On Wednesday, March 20, Houston, Texas-based genomics researcher Erez Lieberman Aiden delivered a keynote address at the for the fourth-annual NVIDIA GPU Technology Conference (GTC) , which was held at the McEnery Convention Center in San Jose, Calif., March 18-21.
Dr. Lieberman Aiden is this summer about to become assistant professor in the Department of Genetics at the Baylor College of Medicine, and in the Department of Computer Science of Computational and Applied Mathematics at Rice University at Houston. He is also the principal investigator at the CUDA Research Centers at Baylor and Rice University. A fellow at the Harvard Society of Fellows, he recently invented a method for 3D genome sequencing, working with a team that created the first three-dimensional map of the human genome in 2009.
The GTC event is held to advance global awareness of GPU computing, computer graphics, game development, mobile computing, and cloud computing. Through world-class education, including hundreds of hours of technical sessions, tutorials, panel discussions, and moderated roundtables, GTC brings together thought leaders from a wide range of fields. event showcases breakthroughs in science and industry made possible with GPU technology.
GPU computing is the use of a GPU (graphics processing unit) together with a Central Processing Unit (CPU) to accelerate general-purpose scientific and engineering applications. Pioneered five years ago by NVIDIA, GPU computing has quickly become an industry standard, employed by millions of users worldwide and adopted by virtually all computing vendors. NVIDIA’s Compute Unified Device Architecture (CUDA) technology is a hardware specification for its General Purpose Graphics Processing Units (GPGPUs). GPGPUs are often called “GPUs” for historical reasons and for brevity.
The latest Tesla 20-series GPUs are based on the new implementation of the CUDA platform called the “Fermi architecture.” Fermi has key computing features such as 500+ gigaflops of IEEE standard double-precision floating-point hardware support, L1 and L2 caches, ECC memory error protection, local user-managed data caches in the form of shared memory dispersed throughout the GPU, and coalesced memory accesses.
Graphics chips started as fixed-function graphics processors but became increasingly programmable and computationally powerful, which led NVIDIA to introduce the first GPU. In the 1999-2000 timeframe, computer scientists and domain scientists from various fields started using GPUs to accelerate a range of scientific applications.
The GTC 2013 event provided hundreds of hours of keynotes, presentations, research posters, tutorials, and instructional sessions from top experts, as well as the Emerging Companies Summit, where some of the world’s most innovative startups showcase new technologies, plus networking events throughout the week, enabling experts to share information.
In his address, entitled “Why Life Is Like a Bowl of Noodles,” Dr. Lieberman Aiden discussed his work sequencing the human genome in 3D, which allows scientists to gain deep insights into gene behavior and fundamental biological processes of life, and how his team harnesses GPUs to accelerate the analysis of massive amounts of genomic information, and to simulate the physical process of genome folding, uncovering insights into gene expression that can now be used by thousands of researchers.
In an NVIDIA blog, Brian Caulfield reports that Dr. Lieberman Aiden explained how a strand of human DNA stretched out to its full length is two meters long., yet all that material – and the information it carries – is packed into the nucleus of a single human cell, and the way the material folds up in order to fit determines how the information carried on a strand of DNA is expressed. When things go right, DNA generates skin cells, blood cells, and brain cells. When they don’t go right, it can generate cancer cells.
DNA, Dr. Lieberman Aiden noted, can be compared to a block of ramen noodles, with both uncooked ramen and DNA inside our cells folded up into a shape called a “fractal globule” that allows the human body to implement this very dense ball of instructions — a discovery he and his researchers made with the help of NVIDIA’s GPUs, whose data-processing power enabled Lieberman Aiden and his team use a similar technique to analyze massive amounts of genomic information and simulate the physical process of genome folding, uncovering insights into gene expression that can be used by thousands of researchers about relationships between chunks of DNA that may seem far apart, when measured along the length of a strand of DNA, but may actually be quite close to one another when bunched up inside a nucleus. His work sequencing the human genome in 3D allows scientists to gain deep insights into gene behavior and fundamental biological processes of life.
Caulfield describes Dr. Lieberman Aiden as “a polymath who has made a career out of mixing different disciplines to come up with new insights,” notes that his brand of “wild cross-disciplinary insight” has shaken up the field of genomics.
Dr. Lieberman Aiden’s research has won numerous awards, including: one of the top 20 “Biotech Breakthroughs that will Change Medicine,” by Popular Mechanics; the Lemelson-MIT prize for the best student inventor; the American Physical Society’s Award for the Best Doctoral Dissertation in Biological Physics; and membership in Technology Review’s 2009 TR35, recognizing the top 35 innovators under 35. On his personal Web page, Dr. Lieberman Aiden says he’s looking for great scientists and postdocs to join his team — especially l molecular biologists, computer scientists, and biophysicists — but if you’re a really creative scientist of any variety, and interested in the sorts of things he does, he’d love to chat.