|Welcome to "CUDA: Week in Review," an online news summary for the worldwide CUDA and GPU Computing community. Follow us on Twitter: www.twitter.com/gpucomputing. See previous issues: http://is.gd/cBXbg
|GPU TECHNOLOGY CONFERENCE COUNTDOWN: 20 DAYS!|
|GTC 2010 Keynote Speakers Announced|
|GTC 2010 is the place to be in September. Over 240 technical sessions and tutorials will be presented by industry experts and researchers from around the world. And, we are delighted to announce that two very distinguished and exciting computing visionaries will join NVIDIA CEO Jen-Hsun Huang as GTC 2010 keynote speakers:
– Dr. Sebastian Thrun, robotics pioneer at Stanford and distinguished engineer at Google
– Dr. Klaus Schulten, computational biologist, Univ. of Illinois, Urbana-Champaign
|GTC 2010 Live Chat with Bill Dally and David Luebke|
|Leading up to GTC, we are holding a series of live chats with NVIDIA experts. The next live chat will be on Wednesday, September 1 at 11:30 am pacific with Bill Dally, NVIDIA’s Chief Scientist and David Luebke, NVIDIA’s Director of Graphics Research. To participate, go to http://blogs.nvidia.com/ntersect/gtc/
|GTC 2010 Online Resources|
|For more info on keynotes, see: GTC blog post|
For session list, see: https://nvidia.confreg.com/gputechconference/schedule/by-session/
To register: www.nvidia.com/gtc (code: GMCUDANEWS10)
|U.S. Air Force Selects EM Photonics, Univ. of Delaware to Develop GPU Computing Algorithms|
|EM Photonics and the University of Delaware have been selected by the Air Force Office of Scientific Research (AFOSR) to develop algorithms for scientific computing, modeling and simulation for a multi-GPU environment. The team will utilize the University’s largest supercomputer, code-named "Geronimo," which was built with NVIDIA CUDA-based Tesla GPU computing technology. See: http://www.udel.edu/udaily/2011/aug/taufer-em-photonics082310.html
|GPUs Highlighted at American Chemical Society Meeting|
|GPU computing was well represented at the ACS meeting this month in Boston:|
– A symposium on "Chemical Computations on GPGPUs" was chaired by Dr. Todd Martinez
(Stanford) and Dr. Thom Dunning (National Center for Supercomputing Applications).
– 30+ GPGPU papers were presented.
– Paper topics included acceleration of popular algorithms and codes, such as AMBER,
DL_POLY, Folding@Home, GAMESS, HOOMD, OpenEye ROCS and TERACHEM.
– Ross Walker of the San Diego Supercomputer Center presented his work on MPI-AMBER,
announcing outstanding results and availability in the next few weeks.
– Best GPGPU paper award went to by J.L. Belof and B. Space for “Solving the many-body
field questions of a point induced dipole potential on GPUs.” The authors won a Tesla C2050.
– NVIDIA presenters included Scott LeGrand and Duncan Poole.
|CUDA Users: Please take a few minutes to tell us how you are using CUDA-capable GPUs and how we can better meet your needs.|
|For a list of CUDA-enabled GPUs, see: http://www.nvidia.com/object/cuda_gpus.html|
|CUDA JOB OF THE WEEK|
|University of Geneva, Switzerland, is offering a one-year programmer position under the supervision of Prof. Bastien Chopard. Principal topic of investigation is the development of Lattice Boltzmann code in CUDA. The position includes close collaboration with teams working on the open-source projects Palabos (http://www.lbmethod.org/palabos) and Sailfish (http://sailfish.us.edu.pl). For further information, contact Dr. Jonas Latt, EPFL Switzerland, firstname.lastname@example.org.
|NVIDIA Parallel Nsight Webinars|
|NVIDIA GPU Computing Webinars|
– For info on all upcoming webinars, see: www.nvidia.com/webinars
|Training from Acceleware|
– Sept. 13-17, Calgary: www.acceleware.com/sep13calgary
|Training from SagivTech|
– Sept. 24, Santa Clara, Calif: http://www.sagivtech.com/36923.html
|Training from EMPhotonics|
|– On-site training programs: http://www.emphotonics.com/services/cuda-training
|– New certification program for GPU computing developers: www.nvidia.com/certification
|CUDA and Academia|
|– Over 350 universities are teaching CUDA and GPU Computing courses around the world.
– The CUDA Center of Excellence Program recognizes universities expanding the frontier
of parallel computing.
– The CUDA Research Center Program recognizes institutions performing leading-edge
– The CUDA Teaching Center Program recognizes universities providing education and
– The Academic Partnership Program provides support to researchers using GPUs to
solve the world´s most challenging problems.
– Learn more about NVIDIA´s Research and University activities at http://research.nvidia.com/
|– Download CUDA 3.1 Toolkit: http://bit.ly/aKCENp
– OpenCL v1.1 pre-release drivers and SDK code samples are available to GPU Computing
registered developers. Log in or apply for an account to download.
– Unconventional High Performance Computing 2010 (UCHPC 2010)
– GPU Technology Conference (GTC) 2010
– Palo Open Conference: Business Intelligence Acceleration with GPUs
– MATLAB Conference 2010
– Supercomputing 2010
– IEEE International Parallel & Distributed Processing Symposium
(To list an event, email: email@example.com)
|CUDA Articles in Dr. Dobb's|
– Supercomputing for the Masses, Part 19: http://is.gd/dTIXj
– Supercomputing for the Masses, Part 18: http://is.gd/cs6b9
– Supercomputing for the Masses, Part 17: http://is.gd/cs6eI
– Supercomputing for the Masses, Part 16: http://is.gd/citaC
|– CUDA By Example by J. Sanders, E. Kandrot: http://is.gd/eo4pF
– Programming Massively Parallel Processors by D. Kirk, W. Hwu: http://is.gd/7bNYP
– See additional books here: http://www.nvidia.com/object/cuda_books.html
|– Download developer guides and documentation:
|CUDA ON THE WEB|
– Read previous issues of CUDA: Week in Review: http://is.gd/cBXbg
– 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
– Read Kudos for CUDA: http://www.hpcwire.com/features/Kudos-for-CUDA-97889444.html
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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