About OPTIMA@HOME
OPTIMA@HOME is a research project that uses Internet-connected
computers to solve challenging large-scale optimization problems. The goal of optimization is to find a minimum (or maximum) for a given function. This topic is perfectly explained in the Internet.
See for example excellent explanation by Arnold Newumaier. Many practical problems are reduced to the global optimization problems. At the moment this project runs an application that is aimed at solving molecular conformation problem.
This is a very challenging global optimization problem consisting in finding the atomic cluster structure that has the minimal possible potential energy. Such structures plays an important role in understanding the nature of different materials, chemical reactions and other fields. The details about the problem can be found here.
You can participate by downloading and running a free program
on your computer.
OPTIMA@HOME is based at Institute for Systems Analysis of Russian Academy of Sciences, department of Distributed Computing - a founding member of the International Desktop Grid Federation.
- Project Status.
- The project is maintained by the Distributed Computing Department team. For communication please use the mposypkin :: at :: gmail {dot} com address.
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News
About GULP Application
December 24, 2015, 14:30 MSD
New application aimed at testing stability of the GULP code.GULP is a program for performing a variety of types of simulation on materials using boundary conditions of 0-D (molecules and clusters), 1-D (polymers), 2-D
(surfaces, slabs and grain boundaries), or 3D (periodic solids). Adaptation of this code for BOINC is a first step to implementation of the computational materials discovery methods to the distributed computing. More
specifically, USPEX evolutionary algorithm. This is an algorithm for crystal structure prediction, which is a problem of global optimization, i.e., finding the global minimum of the free energy of the crystal (per mole) with
respect to variations of the structure. Successful solution of this problem requires local optimization for each structure generated during prediction. GULP is one of the methods supported by USPEX. That is why we have
adapted it for BOINC and providing a test caclucation for it.
This is variable cell calculation of the crystal structure of magnesium aluminate (MgAl2O4) with 28 atoms per unit cell at 100 GPa pressure.
Second experimental data set is submitted
October 03, 2014, 20:00 MSD
We submitted a new series of workunits (12289 wus). Each Wu runs local search for 32 times. So in total 131072 local searches are expected. The precision was set to 0.00001. 10 free parameters for Tersoff potential are
fitted.
First experimental data set is submitted
October 03, 2014, 20:00 MSD
We submitted a series of workunits (4096 wus). Each Wu runs local search for 32 times. So in total 131072 local
searches are expected. The precision was set to 0.00001. 10 free parameters for Tersoff potential are fitted.
New application is deployed!
October 03, 2014, 20:00 MSD
OPTIMA@home now hosts new application aimed at fitting parameters of the Tersoff potential. Molecular dynamics (MD) is often used for modeling various properties of crystals. The essence of this method consists in the numerical solution of the differential equations describing motion of atoms in the crystal lattice to determine the steady state. For molecular-dynamic computations, you must know the potential - a function that determines the interaction energy of atoms in the lattice. Modern potentials used in the simulations contain several parameters. Specific parameter values determine what concrete material is modeled. For example, for silicon, this will be one set, for diamond another etc.
The project is aimed at fitting parameter values of the potential in order to achieve known material properties (energy of the lattice cell, the components of the elastic modulus etc.). Then this potential will be used for molecular dynamics simulation. To identify potential parameters we solve the problem of minimizing the variance of the values of the properties obtained by using the potential from known values. This task is to generate a large sequence of initial approximations, from which further methods local search is a (local) minimum. Next, from the obtained values we select tuples with objective values less than the specified precision.
New test set was launched!
July 08, 2014, 20:00 MSD
It is need for the optimization of the solver smallexpx.
...more
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