5/15/08 Going to the Wall -- Advanced Imaging Magazine
Some jobs are just too big for one person, one company or one technology. In oil and gas exploration, for example, one seismic survey can equal 10 terabytes of data.

4/30/08 Nvidia's David Kirk on CUDA, CPUs and GPUs -- bit-tech.net
David Kirk, Nvidia's Chief Scientist, is an incredibly busy man with an even busier schedule. In the last four weeks, he's been touring some of the top universities in China, Japan and Europe to give guest lectures on how Nvidia's technologies will impact the future of computing—and not just graphics.

4/28/08 Scalable Parallel Programming with CUDA -- ACM Queue magazine
The advent of multicore CPUs and manycore GPUs means that mainstream processor chips are now parallel systems. Furthermore, their parallelism continues to scale with Moore’s law.

4/10/08 Nascentric Announces OmegaSim(TM) GX - the World's First Hardware-Accelerated SPICE Simulator -- Forbes.com
OmegaSim GX harnesses the raw computational power of NVIDIA Graphics Processing Units (GPUs) to provide the highest-performance transistor-level simulation with virtually no loss in accuracy.

4/10/08 Spice accelerator uses nVidia GPU platform -- SCDsource
By rolling out a fast Spice accelerator that uses the massively parallel Tesla GPU platform from nVidia, Nascentric is not only providing a new way to speed analog/mixed-signal simulation.

3/21/08 Nvidia's Supercomputing Effort Wins Fans, Spooks Rivals -- Dow Jones
Gerald Hanweck wants to sniff out the least risky sub- prime borrowers from acres of data. And he's using an enhanced desktop computer for the task, one that is considered laborious for a room full of big server computers.

2/25/08 Nvidia talks up GPU 'supercomputers' -- vnunet.com
Nvidia has claimed that its graphics chips are not just for gaming and watching movies. The company said at a press event in San Francisco that users are harnessing the power of its GPUs in other ways.

2/9/08 CUDA - let the GPU take the strain -- IT PRO
The barracuda is the wolf of the sea, a slim silver dart that hunts in deadly packs. It’s perhaps not surprising that NVIDIA has taken part of its name for its GPU-based supercomputing tools.

2/1/08 Researchers, NVIDIA Collaborate on GPU Petascale Computing -- HPCwire
The combination of CUDA parallel programming tools and NVIDIA Tesla GPU Computing products is driving a fundamental change in the world of scientific computing and delivering unprecedented levels of price performance to research facilities.

1/28/08 PARALLEL PROCESSING WITH CUDA -- Microprocessor Report
Parallel processing on multicore processors is the industry’s biggest software challenge, but the real problem is there are too many solutions—and all require more effort than setting a compiler flag.

1/22/08 Synopsys and Acceleware Deliver Hardware Accelerated Solution for Design of Optoelectronic Devices -- PRNewswire
CAD Sentaurus Device simulation software utilizes the ClusterInABox Quad Q30's built-in NVIDIA graphics processing units (GPUs), which deliver up to two Teraflops of computational power, to significantly accelerate FDTD simulations of optoelectronic devices.

1/21/08 Graphics chips rev up research results -- University of Cambridge
Every serious PC gamer knows what a difference a good graphics card can make to the fun they have. But it is not just hardcore gamers who have recognised the worth of a PC graphics card; increasing numbers of research scientists have woken up to their potential too.

1/4/08 Parting Shots at 2007 -- HPCwire
NVIDIA mounted an aggressive campaign to take the early lead in the nascent GPGPU market. In February, the company launched its CUDA development tools for GPU programming and then in June brought out its spring line of Tesla GPU computing hardware. AMD made some noise with its R600 GPU and is now planning for double precision GPU computing next year with its FireStream Stream Processor and associated SDK. Intel is looking to do a GPGPU end-around with its upcoming "Larrabee" manycore products. Stay tuned; it's going to be a knock down, drag-out fight.

12/31/07 More Chip Stories to Watch - The Channel Wire
Is 2008 the year of accelerators? Examples include FPGA processors, Cell processors and Nvidia's Tesla. The industry has been sniffing around this issue for years. Intel's QuickAssist and AMD's Torrenza initiatives are vying for the industry standard.

12/21/07 The insideHPC Top Five Stories for 2007 -- HPCwire
NVIDIA was much on the minds of our readers as the company moved to build a new market for its legendary graphics cards. They aimed at the HPC market not only with some tweaked GPUs, but they also took a page from ClearSpeed's playbook by introducing an API (CUDA) to allow HPC users to get at all that processing power without contorting scientific algorithms into constructs better suited for textures and pixel shading.

12/14/07 NVIDIA Tesla wins PC Magazine Technical Excellence Award -- GPGPU
NVIDIA's new Tesla GPU Computing line of GPUs have won a PC Magazine Technical Excellence Award in the Component category. From the PC Magazine article: "Sure, you know GPUs, but have you heard of GPGPUs? The concept is simple: Use the massively parallel architecture of the graphics processor for general-purpose computing tasks. Because of that parallelism, ordinary calculations can be dramatically sped up. To create the Tesla, its powerful new entry into this market, nVidia has bundled multiple GPUs (without video connectors!) into either a board or a desk-side box that offers near-supercomputer levels of single-precision floating-point operations. The general-purpose GPU (thus the acronym GPGPU) is being used as a high-performance coprocessor for climate modeling, oil and gas exploration, and other applications—and it's much cheaper than a supercomputer. The Tesla even comes complete with its own C compiler and tools."

12/11/07 HP plots path to server accelerator madness in '08 - The Register
The vendor has fired up talks with AMD/ATI and Nvidia around its Tesla systems to see what makes sense from a resale perspective. Customers can, for example, take a single GPGPU card and slot it into existing systems in order to speed up certain types of software that runs better on the graphics chips' numerous engines than on dual- or quad-core x86 chips. Or you can go the Tesla route and buy a deskside or rack unit with numerous GPUs installed to get a super-charged speed-up.

12/6/07 Playing or processing? -- The Economist Technology Quarterly
The idea of using graphics chips for more general-purpose computing has been around for years, but only recently have the chips become sophisticated enough for it to work in practice. Both Nvidia and AMD, the world's largest graphics-card manufacturers, have decided that GPU computing could be a big opportunity. Nvidia has released a product line designed specifically for non-graphics applications, and a specialised programming language for use with it.

12/4/07 Pixels to PetaFLOPS - Today’s HPC Clusters
CUDA is very interesting because NVIDIA created a new model for programming general purpose computations on GPUs. CUDA is data parallel computing, using thousands of threads with a Parallel Data Cache to help increase arithmetic intensity for large performance boosts (arithmetic intensity refers to the compute intensity of the code). With CUDA, you can program in C and then use extensions to program for the GPUs. This feature allows you to target certain portions of the code for execution on the GPU and the rest to run on the CPU.

12/4/07 The 24th Annual Technical Excellence Awards -- PC Magazine
Sure, you know GPUs, but have you heard of GPGPUs? The concept is simple: Use the massively parallel architecture of the graphics processor for general-purpose computing tasks. Because of that parallelism, ordinary calculations can be dramatically sped up. To create the Tesla, its powerful new entry into this market, nVidia has bundled multiple GPUs (without video connectors!) into either a board or a desk-side box that offers near-supercomputer levels of single-precision floating-point operations. The general-purpose GPU (thus the acronym GPGPU) is being used as a high-performance coprocessor for climate modeling, oil and gas exploration, and other applications—and it's much cheaper than a supercomputer. The Tesla even comes complete with its own C compiler and tools.

11/30/07 HPC: A New Power Base in Europe -- Scientific Computing World
David Robson explores the latest initiatives driving the development of high-performance computing in Europe.

11/30/07 The Future Looks Bright for Teraflop Computing -- Scientific Computing
Amazing power in the lab is feasible right now — and for a bargain price — but programming is required.

11/27/07 New Collaboration Helps the Oil Industry Harness HPC -- Scientific Computing
Mercury Computer Systems and NVIDIA are to collaborate to provide oil exploration and production developers with a comprehensive solution.

11/23/07 SW Development Kit Turns GPUs into Supercomputers -- POPULAR SCIENCE RECOGNIZES NVIDIA CUDA - Chip Design
Popular Science has announced that the NVIDIA® CUDA™ C-compiler and software development kit (SDK) has been recognized as one of the top 100 innovations of the year, winning the coveted “Best of What’s New” award.

11/20/07 GPGPUs and FPGAs are Now Fully Implanted in Our Brains - Channel Register
SC07 One topic - even more so than cheap shrimp - dominated this year's Supercomputing conference in Reno: Accelerators.

11/15/07 NVIDIA Unveils New Version of CUDA Software Development Tools - Hardware Zone
NVIDIA is demonstrating the latest version of its award winning C-compiler for GPU programming, CUDA 1.1, at the SuperComputing 2007 show.

11/14/07 Popular Science Recognizes NVIDIA CUDA - [H]Enthusiast
Popular Science has announced that the NVIDIA® CUDA™ C-compiler and software development kit (SDK) has been recognized as one of the Top 100 innovations of the year, winning the coveted "Best of What's New" award.

11/14/07 NVIDIA Unveils New Version of Award-Winning CUDA Software Development Tools - Embedded Computing Design
NVIDIA is demonstrating the latest version of its award-winning C-compiler for GPU programming, CUDA™ 1.1, at the SuperComputing 2007 show.

11/14/07 NVIDIA Unveils CUDA 1.1, Universities Adopt for Education - InsideHPC.com
SC07: NVIDIA has announced a new version of its CUDA API for harnessing the power of GPU’s in computation.

11/14/07 NVIDIA announces CUDA 1.1 - The Tech Report
NVIDIA has unleashed version 1.1 of CUDA, bringing additions like support for 64-bit versions of Windows XP and extra examples of source code that takes advantage of multi-GPU systems.

11/13/07 Top Schools Adopt NVIDIA CUDA for Parallel Programming Courses - EDN
As the computing industry rapidly moves to multi-core and parallel processing architectures, tomorrow’s software engineer must be educated on the best tools and methodologies for parallel computing. NVIDIA announced today that the CUDA software environment is now being actively used in parallel programming courses at over 20 universities worldwide with many more currently evaluating NVIDIA’s tools for parallel programming for inclusion in their curriculum.

11/13/07 NVIDIA GPU Computing Solutions Recognized by HPC Community - TackTech
HPCwire, the most recognized and accessed news and information site covering the high performance computing (HPC) ecosystem, recognized NVIDIA today with three Readers' and Editors' Choice awards for its Tesla™ line of GPU computing solutions and its CUDA C-compiler and software development kit (SDK).

08/17/07 Nvidia CUDA: Practical Uses - BeHardware
Since our first analysis of CUDA, various elements have evolved. Nvidia has launched a special line of devoted products and the API has improved. We had the opportunity to talk with the main people involved with this technology and were able to test what GPUs are capable of compared to CPUs in a practical application.