Read the Whitepaper on "Fermi", NVIDIA's Next-Gen CUDA Architecture
NVIDIA's next-generation CUDA architecture, codenamed "Fermi," is the outcome of a radical rethinking of the role, purpose, and capability of the GPU.
CUDA Superhero Challenge Winners Announced
NVIDIA's first CUDA Superhero Challenge, hosted in conjunction with TopCoder, concluded on Sept. 25. First place went to Micha Riser of Switzerland, closely followed by runner up Hou Qiming of China. Rounding out the top five were Sergey Ilin, Russian Federation; Jaco Cronje, South Africa; and Noriyuki Futatsugi, Japan. The challenge focused on image processing using GPU-accelerated connected component labeling (CCL). The next challenge starts on November 23, 2009.
Oak Ridge National Laboratory Looks to NVIDIA “Fermi” Architecture For New Supercomputer
SANTA CLARA, Calif. — Sep. 30, 2009 — Oak Ridge National Laboratory (ORNL) announced plans today for a new supercomputer that will use NVIDIA’s next generation CUDA GPU architecture, codenamed “Fermi”.
NVIDIA Unveils Next Generation CUDA GPU Architecture – Codenamed “Fermi”
SANTA CLARA, Calif. — Sep. 30, 2009 — NVIDIA Corp. today introduced its next generation CUDA GPU architecture, codenamed “Fermi”.
mental images Unveils iray Rendering Solution
SANTA CLARA, Calif. and BERLIN, Germany — Sept. 30, 2009 — mental images, an NVIDIA company, today introduced iray – the first fully GPU accelerated, commercially supported, turn-key rendering solution for a wide range of 3D graphics application developers.
NVIDIA Introduces Nexus, The Industry’s First Integrated GPU/CPU Environment For Developers Working With Microsoft Visual Studio
SANTA CLARA, Calif. — Sept 30, 2009 — NVIDIA Corp. today introduced NVIDIA® Nexus, the industry’s first development environment for massively parallel computing that is integrated into Microsoft Visual Studio, the world’s most popular development environment for Windows-based solutions and Web applications and services.
Sony Pictures Imageworks Creates Tornado Out Of Spaghetti Sauce With The Help Of NVIDIA Technology
SANTA CLARA, Calif. — Sept. 29, 2009 — NVIDIA Corporation, the inventor of the graphics processing unit (GPU), announced today that Sony Pictures Imageworks (SPI) utilized NVIDIA Quadro processors to accelerate animation and visual effects production of their latest hit film “Cloudy With a Chance of Meatballs”.
PGI’s CUDA Fortran Compiler Beta Release Now Available
A public beta release of the PGI CUDA-enabled Fortran compiler is now available. Developed in collaboration with The Portland Group, it is the first Fortran compiler compatible with CUDA GPUs. Fortran is well suited for numeric computation and scientific computing and is widely used in applications such as weather modeling and computational fluid dynamics. Developers can download the beta CUDA Fortran compiler for Linux, Windows and Mac OS at www.pgroup.com/support/downloads.php. The CUDA Fortran compiler requires the CUDA Software Developers Kit (SDK) which is available from CUDA Zone at www.nvidia.com/cuda.
NVIDIA Collaborates With Microsoft On High Performance GPU Computing
NVIDIA announced it is working with Microsoft to promote NVIDIA Tesla GPUs for high performance parallel computing using the Windows HPC Server 2008 operating system. “The coupling of GPUs and CPUs illustrates the enormous power and opportunity of multicore co-processing,” said Dan Reed, corporate vice president of Extreme Computing at Microsoft. “NVIDIA’s work with Microsoft and the Windows HPC Server platform is helping enable scientists and researchers in many fields achieve supercomputer performance on diverse applications.
NVIDIA Releases Industry’s First Public OpenCL Conformant GPU Drivers and Performance Profiler
NVIDIA has released the first public OpenCL conformant GPU drivers as well as a powerful performance profiling tool and an OpenCL Best Practices Guide. The OpenCL Visual Profiler uses the extensive performance instrumentation in NVIDIA’s OpenCL drivers and hardware performance signals designed into NVIDIA GPUs to provide developers with insight into performance bottlenecks and opportunities for optimization. The OpenCL Best Practices Guide is designed to help OpenCL developers programming for the CUDA architecture implement high performance parallel algorithms and understand best practices for GPU Computing. The OpenCL drivers, Visual Profiler, and Best Practices Guide are all available at: http://developer.nvidia.com/object/get-opencl.html.
NVIDIA Announces Live Webcast Coverage For GPU Technology Conference
NVIDIA’s inaugural GPU Technology Conference, which runs from Sept. 30 to Oct. 2, has sold out. Keynote and general session addresses will be webcast live. Webcast links, event coverage, and conference details can be found at www.nvidia.com/gtc.
CUDA Zone Hits New Milestone - Over 560 Apps and Papers
The 560+ papers and apps posted on CUDA Zone cover a wide range of scientific, professional, creative, and consumer applications. They are developed / authored by scientists and engineers from all over the world – nearly every major country is represented. The speedups they achieve over traditional methods are dramatic -- almost all of them have speedups in excess of an order of magnitude.
Real-Time Digital Holographic Microscopy Using the GPU – New on CUDA Zone
In digital holographic microscopy (DHM), interfering wave-fronts from a coherent light-source are recorded on a sensor and the image digitally reconstructed by a computer. The image yielded provides a quantitative measurement of the optical thickness of the specimen. In order to obtain a reconstructed image from a hologram, numerous calculations for the Fresnel diffraction are required. The Fresnel diffraction can be accelerated by the FFT (Fast Fourier Transform) algorithm. However, real-time reconstruction from a hologram is difficult. For example, if one obtains a reconstructed image from a hologram whose size is 512×512 using an Intel Core 2 Duo E6300 CPU, the calculation time for the Fresnel diffraction takes about one second. In this paper, the authors describe a real-time DHM system using CUDA to speed up this calculation. Authored by Tomoyoshi Shimobaba, Yoshikuni Sato, Junya Miura, Mai Takenouchi, and Tomoyoshi Ito / Yamagata University, Japan.
Massively Parallel GPUs Accelerate Database Queries – New on CUDA Zone
This paper presents a new parallel indexing data structure that takes full advantage of the increasing thread-level parallelism emerging in multi-core architectures. In this approach, the authors’ Data Parallel Bin-based Index Strategy (DP-BIS) first bins the base data, and then partitions and stores the values in each bin as a separate, bin-based data cluster. In answering a query, the procedures for examining the bin numbers and the bin-based data clusters offer the maximum possible level of concurrency; each record is evaluated by a single thread and all threads are processed simultaneously in parallel. Submitted by Luke Gosink, Kesheng Wu, Wes Bethel, John D. Owens, Kenneth I. Joy / University of Calif. at Davis.
CUDA Drives Innovation in Broadcast and Film Production
IBC 2009, AMSTERDAM—SEPT. 10, 2009—NVIDIA is making it possible for production houses to work faster and easier with the immense quantity of high-resolution data generated for HDTV, Blu-Ray and 4K digital cinema.
GPU Renderer for Maya - Furry Ball from Art and Animation Studio - New on CUDA Zone
New GPU renderer features full Maya integration in Viewport, complete realtime dynamic fur and hair, bump mapping, shadows, reflection, and more. 100-300 times faster on GPU as compared to CPU. Submitted by Art and Animation Studio, Czech Republic.
NVIDIA Releases Industry’s First OpenCL Performance Profiler for the GPU
NVIDIA Releases Industry’s First OpenCL Performance Profiler for the GPU New OpenCL Visual Profiler for Windows and Linux now available. Leveraging the extensive performance instrumentation in NVIDIA’s OpenCL drivers and hardware performance signals designed into NVIDIA GPUs, the OpenCL Visual Profiler provides developers with insight into performance bottlenecks and opportunities for optimization.
CUDA Accelerates Digital Photo Library Management
SANTA CLARA, Calif.—Sept. 8, 2009—NVIDIA announced that CyberLink MediaShow 5, a new software program that organizes digital photos based on who is in them, is utilizing the CUDA parallel processing power of NVIDIA GeForce GPUs to search and sort photo libraries.
New Video on NVIDIA NEXUS for Visual Studio-based GPU Development
Check out the new trailer video for NEXUS, NVIDIA's upcoming Visual Studio-integrated toolset for graphics and GPU Computing. NEXUS includes powerful debugging and platform-wide performance tools. More information about NEXUS will be available at the GPU Technology Conference, Sept. 30 - Oct. 2, 2009.
IEEE Spectrum: Why Graphics Processors Will Transform Database Processing
Authors Andrea di Blas and Tim Kaldewey, researchers at Oracle, write about their work using graphics processors to comb through enterprise databases.
LAPACK for CUDA – New Linear Algebra Library from Magma Project
The MAGMA project aims to develop a dense linear algebra library similar to LAPACK but for heterogeneous/hybrid architectures, starting with current "Multicore+GPU" systems.
September CUDA Webinars. Sign up today!
Webinars on the basics of data parallel computing on GPUs leveraging NVIDIA’s CUDA architecture.
NVIDIA Delivers Comprehensive OpenCL Support under Snow Leopard
SANTA CLARA, Calif. —Sep. 3, 2009— Apple’s new Snow Leopard operating system (OS) is the first OS to integrate OpenCL, a cross-platform open standard that makes it possible for developers to tap into the vast gigaflops of computing power currently in the graphics processing unit (GPU) and use them for any application.
CUDA Supercharges Ray Tracing
Recent ray tracing demos: 1) NVIDIA OptiX ray tracing engine, built on the CUDA architecture, enables developers to quickly create highly-accelerated applications that employ ray tracing. 2) iray is a new rendering mode for the upcoming RealityServer and mental ray built on the CUDA architecture to deliver physically correct, global illumination from scenes using real-world materials and lighting. 3) VRay – Chaos Group has independently implemented a CUDA-based version of their popular ray tracing renderer that shows +20X speed increase over software version running on CPU.
NVIDIA CUDA Superhero Challenge Sparks Competitive Fire for GPU Computing Developers
SANTA CLARA, Calif.—Aug. 27, 2009— NVIDIA Corporation today announced that it will be working with TopCoder, a competitive software development community, on the CUDA Superhero Challenge, a series of contests for computer programmers who will harness the parallel processing power of the NVIDIA® CUDA™ architecture to solve some of computing’s biggest challenges.
NVIDIA GeForce GPUs and DirectCompute in Windows 7 Accelerate Digital Media Applications
SANTA CLARA, Calif.—Aug. 21, 2009— By harnessing the parallel processing power of NVIDIA® GeForce® GPUs and DirectCompute, a new technology in Windows 7, developers can take the power of graphics processors and make it available for general-purpose computing and create cutting-edge digital media applications.
Real-Time Fiber Tracking with CUDA – New on CUDA Zone
Fiber tracking is a technique based on "diffusion tensor magnetic resonance imaging" (DT-MRI) that allows a neurosurgeon to visualize the neuronal fibers in the brain. Submitted by Adiel Mittmann, Federal University of Santa Catarina.
New CULA Linear Algebra Library From EM Photonics Brings GPU Computing To Millions Of Developers
SANTA CLARA, Calif. —Aug. 17, 2009—EM Photonics today released a beta version of CULA, an implementation of the industry-standard LAPACK linear algebra library designed and optimized for NVIDIA’s massively parallel CUDA™-enabled graphics processing units (GPUs).
NVIDIA CUDA Technology Used To Recover Historic APOLLO 11 Man On The Moon Video
SANTA CLARA, CA—AUGUST 5, 2009—When NASA’s originalApollo 11 moon landing video was accidentally destroyed, it seemed theworld had lost a visual record of one of man’s greatest achievements.
NVIDIA Releases Version 2.3 of the CUDA Toolkit
NVIDIA has released a new version of the CUDA Toolkit and SDK for GPU Computing. The release includes performance improvements and expanded support for the cuda-gdb hardware debugger. Available for download.
NVIDIA Announces CUDA C Programming Best Practices Guide
NVIDIA’s first CUDA C Programming Best Practices Guide is designed to help developers programming for the CUDA architecture - using C with CUDA extensions - implement high performance parallel algorithms and understand best practices for GPU Computing.
PGI and NVIDIA Team to Deliver CUDA Fortran Compiler
The Portland Group®, a wholly-owned subsidiary of STMicroelectronics and leading supplier of compilers for high-performance computing (HPC), today announced an agreement with NVIDIA under which the two companies plan to develop new Fortran language support for CUDA GPUs.
Autodesk Leverages NVIDIA GPU Computing to Bolster Moldflow Software Performance
Autodesk today announced it has significantly increased the performance of the latest release of Autodesk Moldflow Insight 2010, part of its software suite for plastics injection molding, by further leveraging cutting-edge GPU technology from NVIDIA
CUDA Toolkit and SDK 2.3 Betas now available for registered developers
This release includes support for all CUDA-capable GeForce, Quadro, and Tesla products on WinXP/Vista/7, MacOS, and Linux. To join the GPU Computing Registered Developer Program, go to: http://developer.nvidia.com/page/registered_developer_program.html
NVIDIA and Supermicro Shatter 1U Server Performance Record
NVIDIA Corporation and Supermicro announced the immediate availability of a new class of server that combines massively parallel NVIDIA® Tesla™ GPUs with multi-core CPUs in a single 1U rack-mount server.
NVIDIA to Host Inaugural GPU Technology Conference
NVIDIA Corporation announced that its inaugural GPU Technology Conference will take place
September 30 to October 2, 2009. 5/26/09
NVIDIA Submits OpenCL 1.0 Driver to Khronos for Conformance Certification for Windows and Linux
NVIDIA Corporation today announced its OpenCL™ 1.0 drivers for Windows XP and LINUX have been submitted to the Khronos OpenCL Working Group for certification immediately after the conformance tests were approved. These pre-release drivers are now available to all NVIDIA GPU Computing registered developers.
NVIDIA CUDA TOOLKIT 2.2 RELEASED
NVIDIA announced today it has released version 2.2 of the CUDA Toolkit and SDK for GPU Computing. This latest release supports several significant new features that deliver a major leap forward in getting the most performance out of NVIDIA’s massively parallel CUDA-enabled GPUs. In addition, version 2.2 of the CUDA Toolkit includes support for Windows 7, the upcoming OS from Microsoft that embraces GPU Computing.
GeoStar And NVIDIA To Transform Oil And Gas Industry In China
NVIDIA Corporation and GeoStar, a leading Chinese geophysical services provider, unveiled today the launch of a new hardware and software solution that will transform seismic computation for oil and gas companies in China.
Cyberlink MediaShow Espresso Uses NVIDIA GPUs And CUDA Technology For Faster Video Encoding
NVIDIA today announced that Cyberlink has released its MediaShow Espresso, an easy to use software application that converts digital video for playback on different portable devices, such as the iPod, iPhone, or PSP at very high speeds with excellent quality.
‘NERO MOVE IT’ Gets 5-Fold Performance Boost From NVIDIA CUDA Architecture
NVIDIA today announced that NERO has released an update to its Nero Move it software that reduces video encoding time by up to five times by utilizing NVIDIA’s CUDA computing architecture built inside select NVIDIA Graphics Processing Units (GPUs).
NVIDIA Releases OpenCL™ Driver To Developers
NVIDIA Corporation, the inventor of the GPU, today announced the release of its OpenCL™ driver and software development kit (SDK) to developers participating in its OpenCL Early Access Program.
Programming The CUDA Architecture: A Look At GPU Computing
GPUs have quickly surpassed CPUs in terms of computation speed. Now programmers can use the CUDA architecture to help simplify their implementation.
NVIDIA Introduces Industry's First Hardware Debugger and Profiler For GPU Computing
The CUDA architecture continues to blaze a trail as the leading platform for developing and running GPU Computing applications, with support for C, OpenCL™ , DirectX™ Compute, Fortran and other languages and APIs. The latest CUDA 2.2 Beta contains a host of significant new features.
NVIDIA APEX Accelerates Physics Creation Pipeline
NVIDIA announced NVIDIA APEX, a new capability for the PhysX SDK. APEX provides artists, level designers, and game developers with easy-to-use tools that streamline the process of implementing scalable physics across multiple platforms.
CSI-Style Video Enhancement For Consumers
MotionDSP released vReveal, an easy-to-use Windows application for PCs that fixes common problems afflicting consumer-generated video. vReveal leverages the parallel processing power in NVIDIA CUDA-enabled GPUs.
NVIDIA Looking For Next Great GPU Computing Company
NVIDIA launched the GPU Ventures Program, a new global initiative whose aim is to identify, support, and invest in early stage companies leveraging the GPU for visual and other computing applications.
Nero Achieves Video Acceleration with NVIDIA's CUDA
Nero, creators of liquid media technology, previewed the latest version of Nero Move it, which now features support for the NVIDIA CUDA architecture, at the CeBIT trade fair.
New open-source software permits faster simulations of molecular motion on desktop computers
Whether vibrating in place or taking part in protein folding to ensure cells function properly, molecules are never still.
NVIDIA Names Stanford's Bill Dally As Chief Scientist, VP of Research
Bill Dally, chairman of Stanford University's computer science department, joined NVIDIA as Chief Scientist and Vice President of NVIDIA Research.
WIPRO To Offer CUDA Software Services To Global Customer Base
NVIDIA announced it is working closely with Wipro to provide CUDA™ professional services to their joint customers worldwide.
NVIDIA CUDA Technology Dramatically Advances The Pace Of Scientific Research
Once thought of as a technology used only for computer games, NVIDIA® GeForce® graphics processing units (GPUs) with CUDA™ technology are now being used for the serious business of scientific computation.
NVIDIA Adds OpenCL To Its Industry Leading GPU Computing Toolkit
NVIDIA announced its full support for the newly released OpenCL 1.0 specification from the Khronos Group.
CUDA Cleans Up At SuperComputing Industry Awards
Every year at the Supercomputing (SC) convention (http://sc08.supercomputing.org), the organizing committee and media partners give awards for outstanding high performance computing (HPC) research and achievements.
NVIDIA And CRAY To Deliver Tesla-Enabled CRAY CX1 Desk Side Super Computer
NVIDIA Corporation (Nasdaq: NVDA) and Cray (Nasdaq GM: CRAY) today announced the availability of NVIDIA Tesla C1060 GPU Computing processors in the new Cray CX1 line of supercomputers.
DICE Puts Faith In NVIDIA PhysX Technology For Mirror's Edge
In the award-winning videogame Mirror’s Edge™, DICE, an Electronic Arts Inc. studio, introduces players to a new heroine named Faith.
NVIDIA Tesla Gives Bull Customers A Revolutionary Performance Boost
Bull, a leading supplier of high performance computing (HPC) technologies, is partnering with NVIDIA to provide the Tesla™ S1070 GPU Computing System as the accelerator option for their HPC solutions.
NVIDIA And NEC Collaborate To Deliver GPU Computing Solutions To HPC Market
NVIDIA has announced today that it has begun a close collaboration with NEC to integrate NVIDIA® Tesla™ GPUs into its systems for the high performance computing (HPC) industry.
NVIDIA Tesla TurboCharges High-Performance Computing Industry With HP Proliant Servers
NVIDIA today announced that the Tesla™ S1070 Computing System is now being offered in the highly successful range of HP ProLiant servers.
NVIDIA Tesla Makes Personal SuperComputing A Reality
Today, scientific research is carried out on supercomputing clusters, a shared resource that consumes hundreds of kilowatts of power and costs millions of dollars to build and maintain.
Mathematica Users Get 100x Performance Boost From NVIDIA CUDA
At SC08, Wolfram Research will demonstrate a new version of Mathematica, the world’s most powerful general computational software, that integrates CUDA®, NVIDIA’s parallel GPU computing architecture.
NVIDIA Demonstrates Powerful GPU Computing Solution From Lenovo At SC08
Today at SC08, NVIDIA demonstrated a Lenovo ThinkStation equipped with Tesla™ C1060 GPU Computing processing technology.
Tokyo Tech Builds First Tesla GPU Based Heterogeneous Cluster To Reach Top 500
The Tokyo Institute of Technology (Tokyo Tech) today announced a collaboration with NVIDIA to use NVIDIA® Tesla™ GPUs to boost the computational horsepower of its TSUBAME supercomputer.
OpenGeoSolutions Transforms Seismic Modeling With NVIDIA TESLA
Geophysicists in the oil and gas industry are seeking more accurate images of what lies beneath the earth. In order to find what’s been buried for millions of years, Calgary-based OpenGeoSolutions uses a technique called “Spectral Decomposition” specifically to reveal geological information that goes beyond classic seismic resolution and detection.
Nvidia’s $50 card destroys ATI’s $500 one or “Why ATI sucks in Folding?”
The Bright Side of IT
As you might already know, I am a bit enthusiastic when it comes to distributed computing. I’ve been looking for aliens through SETI@home, later with BOINC… but then, Folding@Home showed up and I became an enthusiast for this valuable project from Stanford University.
Introduction, CPU and GPU differences
Parallel computing has already entered the mass market and 3D games. Universal devices with multi-core processors for parallel vector computing in 3D graphics reach high peak performance, CPUs cannot keep up with it.
Is Your Personal Computer A CUDA-Enabled Speed Merchant?
Sometimes I don’t hear a rumble until it becomes a roar. I’m not sure if CUDA has become a roar yet, but my ears have perked up based on a bunch of announcements I’ve received over the past few months. If CUDA hasn’t registered on your radar yet, here’s a brief summary.
GPUs Finding A New Role on Wall Street
One of the new kids on Wall Street is GPU computing, a technology that is making inroads across nearly every type of HPC application. The vector processing capabilites of GPUs makes them especially well-suited to financial analytics.
GPUs Finding A New Role on Wall Street
With clock speeds more or less stagnant now and the promise of multicore CPU scalability still a pipe dream, the data parallelism offered by GPUs is one way at least some applications can jump back on the performance curve. The way Hanweck sees it, "from a technology standpoint, GPUs are going to change the way the world works."
Nvidia Chip Speeds Up Imaging for Industrial Use
The New York Times
Energy exploration firms, clothing designers, medical companies and financial services firms have also bought systems running on Nvidia chips. All of these companies share a common problem: they need hardware that can analyze a vast quantity of data and do it much faster than standard computers.
CUDA, Supercomputing for the Masses: Part 8
Optimized libraries often provide an easy way to improve performance of applications. When porting large legacy projects, libraries may be the only real way to optimize for a new platform because code changes would require extensive validation efforts.
NVIDIA to Offer Its New Chips in the New Cray Desktop
After more than two years of pushing its scientific computing efforts, Nvidia’s graphics processors will be offered as an option in the newest line of Cray desktop supercomputers. The chipmaker plans to announce next week that its Tesla chips can be used in the $25,000 Cray desktop supercomputer, according to Nvidia spokesperson Andrew Humber. He said Nvidia has been in talks with Cray ever since the chipmaker announced its Tesla line of graphics processors in 2007, but that this is the first deal the two companies have inked.
NCSA to add 62 teraflops of compute power with new heterogeneous system
University of Illinois' National Center for Supercomputing Applications
Installation has begun on a new computational resource at the National Center for Supercomputing Applications (NCSA) at the University of Illinois at Urbana-Champaign. Lincoln will deliver peak performance of 62.3 teraflops and is designed to push the envelope in the use of heterogeneous processors for scientific computing.
Agilent Collaborates with NVIDIA for Simulation
Desktop Engineering Online
Agilent Technologies Inc. announced its work with NVIDIA to accelerate signal integrity simulations using NVIDIA's CUDA-based GPUs. The association is expected to yield the commercial release of a GPU-enabled ADS Transient Convolution Simulator that will allow signal integrity designers to run these simulations faster than before.
CUDA, Supercomputing for the Masses: Part 7
CUDA and CUDA-enabled devices are co-evolving to deliver more performance and capability with each new generation. NVIDIA's recent introduction of the GeForce 200-series and Tesla 10-series of products, shows the rapidity of this evolution as roughly twice the hardware capability is now available at the same price point of the previous line of products plus the 200-series includes the addition of some valuable (and potentially indispensable) new features.
NVIDIA's GeForce GPUs Used for More Than Graphics
New consumer application pack uses NVIDIA CUDA technology to improve performance beyond graphics on NVIDIA GeForce GPUs. Consumers want blazing fast performance -- whether blasting their way through the latest game or being socially responsible and sharing their PC's processing power to help find cures for diseases.
Larrabee, CUDA and the quest for the free lunch
Opinion – Intel unveiled some key details about its upcoming Larrabee accelerator/discrete graphics architecture earlier this week, sparking speculation how this new technology will stack up to what is already out there in the market.
The Future Looks Bright for Teraflop Computing
Today's GPGPUs are offering a large number of computational cores with a local on-card memory space. A teraflop of commodity computing capability by today's standards is outstanding! In the relatively near future, it is likely that we will see new products and many-core chips from multiple vendors. If your software can transition to utilize these new platforms, the future is bright indeed.Happy teraflop computing!
NVIDIA Recognizes University Of Utah As A Cuda Center Of Excellence
NVIDIA Corporation, the worldwide leader in visual computing technologies, and the University of Utah today announced that the university has been recognized as a CUDA Center of Excellence, a milestone that marks the beginning of a significant partnership between the two organizations.
The processor market is diverging between two paths, the general and the predictable. Where does HPC hitch it’s wagon?
CUDA, Supercomputing for the Masses: Part 6
Astute readers of this series timed the two versions of the reverse array example discussed in Part 4 and Part 5 and were puzzled about how the shared memory version is faster than the global memory version.
Parallel computing with GPUs
Writing highly parallel code is hard, but many of us are going to need to learn to do it in the next few years, since computers are now getting more cores and bigger caches instead of faster clocks. Writing good parallel code for symmetric multi-processor computers with shared memory is hard enough, but when it becomes asymmetric, more than a little art is required.
NVIDIA Accelerates the Search for a Cure
Stanford University's distributed computing program Folding@home has become a major force in researching cures to life-threatening diseases such as cancer, cystic fibrosis, and Parkinson's disease by combining the computing horsepower of millions of processors to simulate protein folding.
NVIDIA Keeps It Interesting
NVIDIA is continuing to push hard on CUDA, the company's C-based software environment for GPU computing. With last month's announcement of the first CUDA Center of Excellence at the University of Illinois at Urbana-Champaign, NVIDIA said it donated half a million dollars to the school.
Going to the Well
Advanced Imaging Pro
"3D visualization has revolutionized the understanding of seismic data, thanks to the performance provided by the GPU," said Jean Bernard Cazeaux, Vice President of the Visualization Sciences Group at Mercury Computer Systems. "GPUs allow much more than visualization; they provide amazing computing capabilities for interactive applications. Mercury has facilitated the interoperability of Open Inventor with NVIDIA's CUDA language, to provide application developers with a unique, integrated solution."
Graphics Chips Help Supercomputers Become Commonplace
The sight of supercomputers in every home and office may soon become a reality thanks to video games such as Grand Theft Auto. High-end 3D games need the fastest graphics chips to run well. This has driven graphics cards makers to build ever-faster cards, and performance from the graphics processor on these cards is hundreds of times faster than the processor in a standard PC.
Applications that have components of sequential and serial processing, such as transcoding digital video from one format to another divide the work between the CPU and the GPU to give about 20 times the performance of just using the CPU alone.
CUDA, Supercomputing for the Masses: Part 5
The local and global memory spaces are not cached which means each memory access to global memory (or local memory) generates an explicit memory access. So what does it cost to access (read or write, for example) each of the different memory types?
Tesla 10 & CUDA 2.0: Technical Analysis & Performance - Page 1
CUDA was announced along with G80 in November 2006, released as a public beta in February 2007, and then finally hit the Version 1.0 milestone in June 2007 along with the launch of the G80-based Tesla solutions for the HPC market. Today, we look at the next stage in the CUDA/Tesla journey: GT200-based solutions, CUDA 2.0, and the overall state of NVIDIA's HPC business.
GPGPUs Make Headway in Bioscience
We're also exploring bioinformatics applications, but the really great thing about the GPGPU and CUDA right now is that post-docs and universities are porting codes and putting them back into the public domain at an incredible rate. This means that the community effort can be used to leverage standard codes without a large investment. Everyone has a GPU, and CUDA can be gotten by just hitting the download button.
More Details on Elemental's GPU Accelerated H.264 Encoder
Elemental's software, if it truly performs the way as seen here, has the potential to be a disruptive force in both the GPU and CPU industries. On the GPU side it would give NVIDIA hardware a significant advantage over AMD's GPUs, and on the CPU side it would upset the balance between NVIDIA and Intel. Video encoding has historically been an area where Intel's CPUs have done very well, but if the fastest video encoder ends up being a NVIDIA GPU -- it could mean that video encoding performance would be microprocessor agnostic, you'd just need a good NVIDIA GPU.
Stanford releases beta Nvidia folding client
The Tech Report
“At last, Stanford University has released a beta version of the GPU2 Folding@home client for Nvidia graphics cards. You can grab the client from this post on the official FAH forums, although Stanford's Adam Beberg suggests users closely read the FAQ page to familiarize themselves with the software first.”
NVIDIA, CUDA and PhysX
“3D card manufacturers shouldn't take this the wrong way, but it takes a lot to make us crawl out of the communal Eurogamer bed (yes, all the Eurogamer writers share a single large bed - we do it for frugality and communality, which remain our watchwords) and go to a hardware presentation. There's a nagging fear someone may talk maths at us and we'd come home clutching the local equivalent of magic beans. And then we'll be laughed at by our fellow writers and made to sleep in the chilly end where the covers are thin and Tom left dubious stains. That's no fun at all.”
Can you feel it?
All of this sounds very familiar to the great cluster disruption. Take a look at the enabling factors list above. Like clusters, the cost to get in the game is minimal. There are over 70 million CUDA enabled GPUs sitting in workstations out there. If you don’t have one, a the cost of a basic GeForce video card was less than $100. As for the software, it is freely available. NVidia, quite wisely, makes the CUDA C compiler available at no cost (and with no registration hassles). It is essentially the same cluster recipe, a low (or no) cost of entry, a possible big pay-off, and some spare time.
NVIDIA's CUDA: The End of the CPU?
CUDA is not a gimmick intended for researchers who want to cajole their university into buying them a GeForce. CUDA is genuinely usable by any programmer who knows C, provided he or she is ready to make a small investment of time and effort to adapt to this new programming paradigm. That effort won’t be wasted provided your algorithms lend themselves to parallelization.
OptiTex to Use NVIDIA's CUDA Technology
"OptiTex' software is an ideal fit for NVIDIA as it leverages the combined personalities of our CUDA enabled GPUs - rich graphics and data intensive computation," said Andy Keane general manager of the GPU Computing business at NVIDIA. "OptiTex' software will deliver new levels of creative freedom for designers."
NVIDIA Looking to Take Computing to the Next Level
“NVIDIA released a new set of GPUs that not only boast a crazy amount of speed, but come with the promise of helping take on a larger set of tasks by delivering a lot more usable horsepower.”
NVIDIA Releases 240-Core Graphics Processor
“Tesla 10 series processor is Nvidia's latest offering for high-performance computing.”
Nvidia and Stanford Finalizing Folding@Home Client for GeForce GPUs
“During Nvidia Editor's Day, we learned that Nvidia and the Folding@Home research group led by Vijay Pande are making final preparation to launch the first version of the Folding@Home client for Nvidia graphics processors.”
Apple Eyeing NVIDIA's CUDA Technology?
“One of the most important performance challenges facing CUDA Apple's Worldwide Developers Conference is expected to cover the parallel tracks of Mac and iPhone software development, but the company may have another aspect of parallelism to discuss.”
CUDA, Supercomputing for the Masses: Part 4
“One of the most important performance challenges facing CUDA (short for "Compute Unified Device Architecture") developers is the best use of local multiprocessor memory resources such as shared memory, constant memory, and registers.”
NVIDIA Processor Has New Niche
Wall Street Journal
CUDA was a breakthrough because it "makes things much, much easier for people developing applications because you no longer have to be a graphics expert," says Steve Briggs, vice president of systems integration at Headwave Inc., a Houston company that makes software that crunches seismic data for the oil-and-gas industry.
OpenCL is a trademark of Apple Inc. used under license to the Khronos Group Inc.
DirectX is a registered trademark of Microsoft Corporation.