Imagine being able to virtually teleport from one space to another in real time.
With 3D-capture cameras and a mixed reality display such as HoloLens, Microsoft Research’s new ‘haloportation’ innovation allows users to see, hear, and interact with remote participants in 3D as if they are actually present in the same physical space.
Custom software helps reconstruct every possibly viewpoint from each camera and then stitches them together into one fully formed 3D model.
“We want to do all of this processing in a tiny window — around 33 milliseconds — to process all the data coming from all of the cameras at once, basically, and also create a temporal model, and then stream the data,” says project lead Shahram Izadi, whose team leans on NVIDIA GPUs to crunch the relevant numbers.
Izadi also mentioned the system is able to record and playback entire previous ‘haloportation’ sessions which is like walking back through time to experience memorable events.
Using Virtual Reality to Optimize User Experience Share Your Science: Using Virtual Reality to Optimize User Experience
EASE VR Co-Founders Prithvi Kandanda, CEO and Fred Spencer, CTO share how they are using NVIDIA GPUs and real-time analytics to understand a user’s behavior in virtual environments. Use cases and applications vary across industries and including retail, sports, social, manufacturing, and entertainment.
Learn more about EASE VR at https://easevr.com.
Share your GPU-accelerated science with us at http://nvda.ly/Vpjxr and with the world on #ShareYourScience.
Watch more scientists and researchers share how accelerated computing is benefiting their work at http://nvda.ly/X7WpH
If you missed the opening keynote by NVIDIA CEO Jen-Hsun Huang, here’s a recap of today’s announcements at the GPU Technology Conference in Silicon Valley.
Watch Jen-Hsun’s complete keynote at the GPU Technology Conference.
Learn more about all the announcements on the NVIDIA Developer website.
Explore the future of artificial intelligent and deep learning, experience virtual reality, and see what the future holds for self-driving cars at the GPU Technology Conference in Silicon Valley, April 4-7.
In addition to keynotes by notable speakers that include NVIDIA CEO Jen-Hsun Hung, Toyota Research Institute CEO Gill Pratt, and IBM Watson CTO Rob High, as well as over 500 talks, tutorials and scientific posters – here are the top six must-see things at GTC this year:
- AI Playground: Interact with hands-on deep learning demos from universities, start-ups and well-known companies like Baidu, Twitter and Yahoo.
- VR Village: New this year, experience the latest advances in a variety of immersive virtual reality experiences from a wide-range of industries including gaming, media & entertainment, manufacturing, medicine and science.
- Emerging Companies Summit Pavilion: Over 90 start-ups will showcase how they are using GPUs to solve some of the world’s most complex challenges. Twelve of the participants will be vying for $100,000 at the Early Stage Challenge.
- Hands-on Labs: Take one of the intensive 26 instructor-led labs that range from 90 to 180 minutes covering a wide-range of topics, from the comfort of your own laptop. Attendees looking for more training can grab a seat in the self-paced labs area or try them from anywhere for free, using promo code GTC16_EARLYBIRD to receive free credits on NVIDIA’s cloud-based learning platform.
- Share Your Science: This is a great opportunity to share how you are doing amazing work with GPUs. NVIDIA will be video interviewing developers, researchers and scientists and then amplifying your stories to the broader community. Fill out this short form to be considered for an interview.
- Face2Face Demo: A team of researchers from Stanford, the Max Planck Institute for Informatics and the University of Erlangen-Nuremberg are using TITAN X GPUs and CUDA to manipulate YouTube videos with real-time facial reenactment that works with any commodity webcam. You can experience the magic of the Face2Face demo in person at the NVIDIA booth.
Register by April 2 to save up to $300, and see what the future holds at the GPU Technology Conference.
Each startup will be given four minutes to present their GPU-accelerated tech and business plan live on stage to an audience of technology executives.
The challenge is designed for startups in the GPU ecosystem that have raised less than $1 million in seed funding and are ready to expand their visibility and demonstrate their potential to investors.
“We’ve had hundreds of companies at different stages of development come to ECS over the years,” says Jeff Herbst, VP of business development at NVIDIA. “They get a big boost in exposure, they get valuable feedback and insights, and many have become incredibly successful, like Oculus Rift and Natural Motion.”
Some of the companies competing in this year’s Early Stage Challenge are:
Aerialguard (Israel) — Provides autonomous situational awareness for drones and UAVs, dramatically increasing safety, survivability, and mission capabilities.
Horus Technology (Italy) — Develops a wearable device that uses computer vision and machine learning to aid visually impaired people, describing the environment through bone conduction.
Hypercubes (U.S.) — Develops satellites that reveal unprecedented details of Earth, with the ability to remotely classify chemical compositions for applications such as precision farming, mining, and oil & gas operations.
Analytical Flavor Systems (U.S.) — Uses machine learning and AI to identify and predict real-time flaws, contaminations and batch-to-batch deviations for food and beverage producers.
My first impression of virtual reality was back in the early 1990s, in a pod playing Dactyl Nightmare in a Dave & Busters restaurant. It was less compelling by today’s standards, but enough to hook me and a whole generation of future engineers and gamers.
That generation has come of age, and so has VR.
Every tradeshow, every product launch and every news beat has a VR angle. And NVIDIA is helping to pioneer the technology that’s making it a reality.
Here are 10 examples:
1) NVIDIA is building the fastest GPUs for VR.
There are two platforms for immersive VR gaming and experiences: entry-level experiences provided by consoles and premier experiences provided by PCs. Consider the view of veteran industry watcher Jon Peddie, of Jon Peddie Research:
“VR will be a multi-tier experience, like all entertainment platforms. Consoles will appeal to the casual user, whereas the PC with three to four times the processing power will be the platform for the intense gamer. In the PC market, NVIDIA has a substantial market share in enthusiast graphics boards, the type needed for Oculus and HTC VR experiences.”
Just like with video games, a PC with a GeForce GTX GPU offers the richest VR experience, with more performance, higher immersion and great fidelity. Even the lowest VR Ready GeForce GTX GPU offers double the performance of console.1 And given that immersive VR requires seven times the processing power of traditional 3D games, you really need that performance to get the best experience.2
2) NVIDIA’s VR SDK, VRWorks, is seeing broad adoption.
NVIDIA has created the VRWorks software development kit to provide headset and application developers with the best performance, lowest latency and plug-and-play compatibility for VR. The top game engines that are being used for creating VR games, including Unity, Unreal Engine and Max Play, are now integrating NVIDIA VRWorks. HTC and Oculus headsets have added support for VRWorks. It’s being adopted by cutting-edge VR developers like Sólfar Studios with Everest VR, Valve Software with The Lab, ILMxLAB with Star Wars Trials on Tatooine and InnerVision Games with Thunderbird: The Legend Begins.
3) NVIDIA GPUs provide Multi-res Shading for up to 50 percent more performance.
NVIDIA Multi-res Shading is an innovative rendering technique for VR in which each part of an image is rendered at a resolution that better matches the final image a user sees on the headset. The technology is integrated and available today to developers in Unreal Engine with performance gains of up to 50 percent. That enables developers to put more visual quality into their VR games and experiences
4) NVIDIA’s Game Ready drivers means VR games ‘just work’ from day one.
Any solution is only as good as the GPU’s drivers. Our Game Ready drivers are recognized as the best in the industry. NVIDIA works closely with developers to make sure games perform well on the day the game ships. This is incredibly important for VR, as the slightest stutter or performance dip can ruin the experience. Delivering launch day drivers will be a big difference for VR games and applications.
5) Our GeForce GTX VR Ready program is more than 100 partners strong.
NVIDIA’s GeForce GTX VR Ready program makes it easy for consumers to get the right gear for VR. Navigating an emerging technology like VR can be confusing — so we’ve worked with our partners worldwide to simplify the buying process. The GeForce GTX VR Ready badge quickly shows if a PC or graphics card is capable of handling the demands of VR. Our program currently has more than 100 PC makers, system builders, add-in card partners and retailers around the globe.
6) VR-ready notebooks are powered by NVIDIA.
Notebooks that feature NVIDIA GeForce GTX 980 GPUs are the only VR-ready notebooks in the world. These powerful NVIDIA notebook GPUs enable developers and gamers to take their immersive VR experiences with them on the go.
7) NVIDIA GPUs are driving Oculus Ready PCs.
8) NVIDIA makes immersive VR accessible.
There is a misconception that VR requires performance capabilities out of reach for most gamers. Truth be told, the GeForce GTX 970 GPU is the most popular graphics card on the Steam survey and millions already have it in their machines. This means more consumers are ready to enjoy immersive VR today.
9) NVIDIA is bringing more performance to mobile VR.
NVIDIA is continuing to push forward the state of the art for mobile-based VR experiences. You can find NVIDIA Tegra processors powering several mobile VR and augmented reality devices, including headsets from GameFace Labs and Atheer. Thanks to the performance of Tegra, developers can tackle new classes of mobile VR/AR experiences.
10) NVIDIA is accelerating 360-degree video for VR.
NVIDIA GPUs are at the heart of 360-degree video used in VR. NVIDIA’s CUDA programming model is used to rapidly stitch video from multiple cameras together into a single 360-degree panorama. At NVIDIA’s GPU Technology Conference in April, attendees will find a full speaker track on VR, including talks from 360-degree video companies that use GPU acceleration, such as Jaunt VR and VideoStitch.
See It for Yourself at GDC
You can see our work in VR at GDC. NVIDIA has partnered with a host of developers to feature amazing VR experiences at our booth (South Hall #824) on HTC Vive and Oculus Rift headsets. They include:
- A new chapter of Everest VR from Sólfar Studios that incorporates NVIDIA Multi-res Shading technology and GameWorks turbulence effects
- ILMxLAB’s Star Wars: Trials on Tatooine VR experience, powered by two GeForce GTX TITAN X GPUs using VR SLI technology
- Epic’s Bullet Train, Oculus Studio’s VR Sports and CCP’s EVE: Valkyrie
Beyond the NVIDIA booth, GDC attendees will find GeForce GTX GPUs powering the top VR experiences across the show floor. These include:
|Epic||Moscone South Hall 1024|
|Oculus||Moscone South Hall 802|
|GDC VR Lounge||Moscone West 3rd Floor|
VR is an exciting new medium for gaming, entertainment and professional use cases. The performance of the PC will make it the destination for premium VR experiences. As the worldwide leader in PC graphics, NVIDIA is working hard to provide a VR graphics platform that offers developers both a large installed base and the best performance.
We can’t wait to see what you build with it.
1 GeForce GTX 970 produces 3.5 teraflops vs 1.8 teraflops for PlayStation 4, delivering 2x performance.
The Facebook Artificial Intelligence Research (FAIR) lab announced a new Research Partnership Program to spur advances in Artificial Intelligence and machine learning — Facebook will be giving out 25 servers powered with GPUs, free of charge.
The first recipient to receive 32 GPUs in four GPU servers is Klaus-Robert Müller of TU Berlin. “Dr. Müller will receive four GPU servers that will enable his team to make quicker progress in two research areas: image analysis of breast cancer and chemical modeling of molecules,” FAIR engineering director Serkan Piantino and research lead Florent Perronnin wrote in a blog post.
Facebook will supply server recipients with all of the necessary software to run the servers and will also send some of its own researchers to various institutions for collaboration.
Facebook CEO Mark Zuckerberg made the announcement from Berlin in a live video feed on his Facebook page – he also discussed the latest in AI with Yann LeCun, who leads Facebook AI Research.
To accelerate biomedical research, Australia’s Monash University boosted its research infrastructure with a third GPU-accelerated supercomputer called MASSIVE-3.
Over the past five years, MASSIVE has played a key role in driving discoveries across many disciplines including biomedical sciences, materials research, engineering, and geosciences.
Alongside the MASSIVE supercomputers at Monash, the university also hosts the CAVE2 immersive visualization platform. This 21st Century Microscope empowers researchers to interactively explore data from electron microscopes and medical imaging instruments.
In this brief video, Dr. David Barnes, senior research fellow at Monash provides an inside-look into their visualization environment.
“Our collaboration with NVIDIA will take Monash research to new heights. By coupling some of Australia’s best researchers with NVIDIA’s accelerated computing technology we’re going to see some incredible impact. Our scientists will produce code that runs faster, but more significantly, their focus on deep learning algorithms will produce outcomes that are smarter,” said Professor Ian Smith, Vice Provost (Research and Research Infrastructure), Monash University.
– See more at: https://news.developer.nvidia.com/monash-university-upgrades-massive-gpu-accelerated-supercomputer/#sthash.RekJmhDy.dpuf
Flood risk assessment is important in minimizing damages and economic losses caused by flood events.
A team of researchers from Vienna University of Technology and visual computing firm VRVis, are using GPUs to run fast simulations of large-scale scenarios, including river flooding, storm-water events and underground flows.
The researcher’s primary interest is in decision-making systems, where they evaluate many different scenarios and select the solution with the best outcome, which is usually very computationally expensive. Therefore, simulation runs need to be as fast as possible to reduce the overall time required to find the best solutions.
کودا به انگلیسی (CUDA) که مخفف عبارت انگلیسی Compute Unified Device Architecture است یک سکوی پردازش موازی و مدل برنامهنویسی است که توسط شرکت انویدیا بهوجود آمده است و در واحدهای پردازش گرافیکی این شرکت پشتیبانی میشود.کودا به توسعه دهنده گان نرمافزار اجازه میدهد تا از یک GPU که ویژگی CUDA-enabled دارد برای هدف پردازش استفاده کنند، رویکردی که GPGUG شناخته میشود. کودا به توسعهدهنده گان امکان دسترسی مستقیم به حافظه و مجموعه دستورالعمل در واحد پردازش گرافیکی را میدهد.
سکوی کودا برای کار با زبانهای برنامهنویسی مانند C و ++C و فرترن طراحی شدهاست.این دسترسی باعث میشود تا برای متخصصان استفاده از منابع GPU آسانتر شود برخلاف راه کار های API دیگر چون DIRECT3D و OpenGL که نیاز به توانایی حرفه ای در برنامه نویسی گرافیک داشتند.همچین کودا از چارچوبهایی چون OpenACC و OpenCL پشتیبانی می کند.
GPU به عنوان یک پردازنده خاص ،درخواستهای های بلادرنگ با کیفیت بالا گرافیک سه بعدی که از نظر وظایف محاسباتی فشرده هستند را مختصاتدهی میکند.از سال 2012 میلادی GPU ها به سیستمهای چند هسته ای قدرتمندی ارتقا یافتند که قادر به دستکاری بلوکهای بزرگی از داده ها هستند.این طراحی بسیار از هدف عامه CPU ها برای الگوریتمها در مواقعی که پردازش موازی روی بلوک های داده انجام میشود موثرتر است.به عنوان مثال:
- الگوریتم ارسال برچسب
- الگوریتم مرتب سازی سریع روی لیستهای بزرگ
- تبدیل موجک سریع دوبعدی
- شبیهسازی دینامیک مولکولی
کودا توسط کتابخانههای مجهز شده کودا ،دستوردهنده کامپایلر مانند OpenACC و همین طور توسعههایی استاندارد صنعتی از زبانهایی شامل C، ++C و فرترن برای توسعهدهندگان قابل دسترسی است.برنامهنویسان C++/C از ‘++CUDA C/C’ استفاده می کنند که کامپایل شده با “nvcc” است.nvcc یک کامپایلر C++/C بر پایه LLVM شرکت انویدیا است.برنامه نویسان فرترن نیز می توانند از ‘CUDA Fortran’ استفاده کنند که کامپایل شده با PGI CUDA Fortran Complier شرکت The Portland Group است. علاوه بر کتابخانهها ،دستوردهندههای کامپایلر و ++CUDA C/C و CUDA Fortran ،سکو کودا از سایر رابطهای محاسباتی شامل موارد زیر پشتیبانی می کند.
- OpenCL گروه Khronos
- DirectCompute مایکروسافت
- محاسبات سایه زنی OpenGL
- C++ AMP
همچنین لفافه سوم شخص (Third party wrappers) برای زبان هایی مانند پرل (Perl)،پایتون (Python)،آر (R) ،فرترن (FORTRAN)،جاوا (Java)،روبی (Ruby)،هسکل (Haskell)،متلب (Haskell) ،آی دی ال (IDL)،لوآ (Lua) و نیز به طور پیشفرض متمتیکا (Mathematica) در دسترس هستند.
در صنعت بازیهای کامپیوتری ،GPUها تنها برای رندر کردن گرافیک نیست بلکه در محاسبات فیزیکی بازی (اثرات فیزیکی شبیه دود ،آتش ،ترشحات و آوار) نیز هستند.مثالهایی نظیر فیز-اکس و گلوله شامل این مورد هستند.کودا همچنین برای کاربردهای شتابدهی غیرگرافیکی در زیستشناسی محاسباتی ،رمزنگاری و حوزه های دیگر نیز استفاده میشود.
کودا هم یک API سطح پایین و هم یک API سطح بالا فراهم می کند.SDK اولیه کودا در 15 فوریه 2007 برای ویندوز مایکروسافت و لینوکس انتشار عمومی شد.پشتیبانی در سیستمعامل مک در نسخه دوم اضافه شد که جای نسخه تست 14 فوریه 2008 را میگیرد.کودا با تمامی GPUهای از سری G8x به بعد شامل جیفورس ،کوادرو و تسلا(گرافیک) کار میکند.کودا با بیشتر سیستمعاملهای استاندارد کار میکند.انویدیا میگوید برنامههایی که برای سری G8x توسعهیافتهاند همچنین بدون تغییر روی نسلهای آینده کارتهای گرافیک بسته به سازگاری دودویی کارخواهند کرد.
کودا چندین برتری در برابر محاسبات عمومی سنتی روی GPU ها(در کل منظورGPGPU) دارد که از واسطهای گرافیکی استفاده میکنند.
- خواندن پراکنده یعنی کد میتواند از آدرسهای دلخواه در حافظه بخواند.
- حافظه مجازی یکپارچه (کودا نسخه 4.0 به بعد)
- حافظه یکپارچه(کودا نسخه 6.0 به بعد)
- حافظه مشترک کودا ناحیه ای که یک حافظه سریع مشترک است ،نشان میدهد که میتواند میان نخها به اشتراک گذاشتهشود.این حافظه میتواند به عنوان یک حافظه نهان مدیریت شده تحت دسترسی کاربر استفاده شود و پهنای باند بیشتری داریم یعنی امکان استفاده را از جستجو بافتی.
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