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Sökning: WFRF:(Lundborg M.) > (2015-2019) > Molecular Simulatio...

Molecular Simulation Workflows as Parallel Algorithms : The Execution Engine of Copernicus, a Distributed High-Performance Computing Platform

Pronk, Sander (författare)
KTH,Beräkningsbiofysik,SeRC - Swedish e-Science Research Centre
Pouya, Iman (författare)
KTH,Beräkningsbiofysik,SeRC - Swedish e-Science Research Centre
Lundborg, Magnus (författare)
Stockholms universitet,Institutionen för biokemi och biofysik,Science for Life Laboratory (SciLifeLab)
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Rotskoff, Grant (författare)
KTH,Beräkningsbiofysik,SeRC - Swedish e-Science Research Centre
Wesén, Björn (författare)
KTH,Beräkningsbiofysik,SeRC - Swedish e-Science Research Centre
Kasson, Peter M. (författare)
Lindahl, Erik (författare)
KTH,Stockholms universitet,Institutionen för biokemi och biofysik,Science for Life Laboratory (SciLifeLab),KTH Royal Institute of Technology, Sweden,Beräkningsbiofysik,SeRC - Swedish e-Science Research Centre,Stockholm Univ, Dept Biochem & Biophys, Sci Life Lab, SE-10691 Stockholm, Sweden
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 (creator_code:org_t)
2015-05-12
2015
Engelska.
Ingår i: Journal of Chemical Theory and Computation. - : American Chemical Society (ACS). - 1549-9618 .- 1549-9626. ; 11:6, s. 2600-2608
  • Tidskriftsartikel (refereegranskat)
Abstract Ämnesord
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  • Computational chemistry and other simulation fields are critically dependent on computing resources, but few problems scale efficiently to the hundreds of thousands of processors available in current supercomputers particularly for molecular dynamics. This has turned into a bottleneck as new hardware generations primarily provide mote processing units rather than making individual units much faster, which simulation applications are addressing by increasingly focusing on sampling with algorithms such as free-energy perturbation, Markov state modeling, metadynamics, or milestoning. All these rely on combining results from multiple simulations into a single observation. They are potentially powerful approaches that aim to predict experimental observables directly, but this comes at the expense of added complexity in selecting sampling strategies and keeping track of dozens to thousands of simulations and their dependencies. Here, we describe how the distributed execution framework Copernicus allows the expression of such algorithms in generic workflows: dataflow programs. Because dataflow algorithms explicitly state dependencies of each constituent part, algorithms only need to be described on conceptual level, after which the execution is maximally parallel. The fully automated execution facilitates the optimization of these algorithms with adaptive sampling, where undersampled regions are automatically detected and targeted without user intervention. We show how several such algorithms can be formulated for computational chemistry problems, and how they are executed efficiently with many loosely coupled simulations using either distributed or parallel resources with Copernicus.

Ämnesord

NATURVETENSKAP  -- Kemi (hsv//swe)
NATURAL SCIENCES  -- Chemical Sciences (hsv//eng)
NATURVETENSKAP  -- Fysik (hsv//swe)
NATURAL SCIENCES  -- Physical Sciences (hsv//eng)
NATURVETENSKAP  -- Kemi -- Fysikalisk kemi (hsv//swe)
NATURAL SCIENCES  -- Chemical Sciences -- Physical Chemistry (hsv//eng)

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