How GPU-Driven Drug Discovery is Finding New Targets to Cure Cancer


The NVIDIA Blog

Posted: 20 Mar 2015 11:06 AM PDT
The race is on to understand how cell mutation causes cancer, which kills hundreds of thousands worldwide each year and is the second leading cause of death in the U.S.
Setting the pace is Rommie Amaro, associate professor at the University of California, San Diego, whose research on how to interrupt the mutation process is aided by high-performance computers.
Amaro is focused on the anti-cancer drug discovery pipeline using advanced molecular dynamics simulations powered by GPUs. The work recently earned her a $200,000 grant as part of the NVIDIA Foundation's Compute the Cure initiative.
"Enormous gains in computing power are enabling a new framework for drug discovery," Amaro said in a presentation she gave at our GPU Technology Conference this week.
Recent work involves using computer simulations to capture various shapes of a tumor suppressor, the protein called p53. It's known as "the guardian of the genome" because it's a key regulator of cell growth and development in normal cells.
In its healthy form, p53 helps with cell repair or triggers cell death if the damage is too great. When p53 doesn't function properly, or mutates, it allows cancer cells that it would normally attack to escape.
"P53 is a protective cell, usually," Amaro said. "But in more than 50 percent of human cancers, if this cell is damaged, tumors grow."
Computer simulations capture not just how proteins are built, but how they function inside the body. The simulations run on GPU-powered computers revealed a new "binding site" that may help cancer researchers create new drugs to help "reactivate" p53 when it mutates and doesn't do its job.
The computational approach led to the discovery of "p53 reactivation compounds in six months, compared to all the research efforts of the previous 20 years combined," she said. "This is a great example of the power of the model."
By building shareable computer-aided drug discovery workflows, her team can create recipes that other researchers can follow to find new drug targets or reproduce the work done by their peers.  The goal: to accelerate the discovery of new and safer medicines to fight cancer.
"Cancer is a big complex disease and it'll take as many people as possible to come up with cures," Amaro said.

The post How GPU-Driven Drug Discovery is Finding New Targets to Cure Cancer appeared first on The Official NVIDIA Blog.
Posted: 20 Mar 2015 10:00 AM PDT
Search and rescue ain't what it used to be.
Gone are the days of rescue teams and their dogs heading into dangerous situations not knowing what they're going to face. Technology has transformed the art of rescue into a science.
One key advance has been the use of robotic devices, which do everything from evaluating surroundings to assessing the situation of those who need help.
But as Pawel Musialik, a programmer and researcher at Poland's Institute of Mathematical Machines (IMM), told attendees during a session at the GPU Technology Conference, getting the most out of these robots takes planning.
"We want to provide tools for rescue teams to get the best use of unmanned platforms," Musialik said. "They're not experts in software development."

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Pawel Musialik talks about how to use GPUs to use rescue robots more effectively.

IMM is one of a handful of entities that comprise the Integrated Components for Assisted Rescue and Unmanned Search operations (ICARUS) project.
Formed after the 2011 earthquake and tsunami in Japan, ICARUS is a joint research effort spearheaded by the European Commission to make the use of robots more practical during search-and-rescue efforts.
Musialik and IMM have been working on developing systems that will help search-and-rescue teams direct ground and aerial robots with less pre-mission preparation.
That means enabling robots to categorize classes of objects (buildings or vegetation, say), understand the relationships between those objects (overlapping or adjacent) and then operate based on rules to make determinations such as whether a situation is unsafe.
The hardware IMM is using takes advantage of NVIDIA GPUs and the CUDA parallel processing architecture. Rugged computers equipped with two NVIDIA GRID K2 cards are combined with GeForce GTX-powered laptops.
Pulling data from sources such as geographical information systems and ground and aerial point clouds, IMM has established models that help instruct robots in real time. That information, combined with detailed graphical visualizations, is creating more informed rescue robots, Musialik said.
"We couldn't do point classifications with CPUs," he said. For instance, Musialik showed an example of a CPU-generated image in which the software couldn't distinguish between a monument and surrounding vegetation. Once a GPU was added to the equation, the monument was clearly identified.
With GPUs, they can get the system to feed robots increasingly granular data.
The moral: If you ever find yourself trapped in a crumbled building or deep ravine, worry not. GPU-powered robots may be on their way.
The post How GPUs Help Rescue Robots Find Their Way appeared first on The Official NVIDIA Blog.
Posted: 19 Mar 2015 06:25 PM PDT
Six promising startups walked away with cash and prizes worth more than $650,000 at NVIDIA's eighth annual Emerging Companies Summit.
More than 50 startups participated in the competition, selected from a field of more than 150 applicants from 30 countries. The event is a regular highlight of NVIDIA's GPU Technology Conference, in Silicon Valley, which drew more than 4,000 attendees.
This year's award winners included:
  • Ersatz Labs – Makes deep learning accessible through a web-based user interface and API. (U.S. based.)
  • QM Scientific – Makes shopping easier by showing the best places to shop based on price, quality or location. (U.S. based.)
  • Viontech  – Creates embedded systems for transport, video surveillance, business intelligence (China based.)
  • Herta Security – Facial recognition software for surveillance and security (Spain based.)
  • Clarifai – Image-recognition software for deep learning (U.S. based.)
Each received $15,000 in legal services from Cooley, $60,000 worth of Microsoft's Windows Azure for BizSpark Plus, an NVIDIA Tesla K40 GPU worth $5,000, and a trophy. But perhaps more valuable is the prestige and visibility that comes from being recognized as one of the world's more innovative startups.
A sixth startup, Artomatix, won the $100,000 Early Stage Challenge at the event for the most promising young startup. The Dublin, Ireland-based company automates artwork creation for video games.
The post Six Startups Split $650,000 in Prizes at Emerging Companies Summit appeared first on The Official NVIDIA Blog.
Posted: 19 Mar 2015 02:25 PM PDT
Andrew Ng doesn't think robots will kill us. But they might take our jobs.
"Maybe in hundreds of years, technology will advance to a point where there could be a chance of evil killer robots," said Ng, a leading machine learning researcher and chief scientist at Baidu, in his keynote speech at the GPU Technology Conference Thursday.
"But I don't work on preventing artificial intelligence from going evil for the same reason I don't work on solving the problem of overpopulation on the planet Mars," he said.
Recent breakthroughs have given machines uncanny new abilities, ones that will have a huge impact in the near future.
But they've also raised concerns. Thinkers ranging from physicist Stephen Hawking to Microsoft co-founder Bill Gates and Tesla Motors CEO Elon Musk have warned that the emergence of machine intelligence poses a threat to humanity.
Ng, who was named by Time magazine as one of the world's 100 most influential people, doesn't see his work posing a threat anytime soon.
"Rather than being distracted by evil killer robots, the challenge to labor caused by these machines is a conversation that academia and industry and government should have," he said.
Ng compared the explosion in machine learning—driven by vast pools of data and powerful GPUs—to a rocket.
Faster computers—powered by GPUs—provide the rocket engine. Vast sums of data provide the fuel.
Pumping that fuel through ever more powerful engines results in rocket that can take researchers farther, faster.

Riding the rocket: GPUs are one of the factors propelling machine learning forward, Baidu Chief Scientist Andrew Ng said.
Rocket Ride: GPUs are one of the factors propelling machine learning forward, Baidu Chief Scientist Andrew Ng said.

The result is machines that are already able to perform tasks better than humans, like identifying scenes in photographs.
“We think that Baidu and other organizations are well beyond what humans are able to achieve on tasks that humans are really good at," Ng said.
Ng is leading Silicon Valley research efforts at Baidu and continues to teach computer science at Stanford University. Prior to Baidu, he led the Google Brain project.
He's among a handful of researchers who have used GPUs to spark a renaissance in deep learning that has given computers the ability to do things—like recognize images and translate speech—that seemed impossible just a few years ago.
While deep learning is complicated stuff, Ng provided a simple explanation for how it works—and why so many breakthroughs have happened in the past few years.
One factor: ubiquitous electronic devices are generating vast pools of user generated data—images, speech, video—that can be crunched by researchers.
The other factor: More sophisticated deep learning networks, supported by ever more powerful processors. These networks are very loosely modeled on the human brain—which Ng pointed out that we know very little about—and are arranged into layers that categorize the information streamed through them by researchers.
GPUs play a key role here by helping researchers feed this data to their models more quickly, giving them the ability to try out new network architectures faster, and build systems that can sort everything from speed to video quickly.
Researchers are still trying to understand how this technology can be applied. But Ng sees deep learning sparking breakthroughs in a wide range of industries, from medical imaging to transportation.
"I hope you will have grandchildren who will come to you and ask 'Is it really true that when you were young and you came home and said something to your microwave that it just would sit there?'"
Meanwhile, smarter machines can help us with challenges people face in the present. Ng compared mastery of machine learning to a super power, a power that's already helping people like Li Chongyang, a blind man who uses speech recognition to listen to music and place phone calls on his smart phone.
"You have superpowers," Ng told his GTC audience. "I hope you all go home and use your superpowers to create the greatest possible good for humanity."

The post Riding the AI Rocket: Robots Won't Kill Us, Says Top Artificial Intelligence Researcher appeared first on The Official NVIDIA Blog.
Posted: 19 Mar 2015 02:02 PM PDT
With diversity in high-tech one of the day's hottest issues, this week's GPU Technology Conference highlights how some women are beating the odds.
Despite being highly under-represented in the field, they're showcasing breakthrough work in GPU computing during sessions including cancer research, video technologies and image recognition.
Nearly 100 female researchers, professors and engineers came together at the Women@GTC event Wednesday at our GPU Technology Conference to discuss women who innovate and how to help inspire female students to pursue careers in technology.
Among the attendees was Rommie Amaro, associate professor at the University of California, San Diego, who is leading research on how to interrupt the mutation process in cells that cause cancer, aided by high-performance computers.
The work, presented by Amaro at GTC, is focused on the anti-cancer drug discovery pipeline using advanced molecular dynamics simulations powered by GPUs. It recently earned her a $200,000 grant as part of NVIDIA's Compute the Cure award.
GPUs are also helping keep us traveling safely. Fanny Nina-Paravecino, a Ph.D. candidate and research assistant in computer engineering at Northeastern University, is using Hyper-Q for real-time image segmentation for luggage scanning at airports.
Other GTC presenters include Chen Sagiv, CEO of SagivTech Ltd., which deploys multiple video sources to create high-quality 3D video scenes that can be shared via social networks. Deborah Bard from SLAC National Accelerator Laboratory uses desktop GPUs to study the structure and evolution of the universe. And Ying Liu, an associate professor at the University of Chinese Academy of Sciences, uses GPUs to accelerate collaborative filtering algorithms.
NVIDIA CEO Jen-Hsun Huang participated in the event, and shared his science-driven way of thinking about how to add value to the company with more inclusive practices. "Believing in something isn't enough, you have to have a system in place to make it happen," he said.
One effort beyond recruitment is a drive to retain women in the technology sector. Showing the world what inspires those working in technology about their jobs is perhaps the best way to find the best candidates, women or men, Huang said. In the end, it's the product that counts because when you see a line of code, you don't know who wrote it, he added.
"Science is a ticket to the world. It's a common language, like music," said Women@GTC panelist Pinar Muyan-Ozcelik, assistant professor of Computer Science at Sacramento State University.
Panelist Fernanda Foertter, an HPC user support specialist at Oak Ridge National Laboratory, noted "one way to increase different points of view is to be inclusive of different points of view." An inclusive work environment in technology means creating and supporting a network that encourages hiring individuals from broad backgrounds.
Panelists suggested several key factors to creating an inclusive environment: ensuring work environments that are family, not just women, friendly; projecting female role models for others to see; and using appropriate language when recruiting — avoiding "hacker," for example, which few women identify with, and replacing it with "problem-solver."
Panelist Lorena Barba, associate professor of mechanical and aerospace engineering at George Washington University, echoed these sentiments, noting that women in science must think of themselves as leaders, because "a leader can imagine the future."
The post Women@GTC Focus on Innovation, Inspiration and Roadmap for Inclusion appeared first on The Official NVIDIA Blog.
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