Anton, a Special-Purpose Machine
for Molecular Dynamics Simulation
by david E. shaw, Martin M. deneroff, ron o. dror, Jeffrey s. Kuskin, richard h. larson, John K. salmon, Cliff Young,
brannon batson, Kevin J. bowers, Jack C. Chao, Michael p. Eastwood, Joseph Gagliardo, J.p. Grossman, C. richard ho,
douglas J. ierardi, istván Kolossváry, John l. Klepeis, timothy layman, Christine Mcleavey, Mark A. Moraes, rolf Mueller,
Edward C. priest, Yibing shan, Jochen spengler, Michael theobald, brian towles, and stanley C. Wang
abstract
The ability to perform long, accurate molecular dynamics (MD)
simulations involving proteins and other biological macromolecules 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 high-speed 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.
1. intRoDuction
Molecular dynamics (MD) simulations can be used to model
the motions of molecular systems, including proteins, cell
membranes, and DNA, at an atomic level of detail. A sufficiently long and accurate MD simulation could allow scientists and drug designers to visualize for the first time many
critically important biochemical phenomena that cannot
currently be observed in laboratory experiments, including
the “folding” of proteins into their native three-dimensional structures, the structural changes that underlie protein
function, and the interactions between two proteins or between a protein and a candidate drug molecule. Such simulations could answer some of the most important open
questions in the fields of biology and chemistry, and have
the potential to make substantial contributions to the process of drug development.
Many of the most important biological processes occur
over timescales on the order of a millisecond. MD simulations on this timescale, however, lie several orders of magnitude beyond the reach of current technology; only a few MD
runs have thus far reached even a microsecond of simulated
time, and the vast majority have been limited to the nanosecond timescale. Millisecond-scale simulations of a biomolecular system containing tens of thousands of atoms will in
practice require that the forces exerted by all atoms on all
other atoms be calculated in just a few microseconds—a
process that must be repeated on the order of 1012 times.
These requirements far exceed the current capabilities
of even the most powerful commodity clusters or general-purpose scientific supercomputers.
This paper describes a specialized, massively parallel machine, named Anton, that is designed to accelerate MD simulations by several orders of magnitude, bringing millisecond-scale simulations within reach for molecular systems
involving tens of thousands of atoms. The machine, which is
scheduled for completion by the end of 2008, will comprise
512 processing nodes in its initial configuration, each containing a specialized MD computation engine implemented
as a single ASIC. The molecular system to be simulated is decomposed spatially among these processing nodes, which
are connected through a specialized high-performance network to form a three-dimensional torus. Anton’s expected
performance advantage stems from a combination of MD-specific hardware that achieves a very high level of arithmetic
density and novel parallel algorithms that enhance scalability by reducing both intra- and inter-chip communication.
Figure 1 is a photograph of one of the first Anton ASICs.
In designing Anton and its associated software, we have
attempted to attack a somewhat different problem than the
ones addressed by several other projects that have deployed
significant computational resources for MD simulations.
The Folding@Home project, 16 for example, has obtained a
number of significant and interesting scientific results by
using as many as 250,000 PCs (made available over the Internet by volunteers) to simulate a very large number of separate
molecular trajectories, each of which is limited to the
timescale accessible on a single PC. While a great deal
can be learned from a large number of independent MD
trajectories, many other important problems require
the examination of a single, very long trajectory—the
principal task for which Anton is designed. Other projects, such as FASTRUN, 6 MDGRAPE, 22 and MD Engine, 23
have produced special-purpose hardware to accelerate
the most computationally expensive elements of an
MD simulation. Such hardware reduces the cost of MD
simulations, particularly for large molecular systems,
but Amdahl’s law and communication bottlenecks prevent the efficient use of enough such chips in parallel