The effort is being led by David E. Shaw, a billionaire computer scientist. In the 1990s, Mr. Shaw was one of the most successful of an elite group of technologists pursuing computer-based trading strategies on Wall Street. Several years ago Mr. Shaw, who is also a major investor in Schrdinger, a chemical simulation software firm, stepped away from day-to-day management of his investment firm, D. E. Shaw & Company. He is now chief scientist of D. E. Shaw Research. It could be used to investigate problems of great scientific interest, like the folding of protein molecules, and in the design of drugs based on the simulated biological activity of different molecules.
Note: This is what billionaires and near billionaires should be doing funding grand technological and scientific research projects that could create huge advances for civilizations capabilities. Fund high leverage, high risk and high potential world changing projects. SENS still needs another billionaire or two and Robert Freitas and Ralph Merkle need one to enable rapid develop of their diamond mechanosynthesis work.
The ability to perform long, accurate molecular dynamics (MD) simulations involving proteins and other biological macro-molecules could in principle provide answers to some of the most important currently outstanding questions in the fields of biology, chemistry, and medicine. A wide range of biologically interesting phenomena, however, occur over timescales on the order of a millisecond—several orders of magnitude beyond the duration of the longest current MD simulations.
We describe a massively parallel machine called Anton, which should be capable of executing millisecond-scale classical MD simulations of such biomolecular systems. The machine, which is scheduled for completion by the end of 2008, is based on 512 identical MD-specific ASICs that interact in a tightly coupled manner using a specialized highspeed communication network. Anton has been designed to use both novel parallel algorithms and special-purpose logic to dramatically accelerate those calculations that dominate the time required for a typical MD simulation. The remainder of the simulation algorithm is executed by a programmable portion of each chip that achieves a substantial degree of parallelism while preserving the flexibility necessary to accommodate anticipated advances in physical models and simulation methods.
Simulations of processes like the folding of proteins into three-dimensional structures or the interactions between proteins or between a protein and a drug molecule hold out the promise of advancing science and drug development. However, each simulation must be validated by experimental scientists in a laboratory setting. Thus one of the principal advantages of increased speed in simulations that now take thousands of hours on the fastest supercomputers is to speed the time to the laboratory.
Scientists said the real value of Anton might not be known until they find out what the machine can do. “Only after Anton van Leeuwenhoek used his microscope did he see protozoa in the pond water,” said Roger Brent, director of the Molecular Sciences Institute, an independent research laboratory in Berkeley, Calif.
If the time steps are too long, individual atoms run into each other, get higher energy configurations, and everything becomes unstable. For each individual step, you must compute the interaction between all pairs of particles, determined by molecular force fields. Then you must move each atom a tiny bit and repeat the process a huge number of times.
Two approaches to protein-folding simulation include simulating many short trajectories and simulating one very long MD trajectory. While both approaches are complementary, Shaw’s group practices the second approach, which requires enormous amount of parallelism. To reach their goal of simulating a full millisecond requires an enormous increase in speed — 10,000 times more speed than single-processors, and 1000 times the speed of the best existing parallel implementations. “We are several orders of magnitude from where we need to be,” said Shaw.
Shaw’s lab has also created specialized software, dubbed Desmond, for MD. It’s developed to run on Anton but the algorithm can be adapted to run on computational clusters
Shaw cautioned that we don’t know enough about the accuracy of molecular force fields, and that maybe after 100 or so microseconds, a small inaccuracy in the force field calculation “would lead to a very fast way of getting the wrong answer.”
From HPCwire review of the Newport conference
Brian Wang is a Futurist Thought Leader and a popular Science blogger with 1 million readers per month. His blog Nextbigfuture.com is ranked #1 Science News Blog. It covers many disruptive technology and trends including Space, Robotics, Artificial Intelligence, Medicine, Anti-aging Biotechnology, and Nanotechnology.
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