Friday, April 2, 2010, Issue #15 - 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 Advancing the Development of RF Systems People rely on radio frequency (RF) systems in all kinds of everyday devices, from cell phones and TVs to remote controls and set-top boxes. RF systems are also used in medical devices for the treatment of health problems such as rapid heartbeat, joint pain, and sleep apnea. Researchers at Aalborg University in Denmark are applying GPUs and the AccelerEyes Jacket platform for MATLAB to advance the theory, design, and implementation of RF systems. A team led by Dr. Torben Larsen is using CUDA and AccelerEyes to develop new algorithms that enable RF systems to run in a fraction of the time that it takes on a CPU. Data interpolation and Fast Fourier Transforms (FFT), for example, are common tasks performed in signal processing applications. Dr. Larsen’s team found that these tasks run 25 to 35 times faster with NVIDIA GPUs and Jacket as compared to CPUs. By increasing the speed at which RF systems can be developed and tested, the team aims to help bring effective and safe RF-enabled devices to market more quickly. Read more here: http://is.gd/b8Q4l CUDA APPS Faster Machine Learning Techniques Using GPUs Support Vector Machine (SVM) is one of the most commonly applied machine learning techniques for classification. It’s used across areas such as web indexing and classification, text classification, image recognition, bio-informatics, predictive financial models, and business analytics. Two new CUDA GPU-enabled SVM software packages are now available as potential drop-in replacements for libSVM (the most popular SVM implementation) showing speedups of 10 to 70X over libSVM. For info on these packages, see: – MultiSVM Multiclass SVM: http://code.google.com/p/multisvm – cuSVM (includes MATLAB MEX wrapper): http://patternsonascreen.net/cuSVM.html CUDA ZONE New on CUDA Zone: Allinea Announces Tools for CUDA Architecture U.K.-based Allinea Software announced a pre-release version of the Distributed Debugging Tool (DDT) for the CUDA architecture, coinciding with the release of CUDA Toolkit 3.0. Over the past year, Allinea has collaborated with the French Commissariat a l’Energie Atomique (CEA) to develop CUDA-specific features within its DDT product. Demonstrations of DDT for CUDA will take place at the International Supercomputing Conference in Hamburg, Germany, May 30-June 5. David Lecomber, CTO of Allinea Software, comments: "We are delighted to see the results of our collaboration with the CEA making it into our mainstream DDT product. We are now able to provide application developers with a single tool that can debug hybrid MPI, OpenMP, and CUDA applications on a single workstation or GPU cluster." See: http://is.gd/b7bh5 CUDA Zone Submissions Have a CUDA-related paper, research, or application? Show it on CUDA Zone: http://is.gd/8G3E4 CUDA JOBS CST - Computer Simulation Technology AG in Darmstadt, Germany develops and markets high performance software for the simulation of electromagnetic fields in all frequency bands. Its customers represent a range of industries, from telecommunications and automotive to electronics and medical. The company is seeking a full-time CUDA developer for development of 3D electromagnetic simulation solutions. – See posting here: http://is.gd/b75ZH – See more CUDA/GPU computing jobs here: http://is.gd/91IEu CUDA Education Seminar: GPU Computing in the Oil & Gas Industry GPU computing is rapidly being adopted in the oil & gas industry, especially for seismic processing and reservoir simulation. On May 12, Microsoft and NVIDIA will team up to offer a seminar/workshop for application programmers in this field. The event will provide an overview of NVIDIA Parallel Nsight for Microsoft Visual Studio, including a look at how this development environment can be used for debugging source code transparently on GPU hardware and profiling applications. To register, visit: https://msevents.microsoft.com/CUI/EventDetail.aspx?EventID=1032446248&culture=en-US GPGPU Conferences and Symposia – Parallel Symbolic Computation 2010 (PASCO), July 21-23, France. Enter the Computer    Algebra Parallel Programming Contest. See: http://pasco2010.imag.fr/contest.html – Workshop on UnConventional High Performance Computing 2010 (UCHPC 2010),    Aug. 31-Sept. 1, Naples, Italy (with Euro-Par 2010). Submission deadline: June 14.    See: http://www.lrr.in.tum.de/~weidendo/uchpc10/ – 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 – 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 Acceleware-Certified CUDA Training Silicon Valley, May 19-20: http://www.acceleware.com/index.cfm/cuda-training/may19sunnyvale/ Calgary, April 12-16: http://www.acceleware.com/index.cfm/cuda-training/apr12calgary/ GPU Computing Webinars (CUDA C and OpenCL) See schedule: http://developer.nvidia.com/object/gpu_computing_online.html CUDA and GPU Computing Courses Over 320 universities are teaching CUDA and GPU Computing courses. See the list: http://www.nvidia.com/object/cuda_courses_and_map.html Industry Event: Visual Studio Launch Conference On April 12, Microsoft will launch Visual Studio 2010 and Silverlight 4 at the Microsoft Visual Studio Launch Conference, Las Vegas. NVIDIA will be on hand to demonstrate NVIDIA Parallel Nsight. See: http://www.devconnections.com/shows/SP2010VS CUDA DOWNLOADS – Download CUDA Toolkit 3.0: http://bit.ly/aKCENp – Download Developer Guides: http://developer.nvidia.com/object/gpucomputing.html CUDA RESOURCES – GPU Technology Conference (GTC) 2010 - Sept. 20-23, San Jose, Calif: www.nvidia.com/gtc – GPGPU Book: 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. Feel free to forward this email to customers, partners and colleagues. Copyright © 2010 NVIDIA Corporation. All rights reserved. 2701 San Tomas Expressway, Santa Clara, CA 95050.