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3D News

For the last few years we’ve worked with the National Stereoscopic Association to support the 3D Digital Showcase photo competition featured at the NSA’s annual conventions. The images from this past year’s showcase are now live for everyone to view. We really enjoy the diversity of images submitted by 3D artists and enthusiasts to this event, and this gallery is certainly no different. You’ll see everything from close ups of insects to people juggling fire. Simply put,...
In driver 334.89 NVIDIA introduced a new proprietary rendering mode for 3D Vision that enables us to improve the 3D experience for many key DirectX 10 and 11 games. This mode is now called “3D Compatibility Mode”. We have continued to iterate on this feature in driver 344.11, increasing game support and adding some new interface elements. You can get the new driver at www.geforce.com/drivers or via the update option in Geforce Experience. With the release of 344.11, new 3D...
We’re fortunate enough to have another fine 3D video from New Media Film Festival to share with you here on 3DVisionLive—a pop music video from Italy called “The Way,” which you can view here. Even better, New Media Film Festival has provided an interview with one of the co-directors of the video, Edoardo Ballanti, which provides insights on how the video was created and the vision behind it. Enjoy! (Alice Corsi also co-directed the video.) What was the Inspiration behind “...
The Fall Photo Contest received nearly 100 images – thanks to all that entered! The contest called for your best “nature” shots with the only other requirement being that they had to be true stereo images. Submissions ranged from shots of spiders in gardens to artistic approaches to tasteful nudes. As before, members were invited to vote for the winner by tagging images in the contest gallery as favorites. Without further ado, the winner is: Autumn Goodbye to Summer This...
In driver 334.89 NVIDIA introduced a new proprietary rendering mode for 3D Vision that enables us to improve the 3D experience for many key DirectX 10 and 11 games. This mode is now called “3D Compatibility Mode”. We have continued to iterate on this feature in beta driver 337, increasing game support and adding a toggle key to enable/disable the mode. Games with 3D Compatibility Mode will launch in this mode by default. To change the render mode back to standard 3D Vision...

Recent Blog Entries

They say you should never meet your heroes. Well don’t listen to them, because we got to work with one of ours  — deadmau5 (Joel Zimmerman) — and it was awesome.

Joel is, of course, one of the world’s best-known electronic music artists. He’s also known for his playful sense of style. In addition to the signature “mau5” heads he wears when he performs, Joel has a collection of cars that can be mistaken for no one else’s.

The common thread: a love for technology. Joel integrates technology into everything he does — his music, his performances, and even his downtime.

“On my days off from making music I’m still at the same computer playing video games,” Joel says. “I would spend my free time there, I would do my work there, I would play games on it. Computers have been at the very core of my life.”

Time for an Upgrade

So when our own Kris Rey spotted Joel playing “Project Cars” on a PC with a tiny 24-inch screen, Kris knew we could do “so much better.” So we teamed up with Joel to make creating the ultimate “mau5 spec,” streaming lab — a home base for Joel’s online game streaming forays — our latest GeForce Garage project.

Joel inspired us to do what we love to do most: create technology that delights our fans. In the first part of our three-part video series NVIDIA creative director Jules Mann sits down with Joel to create designs that reflect Joel’s unique sense of style — and his love of cars. In the second part, you can watch some of the most skilled members of the PC modding community fabricate these one-of-a-kind PCs. And in the third, you’ll be able to see Joel’s reaction to our work.

Inside the World of deadmau5

Throughout the series, you’ll get a look inside Joel’s world as he talks about his love of gaming and cars — and how those two passions intersect. You’ll get a look inside Joel’s “mau5” head collection. And you’ll get to see what one of our generation’s most fascinating — and funny — musical artists thinks of the GeForce GTX 1080-powered gaming PCs we put together with him.

 

The post How We Built 5 Custom Gaming PCs for deadmau5 appeared first on The Official NVIDIA Blog.

Image recognition systems are growing increasingly sophisticated – but they don’t come close to matching the efficiency of the ones we carry around with us inside our skulls.

As part of an effort to close that gap, our Jetson TX1 embedded computing module swept both tracks of the recent Low Power Image Recognition Challenge, held in Austin, Texas, at the IEEE Rebooting Computing event.

We’ve invested substantial resources in the power efficiency of Jetson’s GPU compute architecture. In gaming and professional design, this means fluid framerates on a frugal power budget. But in the realm of computer vision, performance per watt enables rapid control loops and near real-time responsiveness from an autonomous machine, such as a drone or a robot.

The winners and organizers of LPIRC 2016.

The Low Power Image Recognition Challenge began when NVIDIA’s David Kirk and Yung-Hsiang Lu at Purdue University, decided that image recognition on a power budget was a worthy challenge. The first two years presented modest challenges, with smaller groups of researchers, Yung-Hsiang notes. He plans to expand the competition over the coming years, including larger prizes.

Power efficiency is essential to making certain sophisticated computer vision applications — like smart drones, head-mounted displays and object recognition capabilities for cell phones . People can identify objects (and do so much more) with a brain that consumes about 20 watts. By contrast, the best classifiers in the world run in supercomputers, data centers and workstations, which draw thousands of watts.

Maximizing Accuracy, Minimizing Power, with Jetson

On the day of the competition, contestants brought their hardware and logged into a server with a reference Python script. The server then delivered up to 20,000 images for each system to recognize in 10 minutes. The contest’s organizers connect each team’s hardware to a power meter.

The goal is to classify with the greatest accuracy, but using the least amount of power. The server calculates scores by dividing the accuracy of the classifier by the average power consumed by the device.

The contestants and organizers of LPIRC 2016.

This year’s winning team used a Jetson TX1 running the latest release of cuDNN 4.0. The team implemented Bing+ Fast-RCNN for Track 1 and Faster-RCNN within Caffe for Track 3.

“TX1 has all that we want from a mobile device: throughput, low power and flexibility to choose precision mode,” says Wang Ying, the principal investigator and advisor for the winning team. “There are a lot of CNN-based recognition frameworks emerging: fast-rcnn, yolo, ssd, etc. They provide enough options for us to find the most suitable one for both the challenge and the TX1 hardware.”

Winning Strategy: Keeping Jetson’s CPU and GPU Busy

Wang, a professor at the Chinese Academy of Sciences, says the key to success is balancing the workload between the CPU and the GPU, keeping both fully occupied at all times. Starting with NVIDIA Tesla K40 GPU accelerators, the team did a “design space exploration” to determine the best models to use on both desktop GPUs and the Jetson TX1 embedded system.

Through many iterations, they discovered that model pruning and singular value decomposition tended to reduce the size of their CNN models. The team also attempted to use cuFFT and the cuSparse to optimize their pipeline, but didn’t find this sort of approach to help their speed.

Smart. But researchers will have to exercise their minds a little more if we’re going to create image recognition systems that match the brain’s own efficiency, making this a contest to watch for years to come.

The post Jetson Wins by Landslide in Image Classification Efficiency Challenge appeared first on The Official NVIDIA Blog.