming of CUDA-based massively-parallel computing systems. Students will learn about the latest multi-core architectures, programming models, and fundamental principles underlying the construction of efficient parallel algorithms. For more info, email:
PGI CUDA Fortran Webinar
PGI Fortran, a popular commercial-grade Fortran compiler, is now available with GPU acceleration. To learn more, sign up for an interactive webinar with technical experts from the Portland Group on Wed., March 24, 9:00-10:00 a.m. (Pacific):
Acceleware-Certified CUDA Training
Silicon Valley‚ March 24-25:
Calgary‚ April 12-16:
New Symposium at Univ. of Pittsburgh
Symposium on Applications of GPUs in Chemistry and Materials Science, June 28-30, University of Pittsburgh. See:
Call for Papers
Symposium on Chemical Computations on GPGPUs, Aug. 22-26, Boston. Abstracts due April 5. Best paper wins an NVIDIA Tesla C2050! See:
GPU Computing Gems Update
Close to 300 submissions were received for the forthcoming GPU Computing Gems book, covering topics such as medical imaging, financial modeling, engineering and scientific simulation, video, image and signal processing, computer vision, interactive physics simulation and more. Projected publication date is Q4 2010.
GPU Computing Webinars (CUDA C and OpenCL)
March schedule:
CUDA and GPU Computing Courses
Over 310 universities are teaching CUDA and GPU Computing courses. See the list:
– CUDA Videos on YouTube:
– CUDA Toolkit:
– Developer Guides:
– Programming Massively Parallel Processors, by D. Kirk, W. Hwu:
– Follow CUDA & GPU Computing on Twitter:
– Network with other developers:
– Stayed tuned to GPGPU news and events:
– Learn more about CUDA on CUDA Zone:
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

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