Multicomputer Platforms Research Articles

Solving the capacitated vehicle routing problem with Lexi-search approach

In this paper we present a variant vehicle routing problem called “Solving the Capacitated Vehicle Routing Problem with Lexi-Search Approach” (CVRP). The purpose of this article is to propose an efficient Lexi-Search Algorithm using pattern recognition technique for solving CVRP on a scalable multicomputer platform and to obtain an optimal solution. Our results show that the proposed algorithm is highly competitive on a set of benchmark problems. In this paper we focus our investigation on solving the capacitated VPR (CVPR) and considered a variant vehicle routing problem called as “ Solving the Capacitated Vehicle Routing Problem with Lexi-Search Approach”. First the model is formulated into a zero-one programming problem. A Lexi-Search Algorithm using Pattern Recognition Technique is developed for getting an optimal solution. The problem is discussed with suitable numerical illustration. We have programmed the proposed algorithm using C-language. The computational details are reported. As an observation the CPU run time is fairly less for higher values to the parameters of the problem to obtain optimal solutions.

Lexi-search algorithm using pattern recognition technique for solving a variant constrained bulk transshipment problem

In this article we present a variant transportation problem called “A Variant Constrained Bulk Transshipment Problem”. The purpose of this paper is to propose an efficient Lexi-Search Algorithm using pattern recognition technique for solving “A Variant Constrained Bulk Transshipment Problem” on a scalable multicomputer platform and to obtain an optimal solution. Our results show that the proposed algorithm is highly competitive on a set of benchmark problems. The objective of the problem is to minimize the total bulk cost of supplying the required products to the destinations with the restriction that any destination should get its requirement from one source only, even when it gets from a destination. In the sequel we developed a Lexi-Search algorithm based “Pattern Recognition Technique” to solve this problem which takes care of simple combinatorial structure of the problem and computational results are reported. In this discussion we have studied a variation of the transportation problems called “A Variant Constrained Bulk Transshipment Problem”. It also comes under combinatorial programming problems.

Solving the capacitated vehicle routing problem with Lexi-search approach

In this paper we present a variant vehicle routing problem called “Solving the Capacitated Vehicle Routing Problem with Lexi-Search Approach” (CVRP). The purpose of this article is to propose an efficient Lexi-Search Algorithm using pattern recognition technique for solving CVRP on a scalable multicomputer platform and to obtain an optimal solution. Our results show that the proposed algorithm is highly competitive on a set of benchmark problems. In this paper we focus our investigation on solving the capacitated VPR (CVPR) and considered a variant vehicle routing problem called as “Solving the Capacitated Vehicle Routing Problem with Lexi-Search Approach”. First the model is formulated into a zero-one programming problem. A Lexi-Search Algorithm using Pattern Recognition Technique is developed for getting an optimal solution. The problem is discussed with suitable numerical illustration. We have programmed the proposed algorithm using C-language. The computational details are reported. As an observation the CPU run time is fairly less for higher values to the parameters of the problem to obtain optimal solutions.

ISLAND MIGRATION MODEL WITH PARALLEL MUTATION STRATEGIES FOR COMPUTING THE TRAVELING SALESMAN PROBLEM ON MULTICOMPUTER PLATFORM

This paper investigates the efficiency of a model of parallel genetic computation of the traveling salesman problem with circular periodic chromosomes migration. The parallel model is verified by MPI-based program implementation on a multicomputer platform. The correlation of the application and architectural spaces has been investigated by exploring the impact of the scalability of the application and the parallel machine size over the efficiency of the parallel system. Performance profiling, evaluation and analysis have been made for different numbers of cities and different sizes of the multicomputer platform. The paper also investigates the impact of the mutation strategy on the solution quality of coarse-grained parallel genetic algorithm with circular periodic migration for the traveling salesman problem. We propose an approach to improve the quality of solution by applying parallel variable mutation rates for the local evolutions in the concurrent processes. A series of experiments has been carried out with parallel fixed and variable mutation rates in order to estimate the efficiency of the suggested approach. The best quality solutions have been obtained for the strategy with parallel fixed mutation rates.

HETEROGENEITY IN COMPUTING: INSIGHTS FROM A WORKSHARING SCHEDULING PROBLEM

Heterogeneity complicates the use of multicomputer platforms. Can it also enhance their performance? How can one measure the power of a heterogeneous assemblage of computers ("cluster"), in absolute terms (how powerful is this cluster) and relative terms (which cluster is more powerful)? Is a cluster that has one super-fast computer and the rest of "average" speed more/less powerful than one all of whose computers are "moderately" fast? If you can replace just one computer in a cluster with a faster one, should you replace the fastest? the slowest? A result concerning "worksharing" in heterogeneous clusters provides a highly idealized, yet algorithmically meaningful, framework for studying such questions in a way that admits rigorous analysis and formal proof. We encounter some surprises as we answer the preceding questions (perforce, within the idealized framework). Highlights: (1) If one can replace only one computer in a cluster by a faster one, it is (almost) always most advantageous to replace the fastest one. (2) If the computers in two clusters have the same mean speed, then the cluster with the larger variance in speed is (almost) always more productive (verified analytically for small clusters and empirically for large ones.) (3) Heterogeneity can actually enhance a cluster's computing power.

Strategies for Parallel Genetic Computation of Optimization Problems

ABSTRACTThis paper explores the efficiency of various strategies for parallel genetic computation of optimization problems on multicomputer platforms. The strategies for designing parallel genetic algorithms on multicomputer platforms are investigated considering the correlations of the algorithmic and the architectural spaces. Two parallel genetic computational models are considered based on the manager/workers and Single Program Multiple Data parallel paradigms. Parallelism profiling and analysis of parallel system performance have been made for the different parallel computational models in respect to the scalability of the application and the scalability of the parallel machine size.

Parallel processing for boundary element computations on distributed systems

A parallel boundary integral algorithm for solving boundary value problems on distributed memory computer systems is presented in this paper. The paper focuses on parallelizations of the influence coefficients matrix generation and the solution of the resulting linear system, which are the two main parts of boundary integral formulations. The distributed parallel boundary integral algorithm presented in this paper generates a part of the influence coefficients matrix on each computation node of a multicomputer platform and stores that part in the local memory. The distributed influence coefficients matrix is then used in its partitioned form by the parallel linear system solver to obtain the solution. The matrix of coefficients is large, dense and nonsymmetric. Three parallel linear system solvers are presented. Among them, Algorithm-1 and Algorithm-2 are based on the conjugate-gradient-squared (CGS) method, Algorithm-3 is based on a direct method. It is found that distributed memory parallel algorithms are very much machine dependent. The performance of a parallel linear system solver depends not only on the method of solution but also on the multicomputer network topology, and its ratio of node computation speed to network data transfer bandwidth. By selecting the algorithm which fits the characteristics of a distributed computer system hardware one can achieve relative maximum performance. The performance characteristics of distributed linear system solvers are studied in order to select an optimum method for the available hardware at minimum development cost. The performance of sequential linear system solvers which have been extensively documented in the literature are not applicable to distributed memory systems. This paper presents results and discussions on the selection of simple robust algorithms, easily implemented on specific hardware topologies and provides information for extending the selected methods to different parallel machines. The results can also serve as a reference for parallel computer benchmarking.

Object-oriented software tools for parallel PDE solvers

An object-oriented approach is taken to the problem of formulating portable, easy-to-modify PDE solvers for realistic problems in three space dimensions. The resulting software library, Cogito, contains tools for writing programs to be executed on MIMD computers with distributed memory. Difference methods on composite, structured grids are supported. Most of the Cogito classes have been implemented in Fortran 77, in such a way that the object-oriented design is visible. With respect to parallel performance, these tools yield code that is comparable to parallel solvers written in plain Fortran 77. The resulting programs are can be executed without modification on a large number of multicomputer platforms, and also on serial computers.