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Author Wang, Stanley C. ♦ Kuskin, Jeffrey S. ♦ Shan, Yibing ♦ Towles, Brian ♦ Shaw, David E. ♦ Mueller, Rolf ♦ Dror, Ron O. ♦ Larson, Richard H. ♦ Salmon, John K. ♦ Eastwood, Michael P. ♦ Grossman, J. P. ♦ Layman, Timothy ♦ Ho, C. Richard ♦ Deneroff, Martin M. ♦ Gagliardo, Joseph ♦ Spengler, Jochen ♦ Ierardi, Douglas J. ♦ Moraes, Mark A. ♦ Young, Cliff ♦ Chao, Jack C. ♦ Kolossváry, István ♦ Batson, Brannon ♦ Bowers, Kevin J. ♦ McLeavey, Christine ♦ Theobald, Michael ♦ Klepeis, John L. ♦ Priest, Edward C.
Source ACM Digital Library
Content type Text
Publisher Association for Computing Machinery (ACM)
File Format PDF
Language English
Abstract 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.
Description Affiliation: D.E. Shaw Research, New York, NY (Deneroff, Martin M.; Dror, Ron O.; Kuskin, Jeffrey S.; Larson, Richard H.; Salmon, John K.; Young, Cliff; Batson, Brannon; Bowers, Kevin J.; Chao, Jack C.; Eastwood, Michael P.; Gagliardo, Joseph; Grossman, J. P.; Ho, C. Richard; Ierardi, Douglas J.; Kolossváry, István; Klepeis, John L.; Layman, Timothy; McLeavey, Christine; Moraes, Mark A.; Mueller, Rolf; Priest, Edward C.; Shan, Yibing; Spengler, Jochen; Theobald, Michael; Towles, Brian; Wang, Stanley C.) || D.E. Shaw Research, New York, NY and Columbia University, New York, NY (Shaw, David E.)
Age Range 18 to 22 years ♦ above 22 year
Educational Use Research
Education Level UG and PG
Learning Resource Type Article
Publisher Date 2005-08-01
Publisher Place New York
Journal Communications of the ACM (CACM)
Volume Number 51
Issue Number 7
Page Count 7
Starting Page 91
Ending Page 97

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Source: ACM Digital Library