{"title":"RANDOMIZED OPTIMAL LIST RANKING ON COARSE-GRAINED PARALLEL COMPUTERS WITH O(log p) COMMUNICATION PHASES","authors":"Xiaotie Deng, Patrick W. Dymond","doi":"10.1080/10637199808947384","DOIUrl":"https://doi.org/10.1080/10637199808947384","url":null,"abstract":"The cost of interprocessor communication has a substantial impact on execution time when implementing parallel algorithms on physical parallel computers. For coarse-grained parallel computers it is important to minimize the number of communication phases, in order to balance cost of communication with local computation time. We present a log p-phase optimal randomized parallel list ranking algorithm and its application to expression evaluation. These techniques address the general issue of model-independent parallel algorithm design.","PeriodicalId":406098,"journal":{"name":"Parallel Algorithms and Applications","volume":"81 2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2000-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131413204","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"OPTIMAL MULTISELECTION IN HYPERCUBES","authors":"Hong Shen","doi":"10.1080/10637199808947387","DOIUrl":"https://doi.org/10.1080/10637199808947387","url":null,"abstract":"We study efficient parallel solutions to the problem of selecting r elements at specified ranks from a set of n arbitrary elements, known as multiselection, in a hypercube with p<n processors. We propose two parallel algorithms based on different approaches, where one requires processors to operate in the SIMD mode, and the other in the MIMD mode. Our SIMD algorithm runs in O(n ϵ min{r, log p}) time when p = n 1−r for any 0<ϵ<1, which is cost-optimal when r≥p. With the same number of processors, our MIMD algorithm runs in O(n ϵ logr) time and is cost-optimal for any values of r. Both algorithms are more efficient than straightforward solutions and that of direct simulation of the optimal EREW algorithm.","PeriodicalId":406098,"journal":{"name":"Parallel Algorithms and Applications","volume":"59 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2000-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126560012","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"A Distributed Genetic Algorithm with Migration for the Design of Composite Laminate Structures","authors":"T. Mathew, T. W. Layne","doi":"10.1080/10637199808947394","DOIUrl":"https://doi.org/10.1080/10637199808947394","url":null,"abstract":"This paper describes the development of a general Fortran 90 framework for the solution of composite laminate design problems using a genetic algorithm (GA). The initial Fortran 90 module and package of operators result in a standard genetic algorithm (sGA). The sGA is extended to operate on a parallel processor, and a migration algorithm is introduced. These extensions result in the distributed genetic algorithm with migration (dGA). The performance of the dGA in terms of cost and reliability is studied and compared to a sGA baseline, using two types of composite laminate design problems. The nondeterminism of GAs and the migration and dynamic load balancing algorithm used in this work result in a changed (diminished) workload, so conventional measures of parallelizability are not meaningful. Thus, a set of experiments is devised to characterize the run time performance of the dGA.","PeriodicalId":406098,"journal":{"name":"Parallel Algorithms and Applications","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1998-08-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128653216","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"LOCALIZATION STRATEGY FOR PARALLEL COMPUTING","authors":"Zhang Baolin","doi":"10.1080/10637199608915574","DOIUrl":"https://doi.org/10.1080/10637199608915574","url":null,"abstract":"The concept of localization strategy for massively parallel algorithm is presented in the paper, A massively parallel algorithm of the numerical solution of some tridiagonal systems is considered by analyzing the possibility of localization computing. The algorithm can be used in the practical computation of cubic spline approximation as well as for solving some finite difference equations.","PeriodicalId":406098,"journal":{"name":"Parallel Algorithms and Applications","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1996-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121905208","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"USE OF MULTI-SCALAR ANALYSIS FOR BUILDING LATTICE MODELS OF PDE'S∗","authors":"Li Yuan-xiang, Zou Xiu-fen, Huang Zhangcan","doi":"10.1080/10637199608915580","DOIUrl":"https://doi.org/10.1080/10637199608915580","url":null,"abstract":"A new class of methods of building lattice models have been developed recently in numerical simulation of fluid dynamics. Their essential idea is model-rebuilding and direct simulating of mathematical physical problems based on the kinetic description of physical systems. Following the work in fluid dynamics, extensions of the methods to some typical mathematical physical equations have been made. In this paper, a theoretical framework for building lattice models of general partial differential equations is proposed.","PeriodicalId":406098,"journal":{"name":"Parallel Algorithms and Applications","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1996-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131005001","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"BLOCK VECTORIZABLE PRECONDITIONED ITERATIVE METHODS","authors":"Liu Xing-ping, Hu Jia-Gan","doi":"10.1080/10637199408962540","DOIUrl":"https://doi.org/10.1080/10637199408962540","url":null,"abstract":"ABSTRACT In this paper the algorithms of the Block Vectorizable Preconditioned iterative Method for linear systems of the form A× = f are proposed, when A is block tridiagonal matrix. The convergence of these iterative methods is analysed, when A is an M matrix or H matrix- The resulting BVPI method has been tested on a YH-1 computer. Numerical examples indicates that the new method is very efficient, since the vectorial computational can be applied.","PeriodicalId":406098,"journal":{"name":"Parallel Algorithms and Applications","volume":"66 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116291864","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}