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7th Annual International Young Scientists Conference on Computational Science (YSC)

作者： Smirnov, Sergey Voloshinov, Vladimir Russian Acad Sci Inst Informat Transmiss Problems Bolshoy Karetny Per 19-1 Moscow 127051 Russia

Previous publications presented an implementation of coarse-grained parallel Branch-and-Bound (B&B) method. It supports two strategies: decomposition of feasible domain into a set of sub-problems;"multisearch" (or concurrent) solving the same problem with different settings of the BNB-method. In both cases several B&B-solver's processes exchange best values of goal function on feasible solutions they found. Earlier, it was found that this approach gives a noticeable speed-up of solving the original optimization problem. The method has been implemented as an Everest-application called DDBNB (Domain Decomposition B&B). It is based on Everest distributed computing platform, ***, and open source solvers: CBC, projectsxoiri-onorgiCbc;SCIP, ***. Originally, DDBNB has been tested on discrete optimization problems (Traveling Salesman and Load Balancing). The paper presents application of DDBNB to global optimization problems with polynomial functions (solver SCIP supports solving of such class of problems). Well known problems concerning optimal placements of points on 3D-sphere are considered: Tammes and Thomson problems. The first problem is to maximize minimal distance between any two of N points. The second - minimize electrostatic Coulomb energy of unit charges put in N points. Both may be represented as mathematical programming problems with polynomial functions. Feasible domains of both problems are direct products of 3D-spheres and different decompositions of this domains by linear inequalities into hundreds of subproblems have been tested. Tests performed gave promising results and crucial acceleration for Tammes problems, N=7, 8, 9, and Thomson problem, N=5. One should note that Thomson problem got computer aided proof (substantially based on the problem's specifics) less than a decade ago, when proposed approach is rather generic and does not go into details of the problem to be solved. Formulation of original problems and decomposition s

关键词： branch-and-bound domain decomposition distributed global optimization Tammes problem Thomson problem

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On Domain Decomposition Strategies to Parallelize Branch-and-Bound Method for global optimization in Everest distributed Environment

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Procedia Computer Science 2018年 136卷 128-135页

作者： Sergey Smirnov Vladimir Voloshinov Institute for Information Transmission Problems of the Russian Academy of Sciences Bolshoy Karetny per. 19-1 Moscow 127051 Russia

Previous publications presented an implementation of coarse-grained parallel Branch-and-Bound (B&B) method. It supports two strategies: decomposition of feasible domain into a set of sub-problems; “multisearch” (or concurrent) solving the same problem with different settings of the BNB-method. In both cases several B&B-solver’s processes exchange best values of goal function on feasible solutions they found. Earlier, it was found that this approach gives a noticeable speed-up of solving the original optimization problem. The method has been implemented as an Everest-application called DDBNB (Domain Decomposition B&B). It is based on Everest distributed computing platform, ***, and open source solvers: CBC, ***/Cbc; SCIP, ***. Originally, DDBNB has been tested on discrete optimization problems (Traveling Salesman and Load Balancing). The paper presents application of DDBNB to global optimization problems with polynomial functions (solver SCIP supports solving of such class of problems). Well known problems concerning optimal placements of points on 3D-sphere are considered: Tammes and Thomson problems. The first problem is to maximize minimal distance between any two of N points. The second - minimize electrostatic Coulomb energy of unit charges put in N points. Both may be represented as mathematical programming problems with polynomial functions. Feasible domains of both problems are direct products of 3D-spheres and different decompositions of this domains by linear inequalities into hundreds of subproblems have been tested. Tests performed gave promising results and crucial acceleration for Tammes problems, N =7,8,9, and Thomson problem, N =5. One should note that Thomson problem got computer aided proof (substantially based on the problem’s specifics) less than a decade ago, when proposed approach is rather generic and does not go into details of the problem to be solved. Formulation of original problems and decompositio

关键词： branch-and-bound domain decomposition distributed global optimization Tammes problem Thomson problem

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Integration of ParaSCIP solvers running on several clusters on the base of Everest cloud platform 8

Integration of ParaSCIP solvers running on several clusters ...

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8th International Young Scientists Conference on Computational Science (YSC)

作者： Smirnov, Sergey Voloshinov, Vladimir Russian Acad Sci Inst Informat Transmiss Problems Bolshoy Karemy Per 19-1 Moscow 127051 Russia

Software integration of optimization problems' solvers leveraging power of heterogeneous computing environments is a great challenge of last decades. Last several years we have been developing coarse-grained parallelization approaches to speed up Branch-and-Bound (BnB) algorithm for discrete and global optimization problems by exchange of BnB-incumbents in a heterogeneous environment containing standalone servers and clusters via Everest software toolkit, http //***. This approach have been implemented as DDBNB Everest-application (Domain Decomposition BnB), https://***/distcomp/ddbnb. The current implementation is based on two solvers (and their open API to get/put incumbents): SCIP, https://*** and CBC, https ://***/coin-or/Cbc. Recently we began to use ParaSCIP solver, https : //ug. zib. de, - parallel implementation of BnB-algorithm in SCIP based on MPI. ParaSCIP demonstrates an advantages of fine-grained parallelization in homogeneous computing environment, i.e. HPC-clusters. By now we have access to three clusters from Russian Top50 where ParaSCIP have been installed. In the article several ways to involve ParaSCIP processes running on different clusters in solving common optimization problem are discussed. (C) 2019 The Authors. Published by Elsevier Ltd.

关键词： branch-and-bound domain decomposition distributed global optimization message passing interface

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Integration of ParaSCIP solvers running on several clusters on the base of Everest cloud platform

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Procedia Computer Science 2019年 156卷 13-18页

作者： Sergey Smirnov Vladimir Voloshinov Institute for Information Transmission Problems of the Russian Academy of Sciences Bolshoy Karetny per. 19-1 Moscow 127051 Russia

Software integration of optimization problems’ solvers leveraging power of heterogeneous computing environments is a great challenge of last decades. Last several years we have been developing coarse-grained parallelization approaches to speed up Branch-and-Bound (BnB) algorithm for discrete and global optimization problems by exchange of BnB-incumbents in a heterogeneous environment containing standalone servers and clusters via Everest software toolkit, http://***. This approach have been implemented as DDBNB Everest-application (Domain Decomposition BnB), https://***/distcomp/ddbnb. The current implementation is based on two solvers (and their open API to get/put incumbents): SCIP, https://*** and CBC, https://***/coin-or/Cbc. Recently we began to use ParaSCIP solver, https://***, - parallel implementation of BnB-algorithm in SCIP based on MPI. ParaSCIP demonstrates an advantages of fine-grained parallelization in homogeneous computing environment, i.e. HPC-clusters. By now we have access to three clusters from Russian Top50 where ParaSCIP have been installed. In the article several ways to involve ParaSCIP processes running on different clusters in solving common optimization problem are discussed.

关键词： branch-and-bound domain decomposition distributed global optimization message passing interface

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