Articles

21/7/2011
VR-Zone
NVIDIA Tesla Success Stories
Furthermore, with GPUs in large-scale server clusters, new classes of problems can be addressed for which the necessary computing power was only a dream a year ago.

19/7/2011
HPCwire
New Cornell Collaboration to Explore GPU Computing Using MATLAB
Cornell is conducting this research on Dell C6100 servers with the C410x PCIe expansion chassis, which supports server connections to NVIDIA Tesla M2070 GPUs.

“The launch of this GPU capability with eight nodes (each with eight CPU cores) and eight NVIDIA Tesla M2070 GPUs (each with 448 CUDA cores) is extremely valuable particularly for researchers needing to process large blocks of data in parallel,” said David Lifka, Cornell CAC director.

14/7/2011
HPCwire
GPU Computing Wades Into the Mainstream
The idea that the most successful technologies become invisible doesn't yet apply to GPU computing, but it's getting there. This week there were a handful of major HPC system announcements based on GPU-equipped platforms, but you wouldn't have know that from the headlines. No longer the interloper in high performance computing, GPUs are beginning to fade into the background, just like every other mainstream HPC technology.

7/7/2011
Drug Discovery & Development Magazine
GPU Computing Brings Drug Discovery Up to Speed
A combination of advanced technology and close scientific interactions with collaboration members— including Abbott Labs and Pfizer—culminated in the release of a GPU-based implementation of the core 3D shape similarity algorithm used in the original Abbott paper. As a result, a single computer equipped with four NVIDIA Tesla cards is capable of screening over 2 million molecule conformations per second, enabling real-time 3D shape similarity for use in tools like Lead Hopper.

1/7/2011
Miltary & Aerospace Electronics
High-performance computing benefits signal- and data processing in aerospace and defense applications
“This is the data deluge,” Gupta quips. “Traditional technologies just don’t cut it; they aren’t fast enough. All this processing requires a much higher-performance computing solution. This is where the GPU comes in and accelerates all this processing, whether video, image, or signal data. A lot of mil-aero domains are extremely computationally hungry and HPC is needed.”

UAVs continue to shrink in size, weight, and power (SWaP), yet “the problem with [compact and lightweight vehicles] is they are so small that they get jerked around in the wind a lot and the video they acquire is extremely shaky,” Gupta explains. “It is really hard to determine what is happening.” Ikena software from MotionDSP in Burlingame, Calif., performs real-time video stabilization, so it corrects the video and makes it steady. “They could only do this using GPU technology; they just couldn’t do it with traditional processors,” Gupta says

23/6/2011
eWeek
Nvidia Moves From Gamers to Gunners With Intelligence, Defense Apps
The technology behind all of this is built into NVidia’s Tesla M2090 GPU Computing Modules, which are already being used in a variety of applications. The difference is that now the Tesla modules are being put into helmets and Humvees, drones, manned aircraft and into other things the intelligence community really doesn’t want us to know about. The result has been a remarkable transformation in remote imaging and remote sensing.

14/6/2011
Digital Manufacturing Report
Making Digital Manufacturing Affordable: A Vendor Perspective
Says Gupta, "As soon as software products migrate off the desktop, they start to become prohibitively expensive for small business users. For HPC to truly make inroads into the SMMs it has to be easily available — and the best way to make this happen is through an affordable desktop machine. Not every office has an HPC cluster; but every office does have a desktop system." He points out that these new affordable workstations are not only powered by multicore CPUs and GPUs, but the software has also evolved to take advantage of this parallel computing capability in the workstations.

9/6/2011
HPCwire
Top 10 Objections to GPU Computing Reconsidered
CUDA is an extension to C and relatively easily picked up by experienced coders. The model for parallel programming that will take us to the exascale is far from settled, however I believe that the eventual solution will look more like the data parallel CUDA model than the task parallel CPU alternatives. In previous HPCwire contributions I have expressed the opinion that CUDA, by forcing developers to consider the irreducible level of parallel work in their problems and mapping that to threads, is a better programming model for extensible parallelism, lending itself more naturally to scalability across multiple GPUs on a single node and across multiple nodes.

9/6/2011
insideHPC
Interview: GPUs Accelerate China’s Solar Energy Research
When the Tianhe-1A system took the top spot on the TOP500 last year, there seemed to be a lot punditry that the system wouldn’t scale on real applications. Well, put that notion to rest because researchers at the Chinese Academy of Sciences’ Institute of Process Engineering have completed the world’s highest performing molecular simulation to examine improved techniques for more efficient production and use of crystalline silicon, a key material used in solar panels and the semiconductor industry.

8/6/2011
HPCwire
Appro Comes Up Multi-Million Dollar Winner in HPC Procurement for NNSA
They'll be some GPUs in the mix as well. All three labs have expressed an interest in accelerators for some of these clusters. Initially though, only Los Alamos will be installing such a system, in this case, a 324-node cluster, equipped with 648 of the latest NVIDIA Tesla M2090 GPUs. That's just for starters; Los Alamos is also hoping to purchase a GPU-cluster about twice that size. The three labs are also interested in Intel's forthcoming "Knights Corner" accelerators, but they are not in the deliverables on any planned systems at this point, says Lee.

27/5/2011
Enterprise Efficiency
GPUs: Just the Ticket to Reduce Datacenter Power Bills
At the hardware level, Nvidia's GPUs are much more power-efficient than a CPU on a per-cycle basis. CPU cycles are like car engine RPMs. If you can get RPMs for less gas, and that translates to higher gas mileage. The same applies for GPUs. After getting beat up over its power-consuming video cards a few years back, Nvidia replied with a renewed emphasis on power efficiency in recent years.

GPUs have hundreds of cores, as opposed to four or eight in a CPU, and they are highly tuned to perform mathematical computations in parallel. If you've got a big processing job with lots of calculations, that's precisely the architecture you want.

24/5/2011
HPCwire
Cray Unveils Its First GPU Supercomputer
“We're not first to the party here, but we're hoping we're the best dancer," he added.”

14/4/2011
Waters Technology
Fuzzy Logix Unveils Tanay ZXnW Series Appliance
According to Partha Sen, CEO of Fuzzy Logix, “The driving force behind the introduction of Tanay ZXnW Series is to provide a platform where people can instantly take advantage of algorithms accelerated on the GPU. We are very excited to launch this product, and we expect that this appliance will bring tremendous value to our customers

6/4/2011
HPCwire
Microway's BioStack-LS Cluster Named 2011 Best of Show Winner in IT Hardware & Infrastructure at Bio-IT World Conference
The Microway BioStack-LS is a modular, extensible cluster for life science researchers. It provides dense compute power that's easy to use. With over 15 teraflops of InfiniBand-connected computing power spread over 6272 Nvidia Tesla GPU cores and 84 Intel Xeon CPU cores, the BioStack-LS provides performance vastly superior to traditional compute clusters. To suit life science customer needs, all Microway GPU-based clusters are delivered fully tested, integrated, and ready to run NVIDIA's Bio WorkBench applications with the latest CUDA environment.

31/3/2011
HPC Wire
SDSC's Ross Walker Wins Outstanding Junior Faculty Award
The work we are doing in the Walker Molecular Dynamics Lab at SDSC to develop GPU accelerated software promises to transform the way in which scientists approach applying molecular dynamics techniques to the understanding of enzymatic pathways, and ultimately the design of new drugs and biological catalysts

31/3/2011
SciCasts
Researchers Make The Leap to Whole-cell Simulations
Researchers have built a computer model of the crowded interior of a bacterial cell that – in a test of its response to sugar in its environment – accurately simulates the behavior of living cells. The new "in silico cells" are the result of a collaboration between experimental scientists at the Max Planck Institute of Biology in Germany and theoretical scientists at the University of Illinois using the newest GPU (graphics processing unit) computing technology.

March 2011
COTS Journal
GPGPU Computing Carves Out New Military System Design Territory
Graphics processors used as general purpose processors are the latest disruptive technology to invade military embedded computing. Powerful and dense processing combined with easy programming give it a decided edge over traditional signal processing approaches.

March 2011
COTS Journal
Carrier Landing Modeling System Leverages GPGPU Advantages
During Phase I of the program—which was designed to be a proof of concept—compute time of a solver for the Euler equations was reduced from 18 hours to 20 minutes, resulting in a 54x improvement. While this level of performance gain is quite impressive, the challenge for the project’s next phase is to deal with computations that can take up to 150,000 CPU hours to run. According to Humphrey, in Phase II they will build on this prototype to create a full solver that will target both desktop users with GPU coprocessors as well as large GPU clusters meant for running the most difficult simulations.

1/3/11
Scientific American
Star (Finding) Power: Einstein@Home Taps Donated PC Graphics Processors to Uncover a Second Pulsar
Working with leading GPU maker NVIDIA Corp., Allen and his team have improved Einstein@Home software so that it can use GPUs more efficiently. "The detection of gravitational waves from new neutron stars using LIGO data will be a combination of increasingly sensitive LIGO instruments and an increase in the use of GPUs," Allen says.

February 2011
Bio-IT World
HPC, GPUs and Cloud: A Perfect Match?
Bioscience has been one of the most profoundly affected segments by the parallel processing capabilities of GPUs. Many important codes in this segment, such as AMBER, map elegantly to the architecture, and achieve speed increases, in some cases, many times faster than their earlier CPU-bound versions.

From an HPC perspective, GPUs may be a very silver lining to cloud adoption, especially for life science applications like molecular modeling and genome sequence searching.

21/1/11
Machine Vision Online
MVTec Improves Factory Throughput and Quality using NVIDIA GPU-Accelerated Inspection Automation
"Product inspection machines are integral to factory automation today," says Dr. Wolfgang Eckstein, MVTec’s managing director. "By increasing the inspection speed using NVIDIA GPUs, HALCON 10 enables our customers to increase factory throughput and also leads to higher quality assurance."

20/1/11
HPCwire
Finally, AMD needs to swallow its pride and develop a CUDA port for its graphics chips. That doesn't mean it has to drop its long-term commitment on OpenCL. It just needs to recognize that CUDA is currently the de facto API for GPU computing, especially for HPC, and is likely to remain so for at least the near term. Adopting CUDA would go a long way to level the playing field in GPU computing as well as give its larger rival, Intel, something to think about.

14/1/11
CTO Edge
The Coming Graphics in the Cloud Revolution
What’s about to change, however, is that access to graphical processing units (GPUs) is about to get a whole lot less expensive thanks to cloud computing services. What that means, says Sumit Gupta, who heads up product management and marketing for NVIDIA Tesla products, is that mainstream enterprise software, such as business intelligence applications, will be embedding visually-oriented analytics that will be processed in the cloud.

7/1/11
Scientific Computing
Redefining What’s Possible
From personal experience, current GPGPU flop rates meet or exceed the computational capability to which I had access as a scientist in the theoretical division at Los Alamos National Laboratory in the late 1990s. In addition, the machines I used were shared with other users, while current GPGPUs are inexpensive enough to be dedicated for use by a single individual. Installing four high-end GPUs in a workstation can create a machine with a peak flop rate comparable to the large MPP2 supercomputer that Pacific Northwest National Laboratory (PNNL) made available to users just a few years ago.

7/1/11
HPCwire Soundbite
NVIDIA Announces CPU-GPU Strategy
"This is a sound move for NVIDIA in the long term"
"It establishes NVIDIA not just as a graphics company but a computing company"

December 2010
O’Reilly Media
New Year's Watchlist: The Rise of the GPU
Our ability to create data is outstripping our ability to compute with it. For a number of years, a subculture of data scientists has been using high-performance graphics cards as computational tools, whether or not they need graphics. The computational capabilities that are used for rendering graphics are equally useful for general vector computing. That trend is quickly becoming mainstream, as more and more industries find that they need the ability to process large amounts of data in real time ("real" real time, not web time): finance, biotech, robotics, and almost anything that requires real-time results from large amounts of data.

Amazon's decision to provide GPU-enabled EC2 instances ("Cluster GPU Instances") validates the GPU trend. You won't get the processing power you need at a price you want just by enabling traditional multicore CPUs; you need the dedicated computational units that GPUs provide.

17/12/2010
HPCwire Soundbite
Top HPC Trends in 2010; Seeds Planted for 2011
“This year, it (GPU Computing) hit the mainstream, deployed by all the major vendors. Many major ISVs.”

“If NVIDIA hadn’t been there, this wouldn’t have happened. AMD was only lukewarm about this. NVIDIA put energy and money into it. They changed the trajectory of GPU computing, without a doubt. NVIDIA CUDA made this possible.”

13/12/10
O’Reilly Radar
Strata Gems: Use GPUs to speed up calculation
While debate is ongoing about the exact range of performance boost available by using GPUs, reports indicate that speedups over CPUs from 2.5 to 15x can be obtained for calculation-heavy applications. NVIDIA has led the trend for general purpose computing on GPUs with the CUDA. By using extensions to the C programming language, developers can write code that executes on the GPU, mixed in with code running on the CPU.

7/12/10
Real World Technology
Introduction to OpenCL
Of all the different vendors, NVIDIA’s support (of OpenCL) is by far the most full featured and robust, since it leverages their existing investment in CUDA

3/12/10
Smart Planet
What the DoD’s PlayStation-powered Condor Cluster means for the future of supercomputing
“By using the cell processors in the PS3s and the GPGPUs in unison, we've produced a system that does a very good job at handling this kind of [surveillance] information. We've developed the most powerful heterogeneous supercomputer in the world for a fraction of the cost of building it using individual chips and servers." – Mark Barnell, Air Force Research Laboratory HPC director.

4/10/10
insideHPC
Interview: MATLAB Support for GPUs a Game-Changer
So if you want to go from doing something on the desktop talking to one GPU, I can show you how to do it with four GPUs or on the cluster and there is no code change. That’s one of the things getting back to what we have designed our products for; we care a lot about the engineer who doesn’t want to get into the details here.

22/9/10
ZDNET
GTC: A call to (parallel) arms
It also means that there is a way to take advantage of all that processing power, that it is possible to take real-world problems, extract the underlying parallelism, and turn it into code. Some of it is NVIDIA’s CUDA programing model at work, but much of it is new parallel implementations of familiar mathematical libraries. Scientific programmers can take the tools they’re familiar with, and quickly speed them up – 10x, 50x, even 500x.

21/9/10
PC World
High-Performance Computing Rules at GPU Tech Conference 2010
If you’re into high performance computing, there’s some impressive stuff to be seen.

21/9/10
HPCwire
GPGPU Finds Its Groove in HPC
After just four years since the introduction of commercial-grade GPU computing, the technology has become firmly established and is poised to spill out across every application domain that has a need for data-parallel computing.

10/9/10
insideHPC
Crisis in HPC: Will America be Left Behind?
To sustain and extend our lead in High Performance Computing, we don’t have to revive the decades-old debate about industrial policy and the government picking winners through massive bets on industry sectors. We just need to spend smarter to get cost-effective hybrid HPC on the national agenda, and equip our best minds with the computing capacity they need to innovate and create jobs.

10/6/10
CIO
Gaming Chips Score in Data Centers
One oil-and-gas exploration firm replaced their 2,000-CPU cluster with a 32-GPU cluster, delivering the same performance but requiring less than 4 percent of same volume and 4 percent of the same energy as the company's previous system. In total, GPUs could perform on par with the previous system but at 1/20th the cost.

9/6/10
Harvard School of Engineering & Applied Sciences
Harvard…..Where no CPU is Safe!
"When I joined Harvard three years ago, I was immediately struck by the amazing science research going on," he says. "It then turned out that GPU computing was the right approach for many of the projects. This was after NVIDIA had introduced CUDA, which was a huge game-changer for the whole GPU computing community. All of a sudden it was much easier to use GPUs for scientific applications, and performance and productivity increased dramatically."

7/6/10
insideHPC
Video: Why is Everyone Talking About GPUs for HPC?
I think that NVIDIA was a big winner this year at ISC, and it wasn’t just because China’s new Tesla-powered Nebulae Supercomputer came in at number 2 on the TOP500. The reason for me was rapid adoption; I visited at least half a dozen booths that featured the latest NVIDIA GPUs in a variety of configurations. Clearly, the company is getting traction in the market.

19/5/10
insideHPC
NVIDIA Inside New Servers
This is a big step for NVIDIA and GPU computing as a whole. IBM has been inventing technologies for the supercomputing community for quite some time. NVIDIA has landed a serious OEM partner. You now have the biggest name in GPU computing married with [arguably] the biggest name in computing. This could be huge, for NVIDIA and the consumer.

18/5/10
ComputerWorld
IBM Updates iDataPlex server with NVIDIA GPUs
There is increased interest in hybrid computing systems that use graphics processors along with CPUs, with many companies preparing to deploy such systems, Turek said. Some of IBM's clients have been testing hybrid servers combining CPUs and GPUs over the last two years and are ready to put them into production, he said.

18/5/10
GigaOm
NVIDIA Shows Off Its Survival Skills with IBM Win
However, the announcement that IBM has turned to Nvidia GPUs after it stopped producing its own specialty parallel processor also offers a guide on how to succeed in the data center.

29/4/10
GenomeWeb
GPU-Powered AMBER 11
"With GPUs, we can now do most of our work at the desktop and that changes everything. Any research department looking to invest in computing resources to run AMBER should start by equipping every researcher with GPU-enabled workstations," Ross Walker says.

22/3/10
HPCWire
NVIDIA Shifts CUDA Into Third Gear
Fortunately for NVIDIA, they have a running start. Downloads for CUDA Toolkits 2.0, 2.1 and 2.2 leveled off between 80,000 to 120,000. But CUDA 2.3, introduced in July, has already hit 160,000 downloads and is adding new users at a clip 20,000 per month, with no sign of leveling off. Russell attributes this to a number of factors, including the right mix of software features as well as the aggressive outreach to GPGPU developers and partners. Supporting the latter point, CUDA is now taught in over 300 universities worldwide.

22/3/10
Bright Side of News
Without any doubt, NVIDIA Corporation is [currently] the market leader of GPGPU installed user base. The investment company makes in GPGPU is much more than a marketing effort - the company now has more software than hardware engineers, creating a widespread GPGPU ecosystem which includes independent developers, large institutions, universities and many more....All in all, CUDA Toolkit 3.0 looks like a very comprehensive suite for development of GPU-accelerated applications.

11/3/10
Smart Planet
With Nvidia Tesla graphics chips, doctors reduce time to diagnose breast cancer by 4 hours
A Salt Lake City, Utah-based medical device company is using Nvidia Tesla graphics chips to reduce the amount of time it takes to get breast imaging results into the hands of doctors by more than four hours.

10/3/10
Bio-IT World
Graphics Card Maker Turns to High-Performance Bioinformatics
The number of [life science] algorithms that are available to run on GPUs is rather impressive. On the sequence analysis side, BLASTP, HMMer, Smith-Waterman, MUMmerGPU, ClustalW, MEME, and Infernal are all available for download. For those interested in docking, algorithms such as autodock and piper have shown impressive speedups of 10 to 16 times in tests.

9/3/10
The Register
Yellow Dog Linux licks CUDA
Nvidia is ramping up its "Fermi" GPU co-processor line right now, so tweaking Yellow Dog to better support Nvidia's GPUs when used as math units for central processors seems like a logical enough choice. Fixstars is not the first company to embed and support the CUDA programming environment, which simplifies the way compilers and operating systems on PCs and servers dispatch work to GPUs in their own product. Grid computing expert Platform Computing announced last August that it was embedding CUDA into its Platform Cluster Manager and HPC Workgroup Manager tools for managing grids.

8/3/10
Desktop Engineering
Bringing GPU Power to Bear on Engineering Computations
If, over the next few years, your MATLAB code ends up running on NVIDIA GPUs, chances are it will be using AccelerEyes Jacket to do so. It will be under the covers, so you likely won’t know that it’s there, but you’ll see the results in faster execution of your analyses and simulations.

2/3/10
HPCWire
Fixstars Launches Linux for CUDA
Multicore software specialist Fixstars Corporation has released Yellow Dog Enterprise Linux (YDEL) for CUDA, the first commercial Linux distribution for GPU computing. The OS is aimed at HPC customers using NVIDIA GPU hardware to accelerate their vanilla Linux clusters, and is designed to lower the overall cost of system deployment, the idea being to bring these still-exotic systems into the mainstream.

24/2/10
Directions Magazine
Why Geospatial Users and Developers Should Know Their GPU from their CPU
Manifold is not the only GIS company taking advantage of Nvidia's GPUs; PCI Geomatics and DigitalGlobe (press release) have, as well. For a GIS project, the difference in processing speed between a day and an hour is huge. For satellite data, freshest is best, so speeding the time from capture to customer makes more money. There are defense players exploring using GPUs for geospatial work, too.

22/2/10
HPC Projects
HPC to Bounce Back in 2010: IDC Market Predictions
X86 processors will dominate but GPGPUs will gain traction as x86 hits the wall - In the past decade, x86 processors went from 'near zero' to 'hero' in the HPC space, largely replacing RISC machines. And while they will continue to dominate, GPGPUs are starting to make strong headway and are seeing some large-scale deployments.

17/2/10
Linux Magazine
The Cost to Play: CUDA Programming
The rapid uptake of CUDA applications by programmers was no accident. NVidia did an excellent job making CUDA accessible and promoting the toolkit. There are other less obvious factors that, in my opinion, made CUDA a rapid success.

15/2/10
HPC Wire
Aalborg University in Denmark Taps Jacket
Jacket delivers GPU computing power to domain professionals that have little to no CUDA programming background and would prefer to delay or eliminate parallel programming or low level programming languages like C and C++. It enables faster prototyping and problem solving across a range of signal processing -- as well as financial, scientific, and engineering -- applications. Jacket eliminates the need to re-program applications into complex languages which would otherwise require advanced programming knowledge and months to complete.

4/2/10
PC Magazine
Nvidia's CUDA Technology Not Just for Geeks
In total, there have been about 500,000 downloads of the CUDA software, said Dan Vivoli, a senior vice president of Nvidia. "CPU cycles are now GPU cycles," Vivoli said, referring to the shift in how some software is processed.
Quietly, those companies taking that approach are now not only academic or academically-focused companies, but more mainstream applications. [This article] is a short summary of how each of the partners Nvidia invited are using CUDA.

2/2/10
VizWorld
Accelerating 3D Seismic Data Analysis On Desktop Workstations
“We are measuring speedups from two hours to two minutes using CUDA and the Tesla C1060,” says James Allison, president of OpenGeoSolutions. “This kind of performance increase is totally unprecedented and in a market where there is great economic value in being able to determine these fine sub-surface details, this is a game changer.”

29/1/10
Dr. Dobbs Journal
Text for Teaching Parallel Programming Concepts
Through this text (Programming Massively Parallel Processors by Dr. David Kirk and Dr. Wen-mei Hwu), students learn to effectively program massively parallel processors using real-world case studies and actual software development tools -- CUDA and OpenCL. Students also develop computational techniques that enable them to think about problems that are amenable to high-performance parallel computing.

29/1/10
Extremetech
Will Nvidia's Fermi Architecture Bring Movie-Quality 3D to Your PC?
Nvidia's new Fermi GPU architecture may represent a radical change to video hardware that could dramatically impact both gamers and programmers

15/1/10
BioInform
Eyeing a Growing Market, Nvidia Launches Portal to Aggregate GPU-Enabled Life Science Applications
The new portal will help researchers learn how GPU-enhanced software packages "can enable them to work faster or more efficiently, and to be able to do things that were previously impractical due to computational limitations of existing hardware platforms," John Stone, a NAMD (Nanoscale Molecular Dynamics) co-developer, told BioInform

15/12/09
Hexus
Kaspersky works with NVIDIA on GPU virus busting
The firm believes that by using an NVIDIA Tesla S1070 1U GPU system to accelerate the screening of malicious software - using a file similarity detection technology - the entire process can be speeded up some 360 times when compared to doing the same work on a Core2 Duo running at 2.6 GHz.

23/11/09
HPCWire
A pervasive GPU Computing Strategy
NVIDIA is continuing its campaign to nudge the CPU from its dominant position at the center of the computing universe. A trio of announcements this week provides a rough outline of how the company intends to expand its GPU computing footprint.

20/11/09
The Register
Nvidia previews next-gen Fermi GPUs
Graphics chip maker and soon-to-be big-time HPC player Nvidia raised the curtain a little higher on its next-generation of graphics co-processors at the SC09 supercomputing trade show in Portland, Oregon, this week, and it is arguable that the GPU co-processors aimed at personal supers and massive clusters alike were the star of the show.

18/11/09
HPCWire
NVIDIA, Mellanox Increase Cluster Performance
NVIDIA Corporation and Mellanox Technologies Ltd. today introduced new software that will increase cluster application performance by as much as 30 percent by reducing the latency that occurs when communicating over Mellanox InfiniBand to servers equipped with NVIDIA Tesla GPUs.

18/11/09
HPCWire on YouTube
[Video] NVIDIA @ SC09
Andy Keane, General Manager for the Tesla GPU Computing Business Unit at NVIDIA discusses what NVIDIA is showing this week (November 2009) at SC09.  

17/11/09
HPCWire
NVIDIA, Partners Form Parallel Computing Development Ecosystem
NVIDIA and its ecosystem partners will deliver, over the next few months, the industry's broadest set of software releases to developers using GPU computing in their work.

11/11/09
Extremetech
Ubiquitous 3D: Nvidia's RealityServer
[Video: http://www.youtube.com/watch?v=Q-I58PPMPfs&feature=player_embedded]
By moving the CPU-crushing rendering requirements of creating high-resolution images and animations off of the client and onto a back-end computer, Nvidia hopes to bring complex graphics applications like fluid dynamics, architectural design, real-time product styling and design, 3D video games, to computing platforms that don't have the processing power to run them locally. RealityServer could mean the transformation of the Web and its applications into a 3D world complete with photorealistic ray-traced images and high-resolution animations that can be scrolled, rotated, and painted in real time.

9/11/09
insideHPC
NVIDIA Adds UTK as CUDA Center of Excellence
NVIDIA announced this morning that they have recognized the University of Tennessee, Knoxville’s [UTK] Innovative Computing Laboratory [ICL] as a CUDA Center of Excellence.  They made special note of UTK/ICL’s adoption of the CUDA programming model into its curriculum as well as its work in developing linear algebra libraries for use in HPC.  UTK joins a select group of seven other universities and research organizations that include Harvard, Cambridge and the National Taiwan University.

28/10/09
HPCWire
Chinese Academy of Sciences and Tsinghua University Named CUDA Centers of Excellence
They join an elite list of five other universities as CUDA Centers of Excellence, including: Harvard University, University of Illinois at Urbana-Champaign and University of Utah, in the US; Cambridge University, in the UK; and National Taiwan University, in Taiwan. Additionally, more than 250 other universities around the world teach the CUDA C programming model.

12/10/09
insideHPC
MSC adds support for Tesla GPUs to FEA software
“Our customers will achieve new levels of simulation fidelity and product innovation using this breakthrough technology,” said Ash Munshi, CEO of MSC.Software. “This successful collaboration with NVIDIA is the beginning of an alliance that will ultimately add value across a broad range of simulation products from MSC.Software.”

06/10/2009 Podcast: NVIDIA GPU Technology Conference Recap; Impact of "Fermi" on HPC Landscape
NVIDIA is doing everything right on a technology standpoint.

02/10/2009 NVIDIA and "Starting the Next Age of Personal Computing"
We are at the forefront of another massive change in the computer industry.

30/09/2009 NVIDIA's Next Generation GPU Architecture has a lot for HPC to Love
(Oakridge) That's a pretty awesome announcement for a design that isn't even a product yet.

30/09/2009 NVIDIA Fermi Next Generation GPU Architecture Overview
NVIDIA refers to Fermi as the most significant leap forward in GPU architecture since the original G80 and after reading through the documentation, it is hard to argue against their case.

30/09/2009 NVIDIA's 'Fermi' GPU Architecture Revealed
For many corners of the GPU computing world, though, Fermi may be well worth the wait, thanks to its likely superiority in terms of double-precision compute performance, memory bandwidth, caching, and ECC support along with a combination of hardware hooks and software tools that should give Fermi unprecedented programmability for a GPU.

30/09/2009 NVIDIA GT300's Fermi Architecture Unveiled: 512 Cores, Up To 6GB GDDR5
If you had any doubt that computational GPU movement is not real and that CPU is the only way to go for HPC, wake up and smell the coffee.

30/09/2009 NVIDIA Takes GPU Computing to the Next Level
GPU Computing 2.0 is upon us. At the NVIDIA GPU Technology Conference in San Jose, Calif., company CEO Jen-Hsun Huang unveiled a seriously revamped graphics processor architecture representing the biggest step forward for general-purpose GPU computing since the introduction of CUDA in 2006. The stated goal behind the new architecture is two-fold: to significantly boost GPU computing performance and to expand the application range of the graphics processor.

30/09/2009 Nvidia's 'Fermi' GPU Architecture Revealed
                  GPU computing grabs center stage
Graphics processors have been at the center of an ongoing conversation about the future of computing. Nvidia has chosen to reveal the first information about its next-generation GPU architecture at the opening of its GPU Technology Conference. That architecture, code-named Fermi, has a number of computing features never before seen in a GPU.

28/09/2009 NVIDIA Collaborates with Microsoft on GPU Computing
NVIDIA has announced recent work with Microsoft to promote NVIDIA Tesla GPU computing systems using the Windows HPC Server 2008 operating system.

28/09/2009 Nvidia Teams Up with Microsoft for HPC
Nvidia is to work with Microsoft to use its Tesla GPUs for high performance parallel computing using the Windows HPC Server 2008 operating system.

24/09/2009 Bloomberg Uses GPUs to Speed Up Bond Pricing
Two-factor model for calculating hard-to-price asset-backed securities now runs on graphics processing units paired with Linux servers.

23/09/2009 Bloomberg Begins Using Graphics Processors to Calculate Bond Prices
Bloomberg said it had become the first major supplier of market data to commit to and begin using graphical processing units, to speed up the calculation of security prices.

15/09/2009 Eight Ways GPUs Boost HPC
Graphic processing units are finding a greater mainstream computing role. GPUs are cropping up in coprocessing roles in workstations, as well as HPC (high-performance computing) offerings.

02/09/2009 Reliable Memory: Coming to a GPU Near You
GPUs are becoming more like CPUs. But in the critical area of error corrected memory, graphics hardware still lags. The lack of error correction is probably the single biggest factor that makes users of GPUs for high performance computing nervous. The good news is that graphics chip vendors are aware of the problem and it appears to be only a matter of time before GPUs get a memory makeover.

01/09/2009 Why Graphics Processors will Transform Database Processing
The history of technology is full of breakthroughs in one field that wound up working wonders in a related one. Now add another tech crossover: The graphics coprocessor, invented in the 1970s to churn through voluminous and repetitive calculations and render smooth and realistic-looking images on computer screens, can now chew on large-scale databases.

31/08/2009 Mission Possible -- Greening the HPC Data Center
With power bills at supercomputing centers around the world running into the tens of million dollars annually and planned upgrades moving these centers into the exascale range, potential spending on power is set to go off the chart. Greening the data center is a daunting challenge but GPUs could help solve the problem.

31/08/2009 Graphics Chips Speed Up Medical Imaging
One of the growing array of applications being found for the powerful graphics-oriented chips is in speeding up medical imaging.

29/08/2009 Velocity Micro and JRTI Released ProMagix VSC255, VSC250 and VSC135+ Visual Supercomputing Workstations with NVIDIA Tesla
It is not surprising that the producers of powerful computer systems tend to use NVIDIA Tesla GPUs in their products to increase their computing capacity.

25/08/2009 Multicore Designs Keep Up With Moore's Law
The transistor count keeps following Moore’s Law. But unless you’re at the low end of the 32-bit spectrum or below, multicore is the only alternative to more powerful platforms.

25/08/2009 Platform Buys HP’s Message Passing Interface
Platform Computing, which has carved out a niche for itself managing supercomputer clusters and dispatching applications on HPC gear, has been expanding up the stack.

17/08/2009 EM Photonics Releases CULA Linear Algebra Library
EM Photonics 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).

13/08/2009 LAPACK on CUDA Beta Available for Free, Takes Refreshing Approach to HPC Software
The team is working on developing a CUDA-based implementation of the popular LAPACK mathematical library, and the beta is available now for free download from their website.

11/08/2009 Penguin Puts Linux Supercomputer in Sky
Penguin announced on Demand - POD, for short - a service that offers remote access to high-performance computing (HPC) Linux clusters based on Intel's Xeon chip and Nvidia's Tesla supercomputing GPU. The idea is to provide researchers, engineers, and simulation scientists with the sort of number-crunching power they can't get from the typical so-called infrastructure cloud.

10/08/2009 Supermicro Announces 4TF GPU Computing System
Super Micro Computer, Inc. announced availability of its 7046GT-TRF SuperWorkstations, the first to support four NVIDIA Tesla C1060 GPUs as well as three additional PCI-e add-on cards for high-bandwidth I/O.

06/08/2009 SGI Chases Cray with Baby Cluster
Cray thinks there is a market for baby supercomputers that bridge the gap between fast two-socket workstations with peppy graphics cards and the rack-based parallel supercomputer clusters that run large-scale simulations. And the new Silicon Graphics agrees.

05/08/2009 NASA Restores Apollo 11 Moon Landing Video with Graphics Technology
Four decades after the historic Apollo 11 moon landing, NASA found that it had accidentally destroyed the archival video footage of one of mankind’s greatest achievements. But Lowry Digital was able to use digital video restoration technology to reconstruct a high-definition version of the footage.

04/08/2009 DigitalGlobe Sees the World with NVIDIA CUDA
DigitalGlobe re-architected its image processing software for the NVIDIA CUDA parallel processing architecture so that all pixel manipulation now can be done on a power-efficient NVIDIA Tesla S1070 GPU cluster. This enables mass customization of data for much faster image processing.

04/08/2009 NVIDIA's Tesla GPUs Now Power HP Z800 Workstation
Santa Clara, California-based NVIDIA, one of the world's leading vendors of graphics solutions, recently announced that the HP Z800 workstation computer system, one of its most powerful and expandable workstations, is now configurable with up to two NVIDIA Tesla graphics processing units.

03/08/2009 Personal Supercomputers Promise Teraflops on Your Desk
About a year ago John Stone, a senior research programmer at the University of Illinois, and his colleagues found a way to bypass the long waits for computer time at the National Center for Supercomputing Applications.

03/08/2009 HP Workstation Comes with Nvidia Tesla GPUs
HP is offering configurations of its Z800 workstation with Nvidia’s Tesla graphics processors.

03/08/2009 HP Adopts Tesla GPUs for Z800 Workstations
HP has announced that they will offer NVIDIA Tesla GPUs in their Z800 series workstations. The target markets will include scientific research, industrial design, 3D animation and seismic exploration.

27/07/2009 GPU-Based System Improves PSTM (Prestack Time Migration) 600-Fold
Chinese petroleum industry adopts new GPU-accelerated software solution for seismic imaging, delivering up to a 400x performance increase.

05/07/2009 Parallel Programming Tutorial Series - Part 8 - CUDA
We provided many resources of parallel programming tutorials. The following are the ones we have linked so far.

20/07/2009 PGI’s Latest Compilers Aimed at x64+GPU Programming
I was struck by the diversity of vendors and partners exhibiting technology based on NVIDIA’s GPUs at ISC last month in Germany. At least 19 companies were offering products that use, facilitate, or support GPUs as part of a larger solution, including everyone from OS and library providers to HPC system vendors.

20/07/2009 NEC Cluster Ranks High on Green500
Installed at the High Performance Computing Center Stuttgart (HLRS), the new NEC LX-2400 HPC Cluster is supplemented by 32 NVIDIA Tesla GPU Computing Servers and delivers 273 MFLOPS per watt.

19/07/2009 NVIDIA Tesla C1060 Computing Processor
If you remember the long gone legendary parallel computing elements known as Transputers, behold.. they have been revived.. NVIDIA have come up with a supercomputing processor that plugs into a PCI-Express slot and gives your computer an astonishing performance capability of more than 933 GFLOPS.

16/07/2009 Cray Adds CX1 Variant to Entice First Time HPC Users
Putting a Cray supercomputer in your office just got a lot cheaper. The company has unveiled a low-end derivative of its CX1 personal deskside system for high performance computing.

15/07/2009 3D Seismic Data: Taking a Smarter Approach to Interpretation
The demand for computational tools to underpin the 3D seismic interpretation process has never been more apparent.

14/07/2009 Faster, Better, Stronger: Speeding Up Medical Imagery
It is absolutely amazing to think about what computers can do nowadays. Just recently, Nvidia produced the Tesla, which brings supercomputing to the level of personal computing. A supercomputer can now sit on a desk, instead of taking up a whole room.

10/07/2009 Moore's Law and GPUs
Way back when, Gordon Moore of Intel came up with his "law" that the number of transistors on a given area of silicon would double every 18 months. There is a lot of punditry around these days about how Moore's Law is slowing down.

09/07/2009 3D Seismic Data: Taking a Smarter Approach to Interpretation
There is a huge and growing mountain of seismic data - new and archived material requiring reprocessing - out there. To interpret it means that the demand for computational tools to underpin the 3D seismic interpretation process throughout the E&P (exploration and production) workflow has never been more apparent.

01/07/2009 Drilling for Fuel
HPC technology is aiding oil and gas companies locate hidden submarine reserves in a fraction of the time taken by previous methods.

30/06/2009 Penguin Computing Delivers University Of Delaware’s Fastest Supercomputer to Global Computing Laboratory
Penguin Computing announced that the University of Delaware Global Computing Laboratory has deployed the university’s largest supercomputer, code-named “Geronimo”, based on a custom GPGPU design utilizing NVIDIA Tesla GPU computing technology coupled with Intel 5400 series processors.

25/06/2009 Match Mtulicore with Multiprogramming
Multiple cores deliver performance with lower power requirements, but processors can’t contribute much if they’re idle.

23/06/2009 PGI and NVIDIA Team Up on New CUDA Compiler
HPC compiler maker PGI announced that they are in joint development on a new Fortran compiler for CUDA.

23/06/2009 CUDA, Supercomputing for the Masses: Part 13 -- Using texture memory in CUDA
This article resumes the discussion of "texture memory" and includes information on the new CUDA Toolkit 2.2 texture capability.

23/06/2009 PGI and NVIDIA Team To Deliver CUDA Fortran Compiler
The Portland Group announced an agreement with NVIDIA under which the two companies plan to develop new Fortran language support for CUDA GPUs.

22/06/2009 Supermicro Showcases GPU-Accelerated Servers
Super Micro Computer, Inc. is showcasing 2-teraflop SuperServer 6016GT-TF-TM2 with two Tesla GPUs plus a new 4U System that suppports four Tesla GPUs.

22/06/2009 Sander Olson Interview: NVIDIA's Sumit Gupta, Tesla GPU Computing Group
NVIDIA is heavily pushing GPU computing, and the field is expanding exponentially. There is an average of 10X-50X improvement using GPUs instead of CPUs, and they are finding that increasing numbers of appliations can run dramatically faster with GPU Computing.

22/06/2009 Supermicro and NVIDIA Smash 1U Server Performance Records at International SuperComputing (ISC) 2009
Super Micro Computer, Inc. is showcasing the fastest 1U server on the planet, its new, 2-Teraflop SuperServer 6016GT-TF-TM2 at ISC'09. This massively parallel processing dual-GPU server is the first 1U multi-GPU (graphics processing unit) system with a fully non-blocking architecture.

19/06/2009 AMAX Launches Tesla GPU Testing Lab
AMAX has established a GPU parallel computing lab for inquiring HPC customers to experience Tesla's revolutionary performance. The GPU systems available for remote testing are ready equipped with the CUDA programming environment. AMAX's knowledgeable CUDA engineers are available for immediate consultation.

16/06/2009 Bull Makes Big Push Into HPC with New Supercomputer Blades
French-owned computer maker Bull has unveiled a new family of HPC servers based on a novel blade architecture. Branded as "bullx," the blades come in two flavors: CPU-only and GPU-accelerated. Both versions are based on dual-socket Nehalem EP (Xeon 5500) nodes, but the accelerator blades include up to two NVIDIA Tesla M1060 GPUs on board.

15/06/2009 CAPS to Launch CAPS Compute Lab with BULL and NVIDIA
CAPS Entreprise announces the launch of its CAPS Compute Lab, a first and exclusive EMEA solution center for hybrid computing with both BULL and NVIDIA partners.

11/06/2009 Standard GPU Cluster Provides High Performance In The Mid-Range (page 25)
Supercomputing continues to get faster, cheaper, and more available. Costs are dropping rapidly partially because of graphics processing units (GPUs) and their highly parallel architecture.

08/06/2009 Allinea to Enhance DDT Debugging Tool for GPGPU Hybrid through collaboration with CEA
Allinea Software has signed a collaboration agreement with CEA to develop enhancements to Allinea's Distributed Debugging Tool for next generation hybrid and "many-core" computer systems. Once developed, this technology will be made available to Allinea's customers.

01/06/2009 Quantum Leap -- Waters Magazine
BNP Paribas drastically accelerates calculation times while slashing electricity consumption with the help of a new GPU-based architecture.

01/06/2009 NVIDIA, Supermicro Give Birth to CPU-GPU Server
Until now, the only practical way for customers to get GPU-accelerated clusters was to combine NVIDIA's own S1070 Tesla servers with x86 CPU servers from a traditional system vendor. Before May, the onus was on the users to configure the Tesla and x86 boxes themselves. But on May 4, NVIDIA launched its pre-configured cluster program, which brought in OEM partners to construct these mixed-processor clusters, allowing customers to purchase pre-built GPU-accelerated systems

01/06/2009 NVIDIA and Supermicro Announce Server with Integrated Tesla Hardware
Supermicro and NVIDIA have announced a new line of server-based machines with integrated Tesla GPUs. The Supermicro SuperServer 6016T-GF-TM2 is a single, 1U chassis with an integrated NVIDIA Tesla GPU. The new server line is marketed towards those looking to make use of NVIDIA’s CUDA programming paradigm designed for massively parallel computing on their GPUs.

01/06/2009 Nvidia, Supermicro Tout 'Highest-Perfomance 1U Server'
Nvidia and SuperMicro will team up on a 1U server that combines two CPUs and two GPUs, all to be used for computational-intensive algorithms. The two will claim that the SuperServer 6016, due in June, is the world's fastest 1U server, according to Andy Walsh, the director of product marke ting for Nvidia.

01/06/2009 New GPU-based SuperServer delivers 12X more computing power
NVIDIA and Supermicro today 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. This unique configuration delivers 12 times the performance of a traditional quad-core CPU-based 1U server. Supermicro will be demonstrating the NVIDIA Tesla-based SuperServer 6016T-GF-TM2 at Computex 2009 in Taiwan this week.

31/05/2009 Supermicro launches Nvidia Tesla fueled server
Supermicro and Nvidia took the wraps off a class of server that’s turbo charged by graphics processors. At the Computex trade show in Taiwan, Supermicro is demonstrating a server that features Nvidia’s Tesla GPUs with multi-core processors in a single 1U rack server.

07/05/2009 Dell "Personal Supercomputers" Now Available With NVIDIA Tesla GPUs
If you’re worried that just one of these GPUs isn’t enough to handle your hardcore needs, worry not – just one C1060 has enough power to control the main system of the European Extremely Large Telescope project (reportedly the world’s largest).

06/05/2009 Tesla-Based Clusters, Workstations Shipping
Needless to say, there's a lot of power going on whether it's a Tesla-charged Dell Precision workstation, or a Tesla Preconfigured Cluster from NVIDIA.

06/05/2009 French Bank Takes On GPU Computing
Using just two of the four GPUs on an NVIDIA S1070 board, they were able to achieve a 15-fold performance increase and a 100-fold power improvement in performance per watt in this one procedure.

04/05/2009 NVIDIA Shifts GPU Clusters Into Second Gear
The good news is that in the GPU computing realm, NVIDIA is the clear market leader.

05/05/2009 Introducing the personal supercomputer’s big brother: NVIDIA’s Tesla preconfigured clusters
NVIDIA’s new Tesla project is the Preconfigured Cluster, which the company calls “Accessible Supercomputing,” and it follows the model of the Personal Supercomputer project.

05/05/2009 Incremental Twiddling
As GPU Clusters hit the market, users are finding small code changes can result in big rewards.

30/04/2009 The Supercomputer Goes Personal
Today, graphics titan NVIDIA advertises its new workstation, the Tesla, as a “personal supercomputer.” It clusters four NVIDIA C1060 processing boards, each of which unites 240 graphics cores to process instructions at nearly teraflops speeds. We calculate it as about 17 percent more cost-effective than Khanna’s PS3 solution, and a lot more elegant.

27/04/2009 NVIDIA's graphic chips moving into high-end computing arena
Tesla is NVIDIA's bold move to stretch its business well beyond graphics. With considerable software development and some hardware tweaking, NVIDIA can turn advanced graphics chips into powerful number-crunching engines that can attack some of the same parallel-processing problems that cluster computers and even low-end supercomputers go after.

22/04/2009 BNP Paribas will use NVIDIA for its GPU solution but competition in the market is set to open up
NVIDIA actually implemented an architecture for GPU computing in CUDA, while the programming environment that developers can then use to access that capability is called C with CUDA extensions.

13/04/2009 BNP Speeds Risk Calculations With Hardware Acceleration
BNP Paribas, moving to bolster its computational power, has implemented a new technology platform designed to not only accelerate calculation times for complex equity derivatives but also slash energy consumption.

11/04/2009 Collaboration Leads to Success: Most Powerful Computer of its Kind in WNY Available World-Wide
Professor Jack Dongarra, one of the foremost authorities on high-end computing and director of the Innovative Computing Laboratory at the University of Tennessee said, “GPUs have evolved to the point where real-world applications are easily implemented on them and run faster than on multi-core systems. Future computing architectures will be hybrid systems with parallel-core GPUs working in tandem with multi-core CPUs.”

09/04/2009 Programming The CUDA Architecture: A Look At GPU Computing
Graphics processing units (GPUs) were originally designed to perform the highly parallel computations required for graphics rendering. But over the last couple of years, they’ve proven to be powerful computing workhorses across more than just graphics applications.

01/04/2009 GPUs: Here to Stay
The fact that GPU chipmaker NVIDIA has made porting code for GPUs easier for the average bench biologist with its CUDA software technology helps the argument for considering this breed of acceleration technology.