Building a parallel branch and bound library

Benaïchouche, Mohamed; Cung, Van‐Dat; Dowaji, Salah; Cun, Bertrand Le; Mautor, Thierry; Roucairol, Catherine

doi:10.1007/bfb0027123

Cited by 17 publications

(5 citation statements)

References 34 publications

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“…Benaïchouche et al [4] provide an overview of ways to organize a storage structure as a priority queue. Usually, priority queues are represented by heaps where each parent has higher priority than its children.…”

Section: Parallel Implementation Of Exactmpmentioning

confidence: 99%

ExactMP: An Efficient Parallel Exact Solver for Phylogenetic Tree Reconstruction Using Maximum Parsimony

Bader

Chandu

Yan³

2006 International Conference on Parallel Processing (ICPP'06)

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Section: Parallel Implementation Of Exactmpmentioning

confidence: 99%

ExactMP: An Efficient Parallel Exact Solver for Phylogenetic Tree Reconstruction Using Maximum Parsimony

Bader

Chandu

Yan³

2006 International Conference on Parallel Processing (ICPP'06)

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“…ALPS [8] is a framework for implementing parallel algorithms based on tree search. Other parallel solvers are PUBB [9], PPBB-Lib [10], PICO [11] anb BoB [12]. PARINO [13] and FATCOP [14], [15] are generic parallel MIP solvers.…”

Section: Related Workmentioning

confidence: 99%

Performance Evaluation of Grid-Enabled Code: A Case Study

Marcarelli

Mancini

Villano

2009

2009 18th IEEE International Workshops on Enabling Technologies: Infrastructures for Collaborative Enterprises

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Abstract-This paper presents the performance analysis of a grid-enabled MIP solver in a grid environment consisting of three clusters on a campus LAN. In particular, the paper focuses on the analysis of the behavior of the application using two networks connecting the clusters with different latency and bandwidth. I. INTRODUCTIONThe goal of computational grids is to aggregate numerous heterogeneous resources in order to provide sufficient computational power to solve large-scale problems. In a grid environment, users can use unlimited resources as a single powerful entity. However, the heterogeneity of the resources in the grids makes it difficult to predict the performance behavior of the applications. The performance analysis of an application on a grid is a very interesting matter, because the results are dependent on the problem, on the code structure and the communication patterns exploited, on the performance of the grid hardware used (computing node, CPU, memory hierarchy), on the middleware and the run-time systems used, and, above all, on the communication performance inside and among the computational facilities making up the grid. This paper tackles the grid performance analysis problem for a real-world code, a solver of Mixed Integer Programming problems (MIP) developed using the BCP-G framework. BCP-G is a customized version of COIN/BCP, an open source framework developed within the IBM COIN-OR project [1], which is based on the Branch, Cut and Price method for solving large-scale linear integer programming problems. The original COIN/BCP framework, based on the use of PVM libraries [2], has been provided with a new MPI communication API able to exploit the MPICH-G2 system, a grid-enabled MPI implementation [3], [4]. Moreover, the developed application is part of a more complex grid-enabled system, consisting of another framework (Meta-Pbc) and a web portal (SWI-Portal). The first one is a new framework, based on a decentralized master/worker schema [5]. The second one is a web portal designed to manage users and jobs as user-friendly as possible.In a previous paper [6] we studied the performance of the software system sketched above, on a test grid environment consisting of three small clusters on a fairly slow campus LAN. Even if the use of the three clusters led to a nonnegligible speedup, the performance gain was relatively small compared to the one that could be obtained using a single

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“…Most of them focus on particular applications or on various loadbalancing mechanisms. The need for general-purpose parallel search algorithm libraries, though, was recognized as early as 1987 [10], and several libraries have been implemented [4,19,22,29]. Most of them are specialized to branch-and-bound.…”

Section: Portable Software For Parallel Computersmentioning

confidence: 99%

“…Six positions required exactly 80 moves, 4 of them have previously been detected by Gasser [12]. The new ones are (15,14,13,12,10,11,8,9,2,6,5,1,3,7,4,0) and (15,11,13,12,14,10,9,5,2,6,8,1,3,7,4,0). The computation proves that the hardest 15-puzzle positions require exactly 80 moves to be solved.…”

Section: The 15-puzzlementioning

confidence: 99%

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Brüngger¹,

Marzetta²,

Fukuda

et al. 1999

Annals of Operations Research

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Distributed and parallel computation is, on the one hand, the cheapest way to increase raw computing power. Turning parallelism into a useful tool for solving new problems, on the other hand, presents formidable challenges to computer science. We believe that parallel computation will spread among general users mostly through the ready availability of convenient and powerful program libraries. In contrast to general-purpose languages, a program library is specialized towards a well-defined class of problems and algorithms. This narrow focus permits developers to optimize algorithms, once and for all, for parallel computers of a variety of common architectures. This paper presents ZRAM, a portable parallel library of exhaustive search algorithms, as a case study that proves the feasibility of achieving simultaneously the goals of portability, efficiency, and convenience of use. Examples of massive computations successfully performed with the help of ZRAM illustrate its capabilities and use.

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Building a parallel branch and bound library

Cited by 17 publications

References 34 publications

ExactMP: An Efficient Parallel Exact Solver for Phylogenetic Tree Reconstruction Using Maximum Parsimony

ExactMP: An Efficient Parallel Exact Solver for Phylogenetic Tree Reconstruction Using Maximum Parsimony

Performance Evaluation of Grid-Enabled Code: A Case Study

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