By Admin 06 February 2013 0 comments

• NVIDIA Cloud Computing Entreprise Solutions

Introducing the GPU-Accelerated Cloud

NVIDIA GRID™ for enterprise and SMB customers offload VDI graphics processing from the CPU to the GPU, allowing the data center manager to deliver true PC graphics-rich experiences to more users for the first time.

Benefits of NVIDIA GRID for IT:

• Leverage industry-leading VDI solutions, including Citrix, Microsoft, and VMware
• Add your most graphics-intensive users to your VDI solution
• Improve the productivity of all VDI users

Benefits of NVIDIA GRID for users:

• Highly responsive windows and rich multimedia experiences
• Access to all critical applications, including the most 3D-intensive
• Access from anywhere, on any device

A true PC desktop experience for users, virtualized for IT professionals

WHAT THE EXPERTS ARE SAYING

"Using a GPU for hardware-accelerated graphics allows customers to provide a more rich and interactive graphical experience across an even broader set of use cases. All the operational benefits such as vMotion, HA, DRS, etc. are also supported, allowing customers to easily expand or enhance their existing virtual desktop infrastructures. We believe this will enable customers to take their virtual desktop deployments to a different level as they look to further expand the potential of their end users."
Warren Ponder
Director of Product Management for End-User Computing at VMware.

"NVIDIA virtualized GPU technology aligns with Cisco's vision of cloud and delivery of desktop and rich-media applications. GPU virtualization is the one major technology challenge that has been holding back deeper adoption of VDI in the enterprise. We believe NVIDIA's breakthrough will deliver the unique user experience and ease of management customers have been demanding."
David Yen
Senior Vice President and General Manager, Data Center Business Group at Cisco.

VGX Hypervisor

A key technology of the GRID platform that enables hardware virtualization of the GPU is the NVIDIA VGX Hypervisor. The VGX Hypervisor allows a virtual machine to interact directly with a GPU and manages the GPU resources so multiple users can share common hardware, while improving user density.

With the NVIDA VGX Hypervisor, each virtual machine has direct access to the GPU for a true PC experience in the cloud.

User-Selectable Machines (USMs)

The VGX Hypervisor enables the use of User-Selectable Machines (USMs) — allowing system administrators to configure and provision the physical GPU hardware to take on the characteristics needed for specific types of users. This gives IT departments the freedom to support multiple pools of user types, all from a single server.

USMs deliver optimal utilization of hardware resources and the flexibility to configure and deploy new users' desktops based on changing enterprise demands.

NVIDIA Standard User-Selectable Machine

NVIDIA standard USMs come bundled with NVIDIA GRID K2 and K2 boards to provide the maximum user density possible through hardware virtualization. Office productivity professionals can now experience low-latency, high-quality interaction and multimedia.

NVIDIA Quadro User-Selectable Machine

NVIDIA Quadro is the graphics standard for professionals in the workstation industry. The Quadro USM provides industry-leading experience for designers, artists, and scientists who rely on applications requiring interactive 3D graphics and full compatibility. All Quadro professional drivers and APIs (DirectX, OpenGL, and NVIDIA CUDA) are enabled via Quadro USMs for full workstation application certifications, so IT managers can deploy the same Quadro desktop experience remotely.

Partner Solutions

Virtual Remote Workstation Solutions

Citrix > XenDesktop with HDX 3D Pro > XenServer

Virtual Desktop Solutions

Citrix (Coming Soon) > XenDesktop with HDX > XenServer with NVIDIA VGX Hypervisor

Microsoft > RemoteFX > Windows Server 2012

VMware (Coming Soon) > View with vSGA > ESX

Data taken from http://www.nvidia.com/object/vdi-desktop-virtualization.html (accessed on Jan 17, 2013)

By Admin 04 February 2013 0 comments

• GPU Computing | NVIDIA CUDA | KEPLER Architecture | High-Performance Computing

What is GPU Computing?

GPU computing is the use of a GPU (graphics processing unit) together with a CPU to accelerate general-purpose scientific and engineering applications. Pioneered five years ago by NVIDIA, GPU computing has quickly become an industry standard, enjoyed by millions of users worldwide and adopted by virtually all computing vendors.

GPU computing offers unprecedented application performance by offloading compute-intensive portions of the application to the GPU, while the remainder of the code still runs on the CPU. From a user's perspective, applications simply run significantly faster.

CPU + GPU is a powerful combination because CPUs consist of a few cores optimized for serial processing, while GPUs consist of thousands of smaller, more efficient cores designed for parallel performance. Serial portions of the code run on the CPU while parallel portions run on the GPU.

Most customers can immediately enjoy the power of GPU computing by using any of the GPU-accelerated applications listed in our catalog, which highlights over one hundred, industry-leading applications. For developers, GPU computing offers a vast ecosystem of tools and libraries from major software vendors.


"GPUs have evolved to the point where many real-world applications are easily implemented on them and run significantly faster than on multi-core systems. Future computing architectures will be hybrid systems with parallel-core GPUs working in tandem with multi-core CPUs.'
Professor Jack Dongarra
Director of the Innovative Computing Laboratory
The University of Tennessee

History of GPU Computing

Graphics chips started as fixed-function graphics processors but became increasingly programmable and computationally powerful, which led NVIDIA to introduce the first GPU. In the 1999-2000 timeframe, computer scientists and domain scientists from various fields started using GPUs to accelerate a range of scientific applications. This was the advent of the movement called GPGPU, or General-Purpose computation on GPU.

While users achieved unprecedented performance (over 100x compared to CPUs in some cases), the challenge was that GPGPU required the use of graphics programming APIs like OpenGL and Cg to program the GPU. This limited accessibility to the tremendous capability of GPUs for science.

NVIDIA recognized the potential of bringing this performance for the larger scientific community, invested in making the GPU fully programmable, and offered seamless experience for developers with familiar languages like C, C++, and Fortran.

GPU computing momentum is growing faster than ever before. Today, some of the fastest supercomputers in the world rely on GPUs to advance scientific discoveries; 600 universities around the world teach parallel computing with NVIDIA GPUs; and hundreds of thousands of developers are actively using GPUs.

All NVIDIA GPUs—GeForce®, Quadro®, and Tesla®— support GPU computing and the CUDA® parallel programming model. Developers have access to NVIDIA GPUs in virtually any platform of their choice, including the latest Apple MacBook Pro. However, we recommend Tesla GPUs for workloads where data reliability and overall performance are critical. For more details, please see “Why Choose Tesla.”

Tesla GPUs are designed from the ground-up to accelerate scientific and technical computing workloads. Based on innovative features in the “Kepler architecture,” the latest Tesla GPUs offer 3x more performance compared to the previous architecture, more than one teraflops of double-precision floating point while dramatically advancing programmability and efficiency. Kepler is the world’s fastest and most efficient high performance computing (HPC) architecture.

THE CUDA PARALLEL COMPUTING PLATFORM

The CUDA parallel computing platform provides a few simple C and C++ extensions that enable expressing fine-grained and coarse-grained data and task parallelism. The programmer can choose to express the parallelism in high-level languages such as C, C++, Fortran or open standards as OpenACC directives. The CUDA parallel computing platform is now widely deployed with 1000s of GPU-accelerated applications and 1000s of published research papers.

A complete range of CUDA tools and ecosystem solutions is available to developers. Visit CUDA Zone to learn more about developing with CUDA.

KEPLER - THE WORLD'S FASTEST,
MOST EFFICIENT HPC ARCHITECTURE

Get 3x the performance with the NVIDIA® Kepler, the world's fastest and most efficient high performance computing (HPC) architecture. With innovative computing technology and features, it is applicable to a broader range of scientific computing applications and makes hybrid computing more accessible for application developers and researchers.













Data taken from http://www.nvidia.com/object/what-is-gpu-computing.html (accessed on Jan 17, 2013)

By Admin 30 January 2013 0 comments

• NVIDIA GRID Cloud Gaming Review

THE POWER OF CLOUD GAMING

Cloud-based streaming technology has transformed the movie and music industries by delivering unlimited content to consumer devices, including smartphones, tablets, PCs, and TVs. Millions of users now experience the convenience of streaming video and music services like Netflix, Hulu, Spotify, and Pandora.

It's only natural that gaming—the fastest growing media segment and a $68 billion
industry—would follow this trend. NVIDIA is building on a unique legacy in gaming graphics and graphic performance to lead the way in defining the cloud-gaming experience.

FREEDOM FROM THE CONSOLE

NVIDIA GRID is the foundation for the ideal on-demand gaming service, providing tremendous advantages over traditional console gaming systems.

• Any-device gaming: High-quality, low-latency, multi device gaming on any PC, Mac, tablet, smart phone, and TV.
• Click-to-play simplicity: Anytime access to a library of gaming titles and saved games in the cloud. Play or continue games from any device, anywhere.
• Less hassle: No new hardware. No complicated setup. No game discs. No digital downloads. No game installations. No game patches.

Data taken from http://www.nvidia.com/object/cloud-gaming.html (accessed on Jan 17, 2013)

By Admin 23 January 2013 0 comments

• NVIDIA Tegra 3 Super Chip Review and Specifications

NVIDIA® TEGRA® MOBILE PROCESSORS

Take your mobile performance farther with NVIDIA Tegra processors in all your mobile devices. Extreme multitasking. Ultra-smooth web browsing that’s up to twice as fast as other processors. Console-quality gaming. And the best battery-saving technology you’ll find anywhere. Even HD video capabilities for brilliant graphics on the go.


Dara taken from http://www.nvidia.com/object/tegra-3-processor.html (accessed on Jan 15, 2013)

By Admin 16 January 2013 0 comments

• NVIDIA Unveils World's Fastest, Most Efficient Accelerators, Powers World's No. 1 Supercomputer

SC12 -- NVIDIA today unveiled the NVIDIA® Tesla® K20 family of GPU accelerators, the highest performance, most efficient accelerators ever built, and the technology powering Titan, the world's fastest supercomputer according to the TOP500 list released this morning at the SC12 supercomputing conference.

Armed with 18,688 NVIDIA Tesla K20X GPU accelerators, the Titan supercomputer at Oak Ridge National Laboratory in Oak Ridge, Tenn. seized the No. 1 supercomputer ranking in the world from Lawrence Livermore National Laboratory's Sequoia system with a performance record of 17.59 petaflops as measured by the LINPACK benchmark.⁽¹⁾



Tesla K20 - Performance, Energy-Efficiency Leadership
Based on the revolutionary NVIDIA Kepler™ compute architecture, the new Tesla K20 family features the Tesla K20X accelerator, the flagship of NVIDIA's Tesla accelerated computing product line.

Providing the highest computing performance ever available in a single processor, the K20X provides tenfold application acceleration when paired with leading CPUs.⁽²⁾ It surpasses all other processors on two common measures of computational performance -- 3.95 teraflops single-precision and 1.31 teraflops double-precision peak floating point performance.


The new family also includes the Tesla K20 accelerator, which provides 3.52 teraflops of single-precision and 1.17 teraflops of double-precision peak performance. Tesla K20X and K20 GPU accelerators representing more than 30 petaflops of performance have already been delivered in the last 30 days. This is equivalent to the computational performance of last year's 10 fastest supercomputers combined.


"We are taking advantage of NVIDIA GPU architectures to significantly accelerate simulations in such diverse areas as climate and meteorology, seismology, astrophysics, fluid mechanics, materials science, and molecular biophysics," said Dr. Thomas Schulthess, professor of computational physics at ETH Zurich and director of the Swiss National Supercomputing Center. "The K20 family of accelerators represents a leap forward in computing compared to NVIDIA's prior Fermi architecture, enhancing productivity and enabling us potentially to achieve new insights that previously were impossible."

Additional early customers include: Clemson University, Indiana University, Thomas Jefferson National Accelerator Facility (Jefferson Lab), King Abdullah University of Science and Technology (KAUST), National Center for Supercomputing Applications (NCSA), National Oceanic and Atmospheric Administration (NOAA), Oak Ridge National Laboratory (ORNL), University of Southern California (USC), and Shanghai Jiao Tong University (SJTU).



Energy-Efficiency for "Greener" Data Centers
The Tesla K20X GPU accelerator delivers three times higher energy efficiency than previous-generation GPU accelerators and widens the efficiency advantage compared to CPUs.

Using Tesla K20X accelerators, Oak Ridge's Titan achieved 2,142.77 megaflops of performance per watt, which surpasses the energy efficiency of the No. 1 system on the most recent Green500 list of the world's most energy-efficient supercomputers.⁽³⁾


Fastest on Broadest Range of Data Center Applications
The Tesla K20 family accelerates the broadest range of scientific, engineering and commercial high performance computing and data center applications. Today, more than 200 software applications take advantage of GPU-acceleration, representing a 60 percent increase in less than a year.


When Tesla K20X GPU accelerators are added to servers with Intel Sandy Bridge CPUs, many applications are accelerated up to 10x or more, including:⁽⁴⁾

• MATLAB (engineering) - 18.1 times faster
• Chroma (physics) - 17.9 times faster
• SPECFEM3D (earth science) - 10.5 times faster
• AMBER (molecular dynamics) - 8.2 times faster

More information about the Tesla K20 GPU accelerators is available at NVIDIA booth 2217 at SC12, Nov. 12-15, and on the NVIDIA high performance computing website. Users can also try the Tesla K20 accelerator for free on remotely hosted clusters. Visit the GPU Test Drive website for more information.



Availability
The NVIDIA Tesla K20 family of GPU accelerators is shipping today and available for order from leading server manufacturers, including Appro, ASUS, Cray, Eurotech, Fujitsu, HP, IBM, Quanta Computer, SGI, Supermicro, T-Platforms and Tyan, as well as from NVIDIA reseller partners.


¹ Compared to Sequoia system at Lawrence Livermore National Laboratory in Livermore at 16.3 petaflops of performance; Source: Top500.org - www.top500.org/lists/2012/06.
² CPU results: Dual socket E5-2687w, 3.10 GHz, GPU results: Dual socket E5-2687w + 2 Tesla K20X GPUs.
³ Source: Green500.org: www.green500.org/lists/green201206.
⁴ System configuration - CPU results: Dual socket E5-2687w, 3.10 GHz CPUs; GPU results: Dual socket E5-2687w CPUs + 2 Tesla K20X GPUs (MATLAB results running FFT compare one i7-2600K CPU 3.4 GHz vs. Tesla K20 GPU). 




Data taken from http://nvidianews.nvidia.com/Releases/NVIDIA-Unveils-World-s-Fastest-Most-Efficient-Accelerators-Powers-World-s-No-1-Supercomputer-8b6.aspx (accessed on Jan 16, 2013)

By Admin 0 comments

• NVIDIA Powers Titan, World's Fastest Supercomputer For Open Scientific Research

Titan, the world's fastest open-science supercomputer,⁽¹⁾ was completed this month at Oak Ridge National Laboratory in Tennessee, opening new windows of opportunity into the exploration of some of the world's toughest scientific challenges.

Titan's peak performance is more than 20 petaflops -- or 20 million billion floating-point operations per second -- about 90 percent of which comes from 18,688 NVIDIA® Tesla® K20 GPU accelerators. These are based on the NVIDIA Kepler™ architecture, the fastest, most efficient, highest-performance computing architecture ever built.

Researchers use ever faster supercomputers to accelerate the pace of discovery and innovation across a range of scientific fields of inquiry -- from developing more efficient engines and higher capacity, lighter weight batteries, to studying climate change and finding cures for disease. Titan is a milestone on the path to exascale computing, which targets building a 1,000 petaflops supercomputer.

Titan is operated by Oak Ridge National Laboratory, part of the U.S. Department of Energy's network of research labs, as an open-science system. This means it is available to researchers from academia, government laboratories, and a broad range of industries who will use Titan to model physical and biological phenomena and seek breakthroughs faster than possible by experimentation alone.

Supported by the energy efficiency and cost-effectiveness of the Tesla K20 GPU, Titan is more than 10 times faster and five times more energy efficient than its predecessor, the 2.3-petaflops⁽²⁾ Jaguar system, while occupying the same floor space. Had Oak Ridge upgraded Jaguar by simply expanding its CPU-based architecture, the system would be more than four times its current size and consume more than 30 megawatts of power.⁽³⁾
 
"Basing Titan on Tesla GPUs allows Oak Ridge to run phenomenally complex applications at scale, and validates the use of accelerated computing to address our most pressing scientific problems," said Steve Scott, chief technology officer of the GPU Accelerated Computing business at NVIDIA. "You simply can't get these levels of performance, power- and cost-efficiency with conventional CPU-based architectures. Accelerated computing is the best and most realistic approach to enable exascale performance levels within the next decade."

Titan development began three years ago with Oak Ridge's decision to upgrade Jaguar, the previous open science system leader and a former world No. 1 most powerful supercomputer. The upgrade includes the Tesla K20 GPU accelerators, a replacement of the compute modules to convert the system's 200 cabinets to a Cray XK7 supercomputer, and 710 terabytes of memory.

"Science and technology have always been our primary goal, and Titan is a groundbreaking tool that will allow researchers worldwide to leverage GPU-accelerated computing to make unparalleled breakthroughs," said Jeff Nichols, associate laboratory director for computing and computational sciences at Oak Ridge National Laboratory. "The new Tesla GPU accelerators offer the performance and energy efficiency that enable Titan to scale to unprecedented performance levels without consuming the energy equivalent of a small city."


About NVIDIA Tesla GPUs NVIDIA Tesla GPUs are massively parallel accelerators based on the NVIDIA CUDA® parallel computing platform and programming model. Tesla GPUs are designed from the ground up for power-efficient, high performance computing, computational science and supercomputing, delivering dramatically higher application acceleration for a range of scientific and commercial applications than a CPU-only approach.

More information about NVIDIA Tesla GPUs is available at the Tesla website. To learn more about CUDA or download the latest version, visit the CUDA website. More NVIDIA news, company and product information, videos, images and other information is available at the NVIDIA newsroom.




Data taken from http://nvidianews.nvidia.com/Releases/NVIDIA-Powers-Titan-World-s-Fastest-Supercomputer-For-Open-Scientific-Research-8a0.aspx (accessed on Jan 16, 2013)

By Admin 15 January 2013 0 comments

• Top International Cloud-Gaming Pioneers Standardize on NVIDIA GRID Platform

CES -- Six leading international cloud-gaming companies plan to use the NVIDIA® GRID™ Cloud Gaming Platform to deliver gaming services to global broadband companies, NVIDIA announced today.

The NVIDIA GRID Platform enables the smooth, seamless interactive experience of a high-performance gaming PC anywhere, on any screen -- including smart TVs, PCs, tablets and smartphones.


NVIDIA GRID is a server designed to concurrently serve up to 36 times more HD-quality game streams than first-generation cloud-gaming systems, while reducing lag. It is fully integrated with a high density of NVIDIA® GPUs, specialized graphics-application streaming software and NVIDIA® VGX™ Hypervisor technology, which allows multiple users to share a GPU.


Initial partners on the NVIDIA GRID Platform include Agawi (United States); Cloud Union (China); Cyber Cloud Technologies (China); G-cluster Global (Japan); Playcast Media Systems (Israel); and Ubitus (Taiwan).


"By using the NVIDIA GRID Platform, our partners will allow gamers to play anywhere, anytime, without being tethered to a box," said Phil Eisler, general manager of cloud gaming at NVIDIA. "The world's most exciting games can now be played as easily as you can stream a movie, right onto your TV or mobile device. No more discs to shuffle or files to download and install. Just click and play."



Densest GPU Architecture, Broadest Compatibility, Best Interactivity
Consumers already enjoy the benefits of cloud computing to store email and photos and to stream music and movies. The NVIDIA GRID Platform builds on this capability by moving high-end gaming to the cloud, eliminating the need for consumers to manage game discs or fit game consoles next to flat-screen TVs.


The NVIDIA GRID Platform delivers three key attributes:

• Densest GPU system architecture: NVIDIA GRID provides the highest number of concurrent, interactive data streams by using multi-GPU servers and sophisticated NVIDIA VGX GPU-sharing technology. Each server can deliver up to 36 game streams.
  
  
• Broadest compatibility and scalability: NVIDIA GRID software and drivers enable interactive streaming of the widest range of games -- from casual games using low-graphics capabilities with a high density of streams, to high-performance titles requiring high-graphics capabilities.
  
  
• Best interactivity: NVIDIA GRID delivers streamed content for seamless interaction without noticeable lag or latency. NVIDIA GRID technology reduces game server latency by up to 30 milliseconds compared to prior solutions, which effectively hides the network delivery time. Game play from an NVIDIA GRID server feels like that from a console next to a TV.
  
  

Partner Enthusiasm for NVIDIA GRID Platform
Six companies in the newly emerging cloud-gaming services arena are engaged in offering services based on the NVIDIA GRID Platform:


"Consumers love the convenience of any game anywhere instantly, and therefore cloud gaming is the natural evolution of the gaming experience. NVIDIA GRID is a fantastic tool that gives cloud service providers the improved density to make true-GPU clouds a reality and allows our operator, publisher and developer partners to reimagine the gaming experience using the Agawi CloudPlay platform."
-- Rajat Gupta, co-founder of Agawi, which provides B-B cloud-gaming solutions for tablets and TVs.

"In China we don't have game consoles. And therefore we see a large opportunity for cloud gaming in China. The NVIDIA GRID technology is the best that we have seen for delivering high densities of HD-quality game streams to subscribers."

-- Danny Deng, chief executive of Cloud Union, which provides cloud-gaming through China's Telecom/Unicom IPTV network.


"At Cyber Cloud, we focus on delivering cloud gaming services through existing set-top boxes using video-on-demand channels. With NVIDIA's GRID platform we can deliver large numbers of games-on-demand channels to China's digital TV subscribers."

-- Jian Han, general manager of Cyber Cloud, a subsidiary of Beijing Novel-Supertv Digital TV Technology Co. (NYSE: STV), which provides cloud gaming through digital cable TV and IPTV networks.


"As the pioneer in cloud gaming, G-cluster is always looking for ways to increase the performance of our service. G-cluster is working with NVIDIA to reduce the costs for our IPTV operators and improve the experience for our subscribers around the world."

-- Erik Piehl, president of G-cluster, which provides a white-label cloud-based gaming service through France's SFR and Orange.


"Cloud gaming is taking off. NVIDIA GRID technology, Smart Connected TVs and Playcast Media will serve as cloud gaming's catalyst, fueling its explosive growth in 2013."

-- Guy de Beer, chief executive of Playcast Media, which provides a cloud-gaming service to more than 1.2 million subscribers through France's Bouygues Telecom, Korea's CJ Hellovision and Portugal Telecom.


"Ubitus is pleased to partner with NVIDIA to bring the world's most scalable cloud gaming systems to market. Ubitus is the leader in providing cloud gaming over fixed and wireless 4G networks, empowering telecom/cable service providers, hardware OEMs and game developers to benefit from cloud gaming opportunities in a truly sustainable manner."

-- Wesley Kuo, CEO of Ubitus, which provides a cloud-based gaming service through Japan's NTT Docomo, Korea's LGU+ and USA's Verizon.



NVIDIA GRID Cloud Gaming Demonstrated Directly to LG Smart TV at CES
At next week's 2013 International CES event, NVIDIA will demonstrate the NVIDIA GRID Platform streaming games to an LG 55LA6900 Smart TV at 1080p resolution. Among the high-performance games that will be shown are "Assassin's Creed III" by Ubisoft.


"LG is very impressed by the capabilities of NVIDIA's GRID Platform to deliver high-quality game streams directly to LG Smart TVs without a game console," said Bae-Geun Kang, vice president, head of Software Development Group, TV Research Lab, LG. "The NVIDIA GRID Cloud Gaming experience on an LG 55LA6900 Smart TV is beautiful to watch, easy to use and fun to play. It is just like Netflix for games."


Dates for cloud gaming service coverage for LG Smart TVs are not available at this time.




Data taken from http://nvidianews.nvidia.com/Releases/Top-International-Cloud-Gaming-Pioneers-Standardize-on-NVIDIA-GRID-Platform-8ec.aspx (accessed on Jan 15, 2013)

By Admin 0 comments

• NVIDIA Introduces World's Fastest Mobile Processor

CES -- NVIDIA today introduced NVIDIA® Tegra® 4, the world's fastest mobile processor, with record-setting performance and battery life to flawlessly power smartphones and tablets, gaming devices, auto infotainment and navigation systems, and PCs.

Tegra 4 offers exceptional graphics processing, with lightning-fast web browsing, stunning visuals and new camera capabilities through computational photography.


Previously codenamed "Wayne," Tegra 4 features 72 custom NVIDIA GeForce™ GPU cores -- or six times the GPU horsepower of Tegra 3 -- which deliver more realistic gaming experiences and higher resolution displays. It includes the first quad-core application of ARM's most advanced CPU core, the Cortex-A15, which delivers 2.6x faster web browsing and breakthrough performance for apps.

Tegra 4 also enables worldwide 4G LTE voice and data support through an optional chipset, the fifth-generation NVIDIA Icera® i500 processor. More efficient and 40 percent the size of conventional modems, i500 delivers four times the processing capability of its predecessor.


"Tegra 4 provides enormous processing power and efficiency to power smartphones and tablets, gaming devices, auto systems and PCs," said Phil Carmack, senior vice president of the Tegra business at NVIDIA. "Its new capabilities, particularly in the area of computational photography, will help improve a whole range of existing products and lead to the creation of exciting new ones."


Computational Photography Capability
Among the Tegra 4 processor's breakthroughs is its Computational Photography Architecture, which automatically delivers high dynamic range (HDR) photos and video by fusing together the processing power of the GPU, CPU and the camera's image-signal processor.


Its HDR capability captures images, including those taken with a flash, the way they are seen by the human eye -- with detail in both bright and dark areas.


Unprecedented Power Efficiency
Designed for maximum energy efficiency, Tegra 4 includes a second-generation battery saver core for low power during standard use, and PRISM 2 Display technology to reduce backlight power while delivering superior visuals.


Tegra 4 consumes up to 45 percent less power than its predecessor, Tegra 3, in common use cases. And it enables up to 14 hours of HD video playback on phones.



Tegra 4 Key Features

• GeForce GPU with 72 custom cores
• Quad-core ARM Cortex-A15 CPU, plus a 2^nd Generation Battery Saver Core
• Computational Photography Architecture
• LTE capability with optional Icera i500 chipset
• 4K ultra-high-def video support

Tags/Keywords
NVIDIA, Tegra, tablet, smartphone, mobile, quad core, gaming, GPU, CPU, GeForce, ARM, Cortex-A15, LTE, photo, HDR




Data taken from http://nvidianews.nvidia.com/Releases/NVIDIA-Introduces-World-s-Fastest-Mobile-Processor-8ed.aspx (accessed on Jan 15, 2013)

By Admin 0 comments

• NVIDIA Untethers Gaming With Project SHIELD

CES -- NVIDIA today announced Project SHIELD, a gaming portable for open platforms, designed for gamers who yearn to play when, where and how they want.

Created with the philosophy that gaming should be open and flexible, Project SHIELD flawlessly plays both Android and PC titles. As a pure Android device, it gives access to any game on Google Play. And as a wireless receiver and controller, it can stream games from a PC powered by NVIDIA® GeForce® GTX GPUs, accessing titles on its STEAM game library from anywhere in the home.

"Project SHIELD was created by NVIDIA engineers who love to game and imagined a new way to play," said Jen-Hsun Huang, co-founder and chief executive officer at NVIDIA. "We were inspired by a vision that the rise of mobile and cloud technologies will free us from our boxes, letting us game anywhere, on any screen. We imagined a device that would do for games what the iPod and Kindle have done for music and books, letting us play in a cool new way. We hope other gamers love SHIELD as much as we do."

Project SHIELD combines the advanced processing power of NVIDIA Tegra® 4, breakthrough game-speed Wi-Fi technology and stunning HD video and audio built into a console-grade controller. It can be used to play on its own integrated screen or on a big screen, and on the couch or on the go.

Tegra 4 at Its Heart
At the core of Project SHIELD is the world's fastest mobile processor, the new NVIDIA Tegra 4, which delivers enormous power from its custom 72-core GeForce GPU and the first quad-core application of ARM's most advanced CPU core, the Cortex-A15. These, combined with its battery-saver core and energy-saving PRISM 2 technology, deliver hours of gameplay on a single charge.

Windows and Android Games
Windows and Android are the world's most successful computing platforms, with massive ecosystems of system and software developers. While not specifically designed for gaming, both open platforms have drawn gamers by the millions. Project SHIELD is designed to allow them to enjoy Android and Windows games in a new, exciting way.

Project SHIELD can instantly download Android games, including Android-optimized titles available on NVIDIA's TegraZone™ game store, which has already delivered more than 6 million downloads to gamers. It can also be used as a wireless game receiver to a nearby PC equipped with an NVIDIA GeForce GTX 650 GPU or higher.

Console-Grade Controller
Project SHIELD's ergonomic controller was built for the gamer who wants ultimate control and precision.

Retinal Gaming Display
Brilliant gameplay and video are provided by Project SHIELD's integrated 5-inch, 1280x720 HD retinal multitouch display, with 294 dpi. Plus, Tegra 4 with Direct Touch technology gives it touch responsiveness that is a more consistent, accurate and smooth-flowing touch input experience than a standard touch device.

Tuned Port, Bass Reflex Portable Speaker System
Deep, rich audio is critical for a great gaming experience. And Project SHIELD provides fidelity and dynamic range never before available on a portable device, through its custom, bass reflex, tuned port audio system -- with twice the low-frequency output of high-end laptops.

Project SHIELD can also access Android apps such as Hulu, Netflix and Slacker Radio, so users can enjoy their movies and music anywhere without expensive, clumsy wired or wireless speakers.

Support by Leading Industry Analyst
Patrick Moorhead, president and lead analyst at Moor Insights & Strategy, said: "The market has waited years for a breakthrough gaming device that offers the flexibility, quality and total enjoyment of Project SHIELD. Few companies other than NVIDIA have the vision, guts and deep gaming experience to have pulled this off."

Support by Leading Game Developers
Yves Guillemot, co-founder and chief executive officer of Ubisoft, said: "Ubisoft is always excited about new hardware developments, and Project SHIELD promises to bring both mobile and PC gamers a great new gaming experience. Seeing the PC version of Assassin's Creed III run on the device is a great example of this, and further strengthens Ubisoft's long-standing relationship with NVIDIA."

Mark Rein, vice president and co-founder of Epic Games, said: "With Project SHIELD, NVIDIA brings an uncompromising, high-performance console experience to mobile devices. Amazing games including Real Boxing and Hawken, which utilize the latest Unreal Engine technology, look fantastic on Project SHIELD. This is just the beginning, and we're truly excited to see what more Unreal Engine developers will do with so much horsepower in such a compact gaming device."

Bill Wagner, chief production officer at Meteor Entertainment, said: "Coming from the openness of a PC platform, we love how accessible Project SHIELD is, and the flexibility it gives gamers everywhere. Project SHIELD gives us the cutting-edge ability to bring a huge free-to-play PC game like Hawken to the handheld gaming audience."

Support by Broader Industry
"Shadowgun and Dead Trigger showed how Tegra can redefine mobile gaming on Android. Project SHIELD's performance has allowed us to bring an even better experience with Dead Trigger 2, debuting first on Tegra 4 devices. Our fans are going to love it."
- Marek Rabas, chief executive officer of MADFINGER Games

"Project SHIELD has changed how we approach mobile game development. Tegra 4 helped us create Bloodsword -- a new game debuting with the highest resolution textures, graphics and shading we've ever seen on a portable device."
- Seunghee Do, co-founder at OneQ Soft

"We are very excited to be part of Project SHIELD, and are quite amazed by the gaming potential of this device. Project SHIELD is by far the fastest mobile device we've worked on and it lets us put console quality graphics on a handheld device."
- Stine Waern, chief executive officer at Ravn Studio AS

"Thanks to Project SHIELD's performance, we're able to use the same quality textures and shaders in Rochard as on the PC version. We're super excited to bring Rochard to Project SHIELD, the first time it's ever been playable on a mobile device."
- Jan Achrenius, chief executive officer at Recoil Games

"Put simply, Project SHIELD is an amazing leap forward, enabling us to create console-quality visuals previously unthinkable on a mobile platform."
- Arden Aspinall, chief executive officer and project lead at TickTock Games Ltd.

PROJECT SHIELD Features

By Admin 0 comments

• Audi to Globally Roll Out NVIDIA Tegra Visual Computing Module This Year

CES -- NVIDIA today announced that Audi's newest auto-infotainment system featuring NVIDIA^® Tegra^® technology will be rolled out globally in select vehicles this year.

The innovative Audi MIB modular infotainment system introduces a new powerful computing module, MMX, which is based on the NVIDIA Tegra Visual Computing Module (VCM). The new MIB high-end system is currently available in Europe in the all-new Audi A3. Beginning with major markets in Asia, the system will reach further regions this year and come to the United States and Canada by 2014.


The connected Audi MIB system powers Audi connect, which enables live updates of Google Earth imagery complete with Google Maps Street View 360 degree panoramas. It also facilitates the delivery of other online information, such as real-time gas prices, weather forecasts and points of interest search powered by Google Local Search.


The innovative MIB architecture received the "Best Global OEM Infotainment Solution Award" at the 10th Annual Telematics Update ceremony in Novi, Mich.


"The start of production of the Tegra-based MIB infotainment system was a major milestone for Audi," said Mathias Halliger, head of architecture, MMI system at Audi. "The new modular approach allows us an independent evolution of automotive-cycle and consumer-electronics-cycle multimedia systems so that we can implement the latest and greatest innovations that allow the best possible customer experience with infotainment in the vehicle."


The new MIB system approach is planned for all new upcoming Audi cars, generations and further facelifts. It is also empowering the high-end navigation systems of VW group brands Volkswagen and Skoda.


At the heart of the MIB system is the NVIDIA VCM based on the NVIDIA Tegra mobile processor. The modular design of the VCM enables automakers to separate the rapidly advancing processor technologies from the slower to update electronics in vehicles. This can save automakers significant development time and cost by enabling rapid implementation of in-vehicle systems across diverse vehicle models.


"NVIDIA's modular VCM approach lets companies like Audi quickly move from a Tegra 2 processor, to a Tegra 3 and beyond," said Taner Ozcelik, general manager of automotive, NVIDIA. "Never before has an automaker been able to deliver a new generation of consumer electronics technology within such a short time."


NVIDIA works with the most forward-thinking automakers to deliver advanced mobile technology to drivers and their passengers. More information about NVIDIA solutions for the automotive market is available at www.nvidia.com/automotive.

NVIDIA® Tegra® Visual Computing Module (vcm)

This unique platform gives automakers a fast, easy way to integrate the most recent automotive-grade Tegra processor into their vehicles. NVIDIA VCM is a flexible design approach that dramatically closes the technology gap between consumer electronics and in-vehicle systems.

NVIDIA TEGRA processors: The innovation inside

Multi-core Tegra mobile processors enable visually stunning in-vehicle infotainment systems and critical safety applications, truly bringing the driving experience to life.

The Tegra system-on-a-chip (SoC) integrates eight specialized processors, including a multi-core ARM CPU, a GPU, and dedicated audio, video, and image processors. But it consumes 50 times less energy than the typical CPU.

This makes it the ideal solution for today’s—and tomorrow’s—cars.



Data taken from http://nvidianews.nvidia.com/Releases/Audi-to-Globally-Roll-Out-NVIDIA-Tegra-Visual-Computing-Module-This-Year-8ef.aspx, http://www.nvidia.com/object/visual-computing-module.html (accessed on Jan 15, 2013)

By Admin 18 December 2011 0 comments

• NVIDIA CUDA™ Parallel Programming

This post is about NVIDIA CUDA Parallel Programming. You will know what CUDA is, a historical background, along with links for downloads and more information can be obtained there.


What is CUDA?
With millions of CUDA-enabled GPUs sold to date, software developers, scientists and researchers are finding broad-ranging uses for GPU computing with CUDA. Here are a few examples:

• Identify hidden plaque in arteries: Heart attacks are the leading cause of death worldwide. Harvard Engineering, Harvard Medical School and Brigham & Women's Hospital have teamed up to use GPUs to simulate blood flow and identify hidden arterial plaque without invasive imaging techniques or exploratory surgery.
• Analyze air traffic flow: The National Airspace System manages the nationwide coordination of air traffic flow. Computer models help identify new ways to alleviate congestion and keep airplane traffic moving efficiently. Using the computational power of GPUs, a team at NASA obtained a large performance gain, reducing analysis time from ten minutes to three seconds.
• Visualize molecules: A molecular simulation called NAMD (nanoscale molecular dynamics) gets a large performance boost with GPUs. The speed-up is a result of the parallel architecture of GPUs, which enables NAMD developers to port compute-intensive portions of the application to the GPU using the CUDA Toolkit.

GPU Computing: The Revolution

Computing is evolving from "central processing" on the CPU to "co-processing" on the CPU and GPU. To enable this new computing paradigm, NVIDIA invented the CUDA parallel computing architecture that is now shipping in GeForce, ION, Quadro, and Tesla GPUs, representing a significant installed base for application developers.

In the consumer market, nearly every major consumer video application has been, or will soon be, accelerated by CUDA, including products from Elemental Technologies, MotionDSP and LoiLo, Inc.
CUDA has been enthusiastically received in the area of scientific research. For example, CUDA now accelerates AMBER, a molecular dynamics simulation program used by more than 60,000 researchers in academia and pharmaceutical companies worldwide to accelerate new drug discovery.

In the financial market, Numerix and CompatibL announced CUDA support for a new counterparty risk application and achieved an 18X speedup. Numerix is used by nearly 400 financial institutions.

An indicator of CUDA adoption is the ramp of the Tesla GPU for GPU computing. There are now more than 700 GPU clusters installed around the world at Fortune 500 companies ranging from Schlumberger and Chevron in the energy sector to BNP Paribas in banking.

And with the recent launches of Microsoft Windows 7 and Apple Snow Leopard, GPU computing is going mainstream. In these new operating systems, the GPU will not only be the graphics processor, but also a general purpose parallel processor accessible to any application.

There are multiple ways to tap into the power of GPU Computing, writing code in CUDA C/C++, OpenCL , DirectCompute, CUDA Fortran and others.

It is also possible to benefit from GPU Compute acceleration using powerful libraries such as MATLab, CULA and others.

Many widely adopted commercial codes have been developed to use GPU Computing, please visit our vertical solutions page  to find out if the software that you use has already been ported.



You're faced with imperatives: Improve performance. Solve a problem more quickly. Parallel processing would be faster, but the learning curve is steep – isn't it?

Not anymore. With CUDA, you can send C, C++ and Fortran code straight to GPU, no assembly language required.

Developers at companies such as Adobe, ANSYS, Autodesk, MathWorks and Wolfram Research are waking that sleeping giant – the GPU -- to do general-purpose scientific and engineering computing across a range of platforms.

Using high-level languages, GPU-accelerated applications run the sequential part of their workload on the CPU – which is optimized for single-threaded performance – while accelerating parallel processing on the GPU. This is called "GPU computing."

GPU computing is possible because today's GPU does much more than render graphics: It sizzles with a teraflop of floating point performance and crunches application tasks designed for anything from finance to medicine.

CUDA is widely deployed through thousands of applications and published research papers and supported by an installed base of over 300 million CUDA-enabled GPUs in notebooks, workstations, compute clusters and supercomputers.

Visit CUDA Zone for examples of applications in diverse vertical markets… and awaken your GPU giant.

History of GPU Computing

The first GPUs were designed as graphics accelerators, supporting only specific fixed-function pipelines. Starting in the late 1990s, the hardware became increasingly programmable, culminating in NVIDIA's first GPU in 1999. Less than a year after NVIDIA coined the term GPU, artists and game developers weren't the only ones doing ground-breaking work with the technology: Researchers were tapping its excellent floating point performance. The General Purpose GPU (GPGPU) movement had dawned.

But GPGPU was far from easy back then, even for those who knew graphics programming languages such as OpenGL. Developers had to map scientific calculations onto problems that could be represented by triangles and polygons. GPGPU was practically off-limits to those who hadn't memorized the latest graphics APIs until a group of Stanford University researchers set out to reimagine the GPU as a "streaming coprocessor."
In 2003, a team of researchers led by Ian Buck unveiled Brook, the first widely adopted programming model to extend C with data-parallel constructs. Using concepts such as streams, kernels and reduction operators, the Brook compiler and runtime system exposed the GPU as a general-purpose processor in a high-level language. Most importantly, Brook programs were not only easier to write than hand-tuned GPU code, they were seven times faster than similar existing code.

NVIDIA knew that blazingly fast hardware had to be coupled with intuitive software and hardware tools, and invited Ian Buck to join the company and start evolving a solution to seamlessly run C on the GPU. Putting the software and hardware together, NVIDIA unveiled CUDA in 2006, the world's first solution for general-computing on GPUs.

Getting Started - Parallel Computing

Whether you are porting an existing application, designing a new application, or just want to get your work done faster using the applications you have, these resources will help you get started.

GPU Acceleration in Existing Applications

Many scientists, engineers, and professionals can realize the benefits of parallel computing on GPUs simply by upgrading to GPU-accelerated versions of the applications they already use.  Examples include LabVIEW, Mathematica, MATLAB, and many more…

Developing Your Own Applications

If you are developing applications or libraries, first decide whether you want to take advantage of existing libraries that are already optimized for parallel computing on GPUs.  If all the functionality you need already exists in a library, you may simply need to use these libraries in your application.  Even if you know you want to write your own custom code for the GPU, it’s worth reviewing the available libraries to see what you can leverage.
If you will be writing your own code for the GPU, there are many available language solutions and APIs, so it’s worth reviewing the options and selecting the solution that best meets your needs.

Approach	Examples
Application Integration	MATLAB, Mathematica, LabVIEW
Implicit Parallel Languages	PGI Accelerator, HMPP
Abstraction Layer/Wrapper	PyCUDA, CUDA.NET, jCUDA
Language Integration	CUDA C/C++, PGI CUDA Fortran
Low-level Device API	CUDA C/C++, DirectCompute, OpenCL

Once you have decided which libraries and language solution or API you’re going to use, you’re ready to start programming. If you selected a solution provided by NVIDIA, download the latest CUDA Toolkit and review the Getting Started Guide.  There’s also a collection of essential training materials, webinars, etc. on our CUDA Education & Training  page.

Choose Your Development Platform

With over 300M CUDA-architecture GPUs sold to date, most developers will be able to use the GPU you already have to get started.  When you’re ready to test and deploy your applications, make sure you review our current product lines and OEM solutions to select the best systems for your needs.

• Tesla products are designed for datacenter and workstation computing applications
• Quadro products are designed for professional graphics and engineering applications
• GeForce products are designed for interactive gaming and consumer applications

Rounding Out Your Development Environment

There’s a good chance that the debuggers and performance analysis tools you use already have support for GPU development as well.

Need Some Help?

NVIDIA hosts the GPU Computing Developer Forums , where you’ll find a community of expert GPU developers from NVIDIA and around the world.  There are also dozens of domain-specific developer communities at www.gpucomputing.net, so be sure to connect with other developers in your field.
There is a growing ecosystem of consultant firms with expertise in GPU software development.  Check out the list of firms that provide high quality GPU developer training and have done great work for our customers.

Tools and Training

Today, the CUDA ecosystem is growing rapidly as more and more companies provide world-class tools, services and solutions.

If you want to write your own code, the easiest way to harness the performance of GPUs is with the CUDA Toolkit, which provides a comprehensive development environment for C and C++ developers.

The CUDA Toolkit includes a compiler, math libraries and tools for debugging and optimizing the performance of your applications. You'll also find code samples, programming guides, user manuals, API references and other documentation to help you get started.

NVIDIA provides all of this free of charge, including NVIDIA Parallel Nsight for Visual Studio, the industry's first development environment for massively parallel applications that use both GPUs and CPUs.


Here are some links that might interest you, where you`ll obtain more information and download files:-
http://developer.nvidia.com/cuda-downloads
http://developer.nvidia.com/cuda-toolkit
http://developer.nvidia.com/category/zone/cuda-zone
http://developer.nvidia.com/cuda-education-training



Data taken from http://www.nvidia.com/object/cuda_home_new.html  ,  http://developer.nvidia.com/category/zone/cuda-zone