Friday, April 23, 2010, Issue #18 - 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. Reminder: The GPU Technology Conference (GTC), Sept. 20-23, is now accepting proposals for sessions and research posters from industry and academia. – For questions about submissions, email: vcrimmins@nvidia.com – Learn more here: http://www.nvidia.com/object/gpu_technology_conference – Join the email update list here: http://www.nvidia.com/object/email_updates CUDA NEWS Books! Books! Books! GPU computing is being taught at over 330 universities around the world, and now there are at least 10 educational books available/in progress on the topic of programming GPUs with CUDA C and OpenCL. This includes the brand-new "Basics of CUDA Technology" by A.V. Boreskov of Russia. The books reflect the international momentum behind the GPU, as 4 are in Japanese, 3 in Chinese, 2 in English, and 1 in Russian. See them listed here: http://www.nvidia.com/object/cuda_books.html. New Update from AccelerEyes AccelerEyes released a major update to its Jacket software platform for MATLAB (Jacket is a productivity platform for GPU acceleration). Jacket version 1.3 incorporates many new features, including support for double precision linear algebra using the CUDA architecture. Linear algebra has applications in the natural sciences (e.g. chemistry, physics, astronomy) as well as the social sciences (e.g. economics). "Initial results are very promising in Jacket 1.3, with an 8-10 times performance increase," said Norman White, Faculty Director at NYU’s Stern Center for Research Computing. For more details, see: http://www.accelereyes.com/resources/announce and http://www.accelereyes.com/news/version13 CUDA ZONE New on CUDA Zone: N-body Code on GPUs Extract: "We present the characteristics and performance, both in terms of computational speed and precision, of a numerical code which integrates the equation of motions of N ‘particles’ interacting via Newtonian gravitation and moving in an external galactic smooth field. The code, NBSymple, has been parallelized twice by means of the CUDA architecture to make the evaluation as fast as possible on NVIDIA TESLA C1060s. The code works in single precision floating point arithmetic or in double precision." Authors: R. Capuzzo-Dolcetta, A. Mastrobuono-Battisti, D. Maschietti (Dept. of Physics, Sapienza, Univ. of Rome, Italy). [Ed. note: An N-body simulation is a simulation of a dynamic system of particles, usually under the influence of physical forces, such as gravity.] See: http://is.gd/bCOmG CUDA Zone Submissions Have a CUDA-related paper, research, or app? Show it on CUDA Zone: http://is.gd/8G3E4 CUDA JOBS The Irish Centre for High-End Computing (ICHEC) will provide funding for a select number of talented undergraduate students to engage in 10-week summer projects in Ireland. The projects are related to high-performance computing and computational science and will be under the supervision of ICHEC scientists and systems staff. See: http://is.gd/bBgc3 CUDA EVENTS International Supercomputing Conference ISC will be held in Hamburg, Germany, May 30-June 3. NVIDIA and its partners will be on hand to present HPC solutions, tutorials, and sessions. See: http://www.nvidia.com/object/isc2010.html CUDA EDUCATION NEW: SagivTech CUDA Training May 10-12, Ra´anana, Israel. SagivTech offers CUDA courses in Israel and Europe, including customized training for organizations. Expertise in state-of-the-art image processing. See: http://www.sagivtech.com/24054.html GPU Computing Webinars (CUDA C, OpenCL, Parallel Nsight and more…) See schedule: http://developer.nvidia.com/object/gpu_computing_online.html Acceleware-Certified CUDA Training May 19-20, Silicon Valley: http://www.acceleware.com/index.cfm/cuda-training/may19sunnyvale/ GPGPU Conferences and Symposia – GPU Computing in the Oil & Gas Industry (Microsoft/NVIDIA), May 12, Houston:    https://msevents.microsoft.com/CUI/EventDetail.aspx?EventID=1032446248&culture=en-US – Parallel Execution of Sequential Programs on Multi-Core Architectures. June 20,    France: http://cccp.eecs.umich.edu/pespma/cfp.html – GPUs in Chemistry and Materials Science, June 28-30, Univ. of Pittsburgh:    http://www.sam.pitt.edu/education/gpu2010.register.php – Parallel Symbolic Computation 2010 (PASCO), July 21-23, France:    http://pasco2010.imag.fr/contest.html – Symposium on Chemical Computations on GPGPUs, Aug. 22-26, Boston:    http://illinois.edu/lb/article/2101/36281 – UnConventional High Performance Computing 2010 (UCHPC 2010), Aug. 31-Sept. 1, Italy:    http://www.lrr.in.tum.de/~weidendo/uchpc10/ – GPU Technology Conference 2010, Sept. 20-23, San Jose, Calif.:    http://www.nvidia.com/gtc (now accepting proposals from industry and academia) CUDA and GPU Computing Courses Over 330 universities are teaching CUDA and GPU Computing courses. – See the list: http://www.nvidia.com/object/cuda_courses_and_map.html CUDA RESOURCES CULA LAPACK GPU-accelerated linear algebra library (from EM Photonics): http://www.culatools.com (See recent CULA blog post titled "Initial Fermi Performance": http://www.culatools.com/blog/2010/04/16/11-initial-fermi-performance) NVIDIA Parallel Nsight Download the Parallel Nsight Beta: www.nvidia.com/nsight CUDA Toolkit Download CUDA Toolkit 3.0: http://bit.ly/aKCENp CUDA Documentation Download developer guides and documentation: http://developer.nvidia.com/object/gpucomputing.html CUDA Books 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 – CUDA on YouTube: http://www.youtube.com/nvidiacuda 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. 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