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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 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...
3DVisionLive’s first-ever short-form 3D video contest received 14 entries that showed a great deal of diversity, ranging from video game captures to commercial-style clips to raw captures of pets or people doing cool things (such as bashing each other with swords). During judging we laughed, we cried (okay, maybe not), and we simply scratched our heads…. But seriously: thank-you to all that participated and we hope to see more of your content uploaded to the site for all to...

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Genetic interpretation. Giant datasets. Deep learning. This is cancer research, beyond the microscope.

A team at the University of Toronto, led by Dr. Brendan Frey, is advancing computational cancer research by developing a “genetic interpretation engine” – a GPU-powered, deep learning method for identifying cancer-causing mutations.

Today the NVIDIA Foundation, our employee-driven philanthropy arm, awarded Frey and his team a US$200,000 grant to further that work — and help them usher in an era of personal and effective cancer care.

Compute the Cure

Cancer kills almost 600,000 people each year in the U.S. alone. It can be caused by any one of an endless variety of mutations, across many different genes. This can make it hard to identify quickly and treat in a highly targeted way.

As computers grow more powerful, scientists are delving into giant datasets and deploying computer simulations to research how cancer develops.

Part of our “Compute the Cure” initiative, the NVIDIA Foundation’s grant will help Frey’s team scale up their GPU-powered methods so they can be applied to a large number of personal genomes in clinical settings, ultimately involving hundreds of thousands of genomes.

“To make a big difference in genomic medicine, we’ve developed GPU-accelerated technologies for the computationally intensive work,” Frey said. “Now, we’re focused on the next step — to change the lives of patients stricken with cancer — by experimentally validating our technologies using data from these patients.”

Frey’s team, including Leo J. Lee (far left) and Brendan J. Frey (second from right) plan the software architecture of a computational splicing predictor.

Leo Lee, a senior research associate in Frey’s lab, will manage the deployment of GPU-accelerated computational tools and the development of clinical experiments to validate them. Andrew Delong, who co-developed some of tools as a postdoctoral fellow in Frey’s lab, will advise the team on tool deployment and clinical validation.

In addition to demonstrating the utility of the tools in cancer biology, the team will ensure that libraries are freely available for use by other biomedical researchers working on cancer and other genetic diseases, according to Delong.

The university team used servers with eight each of NVIDIA Tesla K80, K40 and K20 GPU accelerators, plus several desktop machines with NVIDIA GeForce GTX TITAN X graphics cards.

Overcoming Roadblocks Depiction of an RNA molecule being transcribed from DNA, juxtaposed with an artificial neural network interpreting the genomic sequence.The computations performed by the neural network run inside NVIDIA GPUs.

The team’s computational approach aims to overcome some of the roadblocks in personalized medicine.

At present a patient’s cancer-causing “driver” mutations have to be identified and separated from their many benign cancer-caused “passenger” mutations.

Today, a highly trained genome diagnostician can spend hours trying to understand the impact of a single mutation, pouring through databases and research papers, often coming up empty-handed.

Deep learning can help identify driver mutations more quickly, consistently and accurately than ever before. In other words, it allows human diagnosticians to scale.

The team’s approach to predicting cancer “hot spots” can learn from new genomes going forward, and, by exposing it to new data, can be trained to find causal mutations for other diseases.

With genomics data now being collected in unprecedented quantities, the University of Toronto’s project represents a groundbreaking way to analyze and gain insights from it.

“The crucial next step is validating that it works and building the clinical bridge,” Frey said. “Then the technology can be used widely and help change the lives of people with cancer.”

For more on the team’s work, watch the TedX talk by Frey.

The post University of Toronto Receives $200K NVIDIA Foundation Award for Cancer Research appeared first on The Official NVIDIA Blog.

Design visualization and virtualization are two of the key topics at next week’s Autodesk University, in Las Vegas – and NVIDIA experts will be there to help.

We’ll be showcasing, with our partners, the latest NVIDIA Iray physically based rendering technology. It lets designers, artists and architects accurately predict their final creations  by maximizing the effectiveness of GPUs – be they local, on the network or in the cloud.

At the show, you can see demos of Iray plug-in –  which enable you to predictably visualize and iterate on designs with unprecedented photorealism and speed – running on HP Z840, Dell T7910 and Lenovo P900 workstations.

There’ll also be:

  • New NVIDIA Quadro mobile GPUs powering the latest mobile workstations from BOXX, Dell, HP, Lenovo and MSI.
  • NVIDIA Iray for 3ds Max on BOXX workstations showing how physically based rendering technology can help architects and designers avoid costly design flaws, like London’s Death Ray.
  • NVIDIA GRID technology running Autodesk AutoCAD , Revit and other software applications, via Citrix and VMware hypervisors, on Dell Precision Rack servers.

And in the Open Lab, attendees can test drive favorite Autodesk apps running remotely from the cloud on NVIDIA, Dell and VMware virtualization technology.

We’re also helping to lead some informative classes, including:

Finally, we’re kicking off phase two of Project Soane with HP, a rendering contest to bring to life the historic Bank of England building based on a recently crowd-sourced Revit model of Sir John Soane’s neo-classical design.

Visit the BOXX, Citrix, Dell, GPL, HP, Lenovo, MSI and VMware booths to see how NVIDIA graphics technologies deliver the best performance and visual experience for Autodesk customers.

Keep up with NVIDIA at the event by following us on Twitter @NVIDIA_MFG.

The post Best in Class: NVIDIA Heads to Autodesk University appeared first on The Official NVIDIA Blog.