|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: email@example.com.|
Reminder: The GPU Technology Conference (GTC), Sept. 20-23, is accepting proposals for sessions and research posters. Learn more: http://www.nvidia.com/object/gpu_technology_conference.html
|CUDA on iTunes!|
|Stanford University is offering lectures on iTunes U from the new computer science course ChS 193G: Programming Massively Parallel Processors with CUDA. The 10-week course includes hands-on CUDA projects. NVIDIA engineers Jared Hoberock and David Tarjan are the instructors. The course is based on the original UIUC ECE 498 AL: Applied Parallel Programming class created by Dr. Wen-mei Hwu and Dr. David Kirk. For info, see: http://news.stanford.edu/news/2010/april/engineering-cuda-course-042210.html
|Moore’s Law Commentary in Forbes|
|Forbes published an intriguing commentary by NVIDIA Chief Scientist Bill Dally titled "Life after Moore’s Law." The column begins: "For the past four decades, explosive gains in computing power have contributed to unprecedented progress in innovation, productivity and human welfare. But that progress is now threatened by the unthinkable: an end to the gains in computing power." Well worth reading in its entirety, the piece proposes that the time has come to take the leap into parallel processing in order to continue the growth in computing performance that has transformed industries and economies around the world. See: http://is.gd/bNIP4
|CUDA Coding in Korea|
|A CUDA coding contest recently took place in Korea. The three grand-prize winners were:
– Deok-su Kim, Korea Advanced Institute of Science and Technology (KAIST).
Topic: "Continuous collision testing."
– Yeong-ho Jeon, Soongsil University. Topic: "Water pollution prediction and response."
– Jong-su Kim, Yonsei University. Topic: "Matrix vector multiplication optimization."
The judges included Yeong-jun Kim, professor at Ewha Women’s University and Dae-seok Kwon, CEO of Clunix and professor at Seoul National University of Technology. Prizes included an NVIDIA ION-based PC and Samsung video player. See: http://www.nvidiaevent.co.kr/cudacontest/
|GPU-Powered AMBER 11 Accelerates Bio-Science Research|
|AMBER 11, the latest version of a popular application for biochemists, is now optimized to run on NVIDIA Tesla 20-series GPUs, achieving up to a 100X speedup over CPU-based servers. Dr. Ross Walker, research professor at the San Diego Supercomputer Center, University of California, San Diego, comments: "With GPUs, we can now do most of our work at the desktop and that changes everything." For info on AMBER 11, see: http://ambermd.org/gpus/. For info on Tesla Bio Workbench, see: http://www.nvidia.com/object/tesla_bio_workbench.html.
|High-Def Video Enhancement with vReveal 2.0|
|MotionDSP, an NVIDIA partner and video enhancement technology leader, has released vReveal 2.0, which adds support for current high-def video formats. vReveal is available in a free version ("vReveal") with an upgrade option to premium ("vReveal Premium"). In both versions, video processing runs up to 5X faster on CUDA GPUs (such as the GeForce GTX 480) vs. CPUs. vReveal makes it easy for users to stabilize, brighten, and sharpen videos with one click and then upload to YouTube and Facebook. Download the free app: http://www.vreveal.com/nvidia
|New on CUDA Zone: Accelerating Computational Fluid Dynamics|
|Extract: "GPUs traditionally designed for graphics have emerged as massively-parallel co-processors. Small-footprint desktop supercomputers with hundreds of cores can deliver teraflops of peak performance at the price of conventional workstations. A computational fluid dynamics (CFD) simulation with rapid computational turnaround time has the potential to transform engineering analysis and design optimization procedures.- Authors: J.C. Thibault and I. Senocak, Boise State University. See: http://is.gd/bMkI3 and http://www.youtube.com/watch?v=I7Kclvviy9g
|CUDA Zone Submissions|
|Have a CUDA-related paper, research, or app? Show it on CUDA Zone: http://is.gd/8G3E4
|CUDA JOB OF THE WEEK|
|Alion Science and Technology Corporation of Alexandria, Virginia, is seeking a signal and image processing scientist/engineer. Requirements include knowledge of FPGA and GPU hardware and coding and a high level of competence in environments including CUDA C and MatLab. Alion is an employee-owned company delivering technical expertise to government agencies and commercial customers. See: http://is.gd/bMp5r
|GPU Computing Webinars (CUDA C, OpenCL, Parallel Nsight and more…)|
|See upcoming May webinars: http://developer.nvidia.com/object/gpu_computing_online.html
– SagivTech CUDA Training, May 10-12, Ra’anana, Israel: http://www.sagivtech.com/24054.html
– Acceleware-Certified CUDA Training, May 19-20, Silicon Valley: http://is.gd/aV5fj
|CUDA and Academia|
|Over 340 universities are teaching CUDA and GPU Computing courses.
– See the list: http://www.nvidia.com/object/cuda_courses_and_map.html
– GPU Computing in the Oil & Gas Industry (Microsoft/NVIDIA)
– ISC ´10 GPU Computing Workshops
– Parallel Execution of Sequential Programs on Multi-Core Architectures
– GPUs in Chemistry and Materials Science
– Parallel Symbolic Computation 2010 (PASCO)
– Symposium on Chemical Computations on GPGPUs
– Unconventional High Performance Computing 2010 (UCHPC 2010)
– GPU Technology Conference 2010
(To list an event, email: firstname.lastname@example.org)
|GPU-accelerated linear algebra library from EM Photonics: http://www.culatools.com
|NVIDIA Parallel Nsight|
|Download the Parallel Nsight Beta: www.nvidia.com/nsight
|Download CUDA Toolkit 3.0: http://bit.ly/aKCENp
|Download developer guides and documentation: http://developer.nvidia.com/object/gpucomputing.html
– 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
|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
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
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