NVIDIA’s New AI Project To Help Cancer Treatment With Government Support; Decade’s Worth Research Done In 5 Years

First Posted: Nov 16, 2016 04:40 AM EST

U.S.-based technology giant NVIDIA announced on Monday that it is joining forces with the National Cancer Institute, the U.S. Department of Energy (DOE), and a number of other organizations to help accelerate cancer research. For this ambitious initiative, dubbed the Cancer Moonshot, the company will focus on building an artificial intelligence (AI) framework called CANDLE -- acronym for Cancer Distributed Learning Environment.

According to National Cancer Institute, Cancer Moonshot was originally announced by President Obama during the State of the Union debate earlier this year. The initiative is aimed to encourage scientists to achieve a decade's worth advancement in cancer research in just five years.

NVIDIA said that CANDLE will bring along a common cancer research and discovery platform that can benefit immensely from fast-evolving AI technologies. It takes advantage of the computing power facilitated by NVIDIA GPUs that typically power high-end gaming computers and design workstations.

CANDLE is based on Pascal, the new GPU architecture currently used by NVIDIA. It was launched earlier in 2016 and has seen high demands from AI researchers.

NVIDIA also announced that its computer scientists and engineers will collaborate with cancer researchers to make sure that CANDLE can make the best use of its powerful computing resources to expedite future studies on cancer.

The AI framework will focus on three key cancer research objectives:

  • To help researchers better understand the genetic signature in DNA and RNA so they can evaluate how individual patients will respond to certain cancer treatments even before the treatments begin.

  • Accelerated protein-interaction simulations that will help scientists' understanding of how protein interactions affect the early formation of cancer cells.

  • An in-depth analysis of the records of millions of cancer patients that could help build a comprehensive cancer surveillance database of disease metastasis and recurrence.

"NVIDIA is at the forefront of accelerated machine learning, and the new CORAL/Sierra architectures are critical to developing the next generation of scalable deep learning algorithms. Combining NVLink-enabled Pascal GPU architectures will allow accelerated training of the largest neural networks," said James M. Brase, Deputy Associate Director for Computation, Lawrence Livermore National Laboratory.

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