Breakthrough in HIV Research Enabled by NVIDIA GPU Accelerators
University of Illinois Team Uncovers New Approach to Combating Virus
Through World's Largest, Atomic-Level Computer Simulation
SANTA CLARA, CA -- (Marketwired) -- 05/29/13 -- Researchers at the
University of Illinois at Urbana-Champaign (UIUC) have achieved a
major breakthrough in the battle to fight the spread of the human
immunodeficiency virus (HIV) using NVIDIA(R) Tesla(R) GPU
accelerators, NVIDIA today announced.
Featured on the cover of the latest issue of Nature, the world's
most-cited interdisciplinary science journal, a new paper details how
UIUC researchers collaborating with researchers at the University of
Pittsburgh School of Medicine have, for the first time, determined
the precise chemical structure of the HIV "capsid," a protein shell
that protects the virus's genetic material and is a key to its
virulence. Understanding this structure may hold the key to the
development of new and more effective antiretroviral drugs to combat
a virus that has killed an estimated 25 million people and infected
34 million more.(1)
UIUC researchers uncovered detail about the capsid structure by
running the first all-atom simulation of HIV on the Blue Waters
Supercomputer. Powered by 3,000 NVIDIA Tesla K20X GPU accelerators --
the highest performance, most efficient accelerators ever built --
the Cray XK7 supercomputer gave researchers the computational
performance to run the largest simulation ever published, involving
64 million atoms.
"It would have been very difficult to run a simulation of this size
without the power of GPU-accelerated supercomputing in the Blue
Waters system," said Klaus Schulten, professor of physics at the
University of Illinois. "We started using GPU accelerators more than
five years ago, and GPUs have fundamentally accelerated the pace of
Designed to accelerate a broad range of scientific and technical
computing applications, NVIDIA Tesla GPU accelerators are enabling
researchers worldwide to make dramatic new breakthroughs across a
variety of scientific domains -- including alternative energy,
astrophysics, drug development, and climate research, among others.
They deliver significantly higher performance and better energy
efficiency as compared with CPU-based systems.
"GPUs help researchers push the envelope of scientific discovery,
enabling them to solve bigger problems and gain insight into larger
and more complex systems," said Sumit Gupta, general manager of the
Tesla Accelerated Computing Business Unit at NVIDIA. "Blue Waters and
the Titan supercomputer, the world's No. 1 open science supercomputer
at Oak Ridge National Labs, are just two of many GPU-equipped systems
that are enabling the next wave of real-world scientific discovery."
Capsid May Be Key to More Effective Drugs
With the planned addition
of more GPUs to the Blue Waters system, UIUC researchers expect to
increase simulation times, providing additional insight into the
structure and behavior of the HIV capsid.
The capsid has become an attractive target for the development of new
antiretroviral drugs, largely due to the discovery that Rhesus
monkeys have developed an immunity to HIV through a protein that
disrupts capsid functioning.
The capsid is the protein cell of a virus, containing the virus's
genetic material. It protects and "smuggles" the genetic material
into the human host cell. Once inside, it uncoats the material and
initiates the infection.
No existing HIV drug treatments are designed to target the capsid.
However, by providing a better understanding of the structure of the
HIV capsid, pharmacologists have a wealth of new information to
develop new and potentially more effective antiviral HIV drugs.
About NVIDIA Tesla GPUs
NVIDIA Tesla GPUs are massively parallel
accelerators based on the NVIDIA CUDA(R) parallel computing platform
and programming model. Tesla GPUs are designed from the ground up for
power-efficient, high performance computing, computational science
and supercomputing, delivering dramatically higher application
acceleration for a range of scientific and commercial applications
than a CPU-only approach.
To learn more about CUDA or download the latest version, visit the
CUDA website. Follow us on Twitter at @NVIDIATesla.
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