What Is Max-Q?

When SpaceX blasts a Falcon Heavy into orbit, it does more than just break payload records. It tests the rocket’s ability to withstand maximum mechanical stress from the physical pressure of pushing against all that air in those first minutes. In aerospace, that maximum dynamic pressure is referred to as Max-Q. Borrowing from the aerospace Read article >

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SoftBank May Sell Nvidia Shares — But Not Because of Crypto Downturn

Nvidia’s share price has fallen 48 percent since October. Now, rumors have surfaced that SoftBank plans to sell its 4.9 percent share in the leading graphics chip maker. Bloomberg reporting has cited anonymous sources who allege that SoftBank, which through its Vision Fund acquired around $3 billion in Nvidia shares in 2017, could sell all

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Ridiculously Fast New Processor for Autonomous Machines, Tasty Kebabs, Bring Crowd to NVIDIA HQ

AI Robots. Chicken kebabs. Ridiculously fast technology. Ah, the good things in life.

At an event that spanned everything from drones that autonomously fly through the air to bots that navigate our sidewalks to the software and semiconductors that power it all, we hosted last night our second public autonomous-machines meetup at NVIDIA’s new headquarters building.

NVIDIA’s Jesse Clayton welcomed more than 300 developers, entrepreneurs, investors and others to Wednesday evening’s event

The event marked the availability of the NVIDIA Jetson AGX Xavier module for next-gen autonomous machines. The module — the latest addition to the Jetson family of products — delivers 32 TOPS of performance, operates in as little as 10 Watts and fits in the palm of your hand.

“Compute is critically important for autonomous machines,” NVIDIA’s Jesse Clayton said, welcoming more than 300 developers, entrepreneurs, investors and others to the event.  “Jetson is how you get there.”

Humans weren’t the only ones invited to Wednesday’s meetup.

Developers can use Jetson AGX Xavier to build the autonomous machines that will solve some of the world’s toughest problems, and help transform a broad range of industries, Clayton explained. Millions are expected to come onto the market in the years ahead.

Consuming as little as 10 watts — about as much as a clock radio — the module enables companies to go into volume production with applications developed on the Jetson AGX Xavier developer kit, bringing next-gen robots and other autonomous machines to life.

Crowded house: conversations at the meetup continued late into the evening.

Jetson AGX Xavier comes as the Jetson ecosystem around it is growing fast. The number of developers using NVIDIA’s Jetson platform has grown 5x since March of 2017, while the number of Jetson customers has grown 6x to 1800 over the same timespan, Clayton said.

Twenty-five of those customers and ecosystem partners were at the event to tell their story, as the crowd noshed on chicken kebabs and house-made pita chips with tzatziki and olive tapenade. A few highlights:

  • Farm of the future — SMART AG’s Autocart module gives farm equipment an autonomous upgrade. The Iowa startup uses Jetson TX2 to help it system see as it navitages farms. It’s already allowing tractors to hustle out during harvest to pick up loads of freshly harvested grain, giving farm productivity an autonomous boost.
  • Self-flying camera — The Skydio R1 is more than just a camera. It uses six pairs of cameras to build a 3D map of its environment. This lets it identify, localize, and track people and cars, and predict movement up to four seconds in the future. The result: stunning videos of your latest, and greatest adventures.
  • Going the extra mile — Marble’s building a “last mile delivery solution,” or, put another way, this San Francisco-based startup creates robots that save you a schlep by bringing food to your doorstep. Its intelligent delivery robots reliably and securely transport things that you need and want in a way that is safe and accessible to everyone. Uses advanced sensors, including LIDAR and cameras, to carefully navigate sidewalks.

Attendees were impressed. “It’s like living in the future,” Terry Smith, from Liquid Robotics said as he looked around the meetup. Smith’s company makes autonomous vehicle that rely on wind and solar power to roam the oceans, autonomously. He said Jetson TX 2 has “revolutionized,” what his company can do.

Skydio was among the startups inspiring the meetup’s attendees with wild new ideas.

Others were scouting for breakthrough technology for even wilder projects. Attendees included Tad Morgan, whose company, Made In Space, is working to bring manufacturing to outer space; and Randy Gobbel, who works on deep learning at genomics startup Illumina, who is already experimenting with Jetson TX 2 and Xavier processors to “see what they can do.”

Maybe you’ll want to see for yourself, too. For more details see our NVIDIA embedded computing page.

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Ridiculously Fast New Processor for Autonomous Machines, Tasty Kebabs, Bring Crowd to NVIDIA HQ

AI Robots. Chicken kebabs. Ridiculously fast technology. Ah, the good things in life. At an event that spanned everything from drones that autonomously fly through the air to bots that navigate our sidewalks to the software and semiconductors that power it all, we hosted last night our second public autonomous-machines meetup at NVIDIA’s new headquarters Read article >

The post Ridiculously Fast New Processor for Autonomous Machines, Tasty Kebabs, Bring Crowd to NVIDIA HQ appeared first on The Official NVIDIA Blog.

RED Digital Cinema and NVIDIA Make 8K Movie Editing a Reality

Working with 8K video will be easier and more accessible than ever thanks to collaboration between RED Digital Cinema and NVIDIA revealed last night during an industry event at the historic Linwood Dunn Theater in Hollywood.

In front of leaders from Adobe, Colorfront, HP and others, RED and NVIDIA announced an NVIDIA CUDA-accelerated REDCODE RAW decode SDK that gives software developers and studios a powerful new way to work with 8K video.

“Our mission is to bring cinema-grade images and performance to content creators everywhere,” said Jarred Land, president of RED Digital Cinema. “RED, NVIDIA and our industry partners are leveling the playing field, making the technology for high-resolution processing and image quality accessible to everyone.”

While consumers are snapping up millions of 4K TVs each month and Netflix, Hulu, Amazon and others are streaming a growing tsunami of content in the format, 8K is becoming the new frontier in video with 100,000 8K TVs hitting the market this year.

But 8K’s real importance to video editors today is making 4K post-production more flexible. “Overshooting” resolution lets creators do more with their footage such as stabilize, pan, crop and zoom in on the best parts of a shot. Compositors can benefit from more precise masks for keying and image tracking.

Just downsampling from 8K to 4K reduces artifacts, such as noise, and produces higher quality visuals. The fact 8K is exactly four times the size of 4K makes the operation much simpler.

Yet, as 8K production has increased, the need for massive CPU processing power or single-purpose hardware like the RED ROCKET-X puts it beyond reach for most content creators. That’s changing.

Opening the Door to 8K Editing

Earlier this year, NVIDIA and RED announced an initiative to accelerate 8K video processing by offloading the compute-intensive decoding and debayering of REDCODE RAW footage onto a single NVIDIA GPU.

At last night’s event, these real-time, 24+ frames per second capabilities were demonstrated running on an NVIDIA Quadro RTX 6000 GPU to play back, edit and color-grade RAW 8K footage on a system with a single-CPU HP Z4 Workstation — eliminating the need for either a $6,750 RED ROCKET-X or a $20,000 dual-processor workstation.

This 8K performance is also available with NVIDIA TITAN RTX or GeForce RTX 2080 Ti GPUs, so editors can choose the right tools for their budget or shooting location.

NVIDIA GPUs are the only solutions capable of playing RED MONSTRO’s 8192×4320 frames at 24 FPS with no pre-caching or proxy generation. The GPU is processing every frame as it needs it, so jumping around the timeline is quick and responsive, and scrubbing is smooth.

And the acceleration isn’t limited to 8K — the new SDK runs across a variety of legacy GeForce, TITAN and Quadro desktop and notebook GPUs, benefiting 4K, 5K and 6K workflows as well.

Colorfront, a pioneer in 8K workflows, was also on-hand to demonstrate faster-than-realtime RAW processing and 8K playback in HDR.

“Colorfront has been shipping 8K-capable systems for several years now and we are delighted to join with RED and NVIDIA and other industry leaders to celebrate a faster, more streamlined future for 8K,” said Colorfront managing director Aron Jaszberenyi. “With the new RED SDK allowing wavelet decompression on NVIDIA GPUs, Colorfront can do all the RAW processing in GPU and output 8K video (up to 60p) using AJA Kona5 video cards. With this latest advance – faster-than-realtime Debayer and decompression of 8K RAW footage, with simultaneous display of the 8K image on an 8K HDR monitor – Colorfront and our partners have achieved a significant milestone.”

Filmmakers and content creators are excited about the advances taking place.

“A few years ago, things like real-time playback or real-time encoding when exporting footage was not even possible,” said Director and Cinematographer Phil Holland. “As GPUs advanced further, this has empowered content creators to receive these performance gains in much more modest systems. Working in native raw formats, real-time effects, significantly faster exports, as well as much faster in application playback have all been huge time savers as digital cinema cameras advanced from 4K to 5K, to 6K, to 8K and likely beyond.”

Availability

Released RED R3D SDK and REDCINE-X PRO software are planned to be available at the end Q1 2019.  Beta versions of the SDK have been made available to major third parties to support integration. Stay tuned for more details on REDCINE-X PRO beta.

The post RED Digital Cinema and NVIDIA Make 8K Movie Editing a Reality appeared first on The Official NVIDIA Blog.

RED Digital Cinema and NVIDIA Make 8K Movie Editing a Reality

Working with 8K video will be easier and more accessible than ever thanks to collaboration between RED Digital Cinema and NVIDIA revealed last night during an industry event at the historic Linwood Dunn Theater in Hollywood. In front of leaders from Adobe, Colorfront, HP and others, RED and NVIDIA announced an NVIDIA CUDA-accelerated REDCODE RAW Read article >

The post RED Digital Cinema and NVIDIA Make 8K Movie Editing a Reality appeared first on The Official NVIDIA Blog.

Now Available: NVIDIA Jetson AGX Xavier Module for Next-Gen Autonomous Machines

Delivery robots that speed orders right to your door. Manufacturing robots that collaborate with humans. Handheld DNA sequencers that help scientists save crops from disease. These machines are among the first to make the leap from sci-fi into reality, thanks to the latest advances in the NVIDIA Jetson AGX Xavier platform. And the massive AI Read article >

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Now Available: NVIDIA Jetson AGX Xavier Module for Next-Gen Autonomous Machines

Delivery robots that speed orders right to your door. Manufacturing robots that collaborate with humans. Handheld DNA sequencers that help scientists save crops from disease.

These machines are among the first to make the leap from sci-fi into reality, thanks to the latest advances in the NVIDIA Jetson AGX Xavier platform.

And the massive AI capabilities powering them is moving within reach of a multitude of devices with the availability today of the Jetson AGX Xavier module, the latest addition to the Jetson TX2 and TX1 family of products.

Developers can use Jetson AGX Xavier to build the autonomous machines that will solve some of the world’s toughest problems, and help transform a broad range of industries. Millions are expected to come onto the market in the years ahead.

Workstation Performance, Clock-Radio Energy Consumption

The Jetson AGX Xavier module can serve as the powerful brain behind any bot you dream up. It delivers the performance of a workstation server in a computer that fits in the palm of your hand.

Consuming as little as 10 watts — about as much as a clock radio — the module enables companies to go into volume production with applications developed on the Jetson AGX Xavier developer kit, bringing next-gen robots and other autonomous machines to life.

Software Makes Hard Impact

The Jetson AGX Xavier module leverages NVIDIA’s world-class AI platform, which is used for numerous AI applications. This includes a complete set of tools and workflows to help developers quickly train and deploy neural networks.

It supports applications developed with the JetPack and DeepStream software development kits. JetPack is NVIDIA’s SDK for autonomous machines and includes support for AI, computer vision, multimedia and more.

The DeepStream SDK for Jetson AGX Xavier enables streaming analytics, bringing AI to IoT and smart city applications. Developers can build multi-camera and multi-sensor applications to detect and identify objects of interest, such as vehicles, pedestrians and cyclists.

These SDKs save developers and companies time and money, while making it easy to add new features and functionality to machines to improve performance.

With this combination of new hardware and software, it’s now possible to deploy AI-powered robots, drones, intelligent video analytics applications and other intelligent devices at scale.

Industry Support

Early users of Jetson AGX Xavier are praising its incredible processing capability and power efficiency.

It’s central to handling DNA sequencing in real time for Oxford Nanopore, a U.K. medical technology startup.

“We’re using Jetson AGX Xavier for our MinIT hand-held AI supercomputer, which is used to perform real-time analyses with the MinION, a powerful handheld DNA sequencer,” said Gordon Sanghera, CEO of Oxford Nanopore. “MinIT can be nearly 10 times more powerful than standard laptops and brings portable, real-time sequencing to more people in more locations.”

And Japan’s DENSO, a global auto parts maker, believes that Jetson AGX Xavier will be key to helping it introduce a new wave of efficiency into its operations.

“DENSO can leverage its long history in auto parts manufacturing to bring AI to factories, boosting productivity and efficiency while increasing workplace safety,” said Katsuhiko Sugito, executive director of DENSO Corp. “We believe that Jetson AGX Xavier will be the key platform driving this initiative.”

All in the Family

NVIDIA Jetson AGX Xavier family
NVIDIA Jetson solutions offer performance levels and prices to suit a variety of autonomous robotic applications.

The Jetson AGX Xavier module brings accelerated computing capability to the Jetson family, which includes solutions at different performance levels and prices to suit a variety of autonomous robotic applications.

The Jetson TX2 embedded module for edge AI applications now comes in three versions: Jetson TX2, Jetson TX2i and the newly available, lower cost Jetson TX2 4GB. Jetson TX1-based products can migrate to the more powerful Jetson TX2 4GB at the same price.

NVIDIA developer kits are also available for each member of the Jetson family. With these kits, companies can create and deploy multiple applications for a variety of use cases, using one unified software architecture.

Adventure Awaits: Start Creating Today

The Jetson AGX Xavier module is available today from distributors worldwide. Volume pricing of quantities of 1,000+ units is $1,099.

For more details, including system specs and software, see our Jetson page.

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NVIDIA Sets Six Records in AI Performance

NVIDIA has set six AI performance records with today’s release of the industry’s first broad set of AI benchmarks. Backed by Google, Intel, Baidu, NVIDIA and dozens more technology leaders, the new MLPerf benchmark suite measures a wide range of deep learning workloads. Aiming to serve as the industry’s first objective AI benchmark suite, it Read article >

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NVIDIA Sets Six Records in AI Performance

NVIDIA has set six AI performance records with today’s release of the industry’s first broad set of AI benchmarks.

Backed by Google, Intel, Baidu, NVIDIA and dozens more technology leaders, the new MLPerf benchmark suite measures a wide range of deep learning workloads. Aiming to serve as the industry’s first objective AI benchmark suite, it covers such areas as computer vision, language translation, personalized recommendations and reinforcement learning tasks.

NVIDIA achieved the best performance in the six MLPerf benchmark results it submitted for. These cover a variety of workloads and infrastructure scale – ranging from 16 GPUs on one node to up to 640 GPUs across 80 nodes.

The six categories include image classification, object instance segmentation, object detection, non-recurrent translation, recurrent translation and recommendation systems. NVIDIA did not submit results for the seventh category for reinforcement learning, which does not yet take advantage of GPU acceleration.

A key benchmark on which NVIDIA technology performed particularly well was language translation, training the Transformer neural network in just 6.2 minutes. More details on all six submissions are available on the NVIDIA Developer news center.

NVIDIA engineers achieved their results on NVIDIA DGX systems, including NVIDIA DGX-2, the world’s most powerful AI system, featuring 16 fully connected V100 Tensor Core GPUs.

NVIDIA is the only company to have entered as many as six benchmarks, demonstrating the versatility of V100 Tensor Core GPUs for the wide variety of AI workloads deployed today.

“The new MLPerf benchmarks demonstrate the unmatched performance and versatility of NVIDIA’s Tensor Core GPUs,” said Ian Buck, vice president and general manager of Accelerated Computing at NVIDIA. “Exceptionally affordable and available in every geography from every cloud service provider and every computer maker, our Tensor Core GPUs are helping developers around the world advance AI at every stage of development.”

State-of-the-Art AI Computing Requires Full Stack Innovation

Performance on complex and diverse computing workloads takes more than great chips. Accelerated computing is about more than an accelerator. It takes the full stack.

NVIDIA’s stack includes NVIDIA Tensor Cores, NVLink, NVSwitch, DGX systems, CUDA, cuDNN, NCCL, optimized deep learning framework containers and NVIDIA software development kits.

NVIDIA’s AI platform is also the most accessible and affordable. Tensor Core GPUs are available on every cloud and from every computer maker and in every geography.

The same power of Tensor Core GPUs is also available on the desktop, with the most powerful desktop GPU, NVIDIA TITAN RTX costing only $2,500. When amortized over three years, this translates to just a few cents per hour.

And the software acceleration stacks are always updated on the NVIDIA GPU Cloud (NGC) cloud registry.

NVIDIA’s Record-Setting Platform Available Now on NGC

The software innovations and optimizations used to achieve NVIDIA’s industry-leading MLPerf performance are available free of charge in our latest NGC deep learning containers. Download them from the NGC container registry.

The containers include the complete software stack and the top AI frameworks, optimized by NVIDIA. Our 18.11 release of the NGC deep learning containers includes the exact software used to achieve our MLPerf results.

Developers can use them everywhere, at every stage of development:

  • For data scientists on desktops, the containers enable cutting-edge research with NVIDIA TITAN RTX GPUs.
  • For workgroups, the same containers run on NVIDIA DGX Station.
  • For enterprises, the containers accelerate the application of AI to their data in the cloud with NVIDIA GPU-accelerated instances from Alibaba Cloud, AWS, Baidu Cloud, Google Cloud Platform, IBM Cloud, Microsoft Azure, Oracle Cloud Infrastructure and Tencent Cloud.
  • For organizations building on-premise AI infrastructure, NVIDIA DGX systems and NGC-Ready systems from Atos, Cisco, Cray, Dell EMC, HP, HPE, Inspur, Lenovo, Sugon and Supermicro put AI to work.

To get started on your AI project, or to run your own MLPerf benchmark, download containers from the NGC container registry.

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