| Friday, June 11, 2010, Issue #25 - Newsletter Home |
| WELCOME | ||||||||||||||||||||||||||||||||
| Welcome to "CUDA: Week in Review," a weekly newsletter for the worldwide CUDA and GPU Computing community. – Contact us at: cuda_week_in_review@nvidia.com. – Follow us on Twitter: www.twitter.com/gpucomputing. – See previous issues: http://is.gd/cBXbg Update on GTC 2010 (GPU Technology Conference) – We are pleased to welcome Adobe, HP, Microsoft, PNY, Supermicro and Dell as GTC 2010 Platinum Sponsors, and Cooley LLP as a GTC 2010 Emerging Companies Summit Sponsor – GTC 2010 registration is now open! – Special code for "CUDA: Week in Review" readers - GMCUDANEWS10 |
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| CUDA NEWS | ||||||||||||||||||||||||||||||||
| GPU Computing - At the Tipping Point | ||||||||||||||||||||||||||||||||
IEEE Computer Society has published an informative article about GPU Computing by NVIDIA's John Nickolls and Bill Dally. Here's the introduction:
Read full article here: http://www.computer.org/portal/web/computingnow/0610/whatsnew/micro |
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| Learn about MAGMA from the Experts | ||||||||||||||||||||||||||||||||
| Professor Jack Dongarra and Dr. Stan Tomov of the University of Tennessee will present a webinar on "The MAGMA Project: Acceleration of Dense Linear Algebra on the GPU" on Monday, June 14 at 9:00 a.m. pacific. MAGMA (Matrix Algebra on GPU and Multicore Architectures) aims to develop a dense linear algebra library similar to LAPACK but for heterogeneous/hybrid architectures, starting with current "Multicore+GPU" systems. – Prof. Jack Dongarra has a deep background in the development, testing and documentation of mathematical software. He has contributed to the design and implementation of open source software including EISPACK, LINPACK, the BLAS, LAPACK, ScaLAPACK, Netlib, PVM, MPI, NetSolve, Top500, ATLAS, and PAPI. See bio: http://www.netlib.org/utk/people/JackDongarra/ – Dr. Stan Tomov has been involved in research and development for LAPACK/scaLAPACK, multicore computing and MAGMA. Research interests include parallel algorithms and high performance scientific computing. See bio: http://www.cs.utk.edu/~tomov/resume.html – Sign up for the MAGMA webinar here: https://www2.gotomeeting.com/register/565103979 – This presentation is a feature of NVIDIA’s ongoing series of webinars on GPU Computing |
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| CUDA APPS | ||||||||||||||||||||||||||||||||
| Attention Photographers: New Photoshop Plugin Powered by CUDA | ||||||||||||||||||||||||||||||||
| Digital Anarchy, provider of software for photographers and digital artists, recently introduced "Beauty Box Photo" skin retouching software - the world’s first CUDA-accelerated Photoshop plugin. The software automatically smoothes skin and removes blemishes, saving photographers hours of time. It identifies skin tones and creates an ‘intelligent mask’ to limit the smoothing effect to skin areas while keeping facial details sharp. Beauty Box Photo gets its render speed from new technology from Toonmation and leverages CUDA for up to 6X faster processing. – Read about Beauty Box Photo: http://www.digitalanarchy.com/beautyPS/main.html – Read about Digital Anarchy: http://www.digitalanarchy.com/ – Read about Toonmation: http://toonamation.com/ |
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| GPU-Accelerated Imaging and Vision Processing | ||||||||||||||||||||||||||||||||
| In March we introduced you to Canada-based DALSA, a leader in machine vision systems. At a recent event in Boston called "The Vision Show," DALSA announced that GPUs enable the "Sapera Nitrous" product to accelerate image processing for filters, point-to-point, color and other image/vision processing functions. DALSA products are used across applications from solar panel inspection to postal automation. – Read the press release: http://www.dalsa.com/mv/news/news.aspx?itemID=241 – Learn more about Sapera Nitrous: http://www.dalsa.com/mv/products/Nitrous.aspx |
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| CUDA ZONE | ||||||||||||||||||||||||||||||||
| New on CUDA Zone: Acceleration of the Smith-Waterman Algorithm using GPUs | ||||||||||||||||||||||||||||||||
| Application Domain: DNA/protein sequence testing Authors: Ali Khajeh-Saeed, Univ. of Mass at Amherst; Stephen Poole, Oak Ridge National Lab; J. Blair Perot, Univ. of Mass at Amherst Extract: "Finding regions of similarity between two very long data streams is a computationally intensive problem referred to as sequence alignment. Perhaps the most well known application of sequence matching is the testing of DNA or protein sequences against genome databases. The Smith-Waterman algorithm is a method for characterizing how well two sequences can be aligned…. The results indicate that for large problems a single GPU is up to 45 times faster than a CPU for this application, and the parallel implementation shows linear speed up on up to 4 GPUs." See: http://is.gd/cJELx |
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| CUDA Zone: Have a CUDA-related app or paper? Let us know when you post it on CUDA Zone and we'll send you a CUDA t-shirt! | ||||||||||||||||||||||||||||||||
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| CUDA JOB OF THE WEEK | ||||||||||||||||||||||||||||||||
| KLA-Tencor, supplier of process control and yield management solutions, is seeking an algorithm engineer. The ideal candidate will have an M.S. or Ph.D. in Computer Science or Electrical Engineering, with a background in image processing or digital signal processing with an emphasis on computational algorithms, optimization and parallel computing. Experience using SIMD extensions or GPU programming (CUDA/OpenCL) is preferred. See: http://kla-tencor-jobs.blogspot.com/ | ||||||||||||||||||||||||||||||||
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| CUDA EDUCATION | ||||||||||||||||||||||||||||||||
| GPU Computing Webinars (CUDA C, OpenCL, Parallel Nsight and more…) | ||||||||||||||||||||||||||||||||
| See June webinar schedule: http://developer.nvidia.com/object/gpu_computing_online.html. Upcoming webinars include: – Intro to the MAGMA Project - Acceleration of Dense Linear Algebra
– Intro to CULA GPU Accelerated Linear Algebra
– Rapid Application Development Platform for GPGPUs - Jacket / MATLAB
– Intro to MainConcept's CUDA H.264/AVC Encoder
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| CUDA Training | ||||||||||||||||||||||||||||||||
– CUDA training from Acceleware
– CUDA training from SagivTech
– CUDA training from EMPhotonics
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| CUDA Research and Certification | ||||||||||||||||||||||||||||||||
| NVIDIA has launched new programs for GPU Computing developers. For more info, see: http://www.nvidia.com/object/io_1275409333119.html | ||||||||||||||||||||||||||||||||
| CUDA and Academia | ||||||||||||||||||||||||||||||||
Over 350 universities are teaching CUDA and GPU Computing courses. We recently learned about a new course taught at the University of Jordan:
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| CUDA Center of Excellence Program | ||||||||||||||||||||||||||||||||
| The CUDA Center of Excellence (CCOE) Program recognizes universities that are expanding the frontier of massively parallel computing using CUDA. See: http://research.nvidia.com/content/cuda-centers-excellence | ||||||||||||||||||||||||||||||||
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| CUDA CALENDAR | ||||||||||||||||||||||||||||||||
– DoD High Performance Computing Modernization Program (HPCMP) Users Group
– European Association of Geoscientists & Engineers (EAGE) Conference
– Parallel Execution of Sequential Programs on Multi-Core Architectures
– GPGPU Briefing on Financial Services (Microsoft/NVIDIA)
– SIFMA Financial Services Tech Expo
– High Performance Graphics 2010
– GPUs in Chemistry and Materials Science
– Parallel Symbolic Computation 2010 (PASCO)
– SIGGRAPH
– Virtual School of Comp. Science & Engineering Summer School
– Symposium on Chemical Computations on GPGPUs
– Unconventional High Performance Computing 2010 (UCHPC 2010)
– GPU Technology Conference (GTC) 2010
– Supercomputing 2010
– IEEE International Parallel & Distributed Processing Symposium
(To list an event, email: cuda_week_in_review@nvidia.com) |
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| CUDA RESOURCES | ||||||||||||||||||||||||||||||||
| CUDA Articles in Dr. Dobb's | ||||||||||||||||||||||||||||||||
| – 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 – Supercomputing for the Masses, Part 15: http://is.gd/citnJ |
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| CUDA Books | ||||||||||||||||||||||||||||||||
| – 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 |
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| 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 | ||||||||||||||||||||||||||||||||
| NVIDIA Parallel Nsight | ||||||||||||||||||||||||||||||||
| Download the Parallel Nsight Beta: www.nvidia.com/nsight | ||||||||||||||||||||||||||||||||
| Download the Parallel Nsight Beta Release Notes: http://bit.ly/9iEYMs | ||||||||||||||||||||||||||||||||
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| CUDA ON THE WEB | ||||||||||||||||||||||||||||||||
| – NEW: Check out the NVIDIA Research site: http://research.nvidia.com – 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 – Watch CUDA on YouTube: http://www.youtube.com/nvidiacuda |
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| 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. Send comments and suggestions to: cuda_week_in_review@nvidia.com |
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