Friday, March 19, 2010, Issue #13 - Newsletter Home   WELCOME 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: cuda_week_in_review@nvidia.com. CUDA NEWS 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: http://is.gd/aO6tf - Download CUDA Toolkit 3.0: www.nvidia.com/getcuda CUDA APPS 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: http://www.dalsa.com/mv/products/software.aspx (click on "Nitrous" tab) http://www.dalsa.com/mv/products/saperatour.aspx (click on "Nitrous" pie slice) CUDA ZONE 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: http://bit.ly/9ZcP5t Submit Your Work Have a CUDA-related paper or research? Show it on CUDA Zone: http://is.gd/8G3E4 CUDA JOBS 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: http://bit.ly/bJ8VdQ - See more CUDA/GPU computing jobs here: http://is.gd/91IEu 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: sergei.chadov@gmail.com 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): https://www2.gotomeeting.com/register/929210147 Acceleware-Certified CUDA Training Silicon Valley‚ March 24-25: http://www.acceleware.com/index.cfm/cuda-training/mar24sunnyvale/ Calgary‚ April 12-16: http://www.acceleware.com/index.cfm/cuda-training/apr12calgary/ New Symposium at Univ. of Pittsburgh Symposium on Applications of GPUs in Chemistry and Materials Science, June 28-30, University of Pittsburgh. See: http://www.sam.pitt.edu/education/gpu2010.register.php 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: http://illinois.edu/lb/article/2101/36281 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: http://developer.nvidia.com/object/gpu_computing_online.html CUDA and GPU Computing Courses Over 310 universities are teaching CUDA and GPU Computing courses. See the list: http://www.nvidia.com/object/cuda_courses_and_map.html CUDA RESOURCES – CUDA Videos on YouTube: http://www.youtube.com/nvidiacuda – CUDA Toolkit: http://bit.ly/aKCENp – Developer Guides: http://developer.nvidia.com/object/gpucomputing.html – Programming Massively Parallel Processors, by D. Kirk, W. Hwu: http://is.gd/7bNYP CUDA ON THE WEB – Follow CUDA & GPU Computing on Twitter: www.twitter.com/gpucomputing – Network with other developers: www.gpucomputing.net – Stayed tuned to GPGPU news and events: www.gpgpu.org – Learn more about CUDA on CUDA Zone: www.nvidia.com/cuda 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 See previous issues of CUDA: Week in Review: http://www.nvidia.com/object/cuda_week_in_review_newsletter.html Send comments and suggestions to: cuda_week_in_review@nvidia.com You are receiving this email because you have previously expressed interest in NVIDIA products and technologies. Click here to opt in specifically to CUDA: Week in Review. Feel free to forward this email to customers, partners and colleagues. If you would like to stop receiving emails from NVIDIA. 2701 San Tomas Expressway, Santa Clara, CA 95050 Copyright © 2010 NVIDIA Corporation. All rights reserved.