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The votes have all been cast and we can now, finally, bring you the results of our First Annual Summer Photo Contest. Dozen's of excellent images were submitted and it was a challenge to whittle all the entries down and select the prize winners. Without further ado we get to the results - drumroll please!   First Prize: "Soap Bubble" Zoran Zelic (ZZ3D)'s "Soap Bubble 1" takes the top prize. We like the spontaneity the image implies along with the overall composition...
Sometimes it’s just great “when a plan comes together.” An avid warbird photographer, I’d been familiar with Christian Kieffer’s outstanding pinup photography for years – his company produces some truly amazing nostalgic calendars featuring vintage WWII aircraft and models done up to mimic the pinups from the same era that helped to keep many an airman’s spirits high. Thinking the subject matter would lend itself well to 3D, I approached Christian a few months ago about...
The 2004 release of id Software’s Doom 3 spurred many PC gamers to upgrade their rigs – with many building completely new machines with the sole intent of driving this game at its ultimate eye-candy settings. And many gamers still came up a bit short, which is just one reason why they are looking forward to jumping into the corridor-crawling fray again with the release of Doom 3 BFG Edition.Silverlight.createObject("
We’ve rolled out a new look for the Photo page that updates the page to have a similar look and feel to the home and video pages. We’ve added a pane of larger thumbnails across the top that is user-navigable. Just click the right or left arrows to cycle. (We will be adding an auto-scroll mechanism to this soon.) And these are viewable in 3D - just click the 2D/3D toggle button at the top right of the page. Make sure to upgrade to the most recent drivers for best performance...
If you know the Trine series, you’re already salivating: the first downloadable content (DLC) for Trine 2 is now available! If you’ve not heard of Trine at all, then prepare yourself for a visual feast. Trine is a physics-based action game in which you can switch amongst three characters – each with distinct attributes – to come up with clever solutions to an array of challenges created by hazardous puzzles and threatening enemies. The platform-style gameplay is based on...

Recent Blog Entries

Black Friday is upon us, kicking off the holiday shopping season. While millions are scouring shopping malls for the best deals, GPU-powered technology from a promising startup, Cypheme, could be used to scrutinize the items in our carts to ensure they’re the genuine article.

Cypheme’s quest began when the mother of one of its four cofounders nearly died from taking counterfeit medicine. He and three friends — who had been working together on a different project in Silicon Valley — decided to start a crusade against counterfeit goods.

Counterfeiting is a worldwide problem, particularly affecting three major categories of products: drugs and medicines, luxury goods (including alcoholic beverages) and consumer electronics. Each can pose risks to consumer and worker safety, from dangerous side effects to toxic components. Yet the counterfeit industry generates hundreds of billions of dollars a year, according to the United Nations Office on Drugs and Crime.

“Counterfeiting is actually a big problem in society,” said Cypheme CEO Hugo Garcia-Cotte. “But since it doesn’t happen at our doorstep, we don’t talk about it.”

The Cypheme team realized that if they wanted to make a difference, they’d have to go to the source. Three-quarters of the world’s counterfeit goods from 2008 to 2010 originated in East Asia, particularly China, according to seizure data from the World Customs Organization. So they relocated to Hong Kong.

Picture perfect: Cypheme’s AI-based app can verify these pills as authentic with a smartphone camera. GPU-Powered Paper Trail

Cypheme’s appeal lies in the unobtrusive nature of its artificial intelligence-based counterfeit protection technology. It includes two components: a smartphone app and special traceable paper.

Following the paper trail: Cypheme’s AI technology recognizes the unique grain of a product’s paper label.

Factories include the traceable paper in a product’s packaging. Cypheme’s AI algorithms use a smartphone camera to recognize the individual grain of that piece of paper. Within seconds, the app can identify exactly which good is being scanned and when it was manufactured.

Speed is essential for this process, so as not to gum up the consumer’s purchasing decisions. Cypheme uses NVIDIA GPUs to accelerate its complex pattern recognition algorithm. This allows it to run at least 50 times faster than on a single CPU core.

“There is a point where CPUs are just out of the game,” said Garcia-Cotte.

Cypheme’s offering doesn’t mar the consumer product or require a relatively expensive, embedded RFID chip, yet it traces products with precision. The only requirement is an eight megapixel camera, which makes the solution available to nearly all smartphone users.

Thus far, Cypheme has been working with a major French luxury brand to protect 3 million products a year, and plans to expand into other counterfeit plagued sectors soon.

The post The Real Deal: How GPU-Accelerated Computing Is Putting a Crimp on Counterfeiting appeared first on The Official NVIDIA Blog.

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.