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PELLPACK: a problemsolving environment for PDEbased applications on multicomputer platforms
 ACM Transactions on Mathematical Software
, 1998
"... This paper presents the software architecture and implementation of the problem solving ..."
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Cited by 26 (4 self)
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This paper presents the software architecture and implementation of the problem solving
Parallel Adaptive Mesh Generation and Decomposition
 WHR
, 1996
"... An important class of methodologies for the parallel processing of computational models defined on some discrete geometric data structures (i.e., meshes, grids) is the so called geometry decomposition or splitting approach. Compared to the sequential processing of such models, the geometry splitting ..."
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Cited by 6 (2 self)
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An important class of methodologies for the parallel processing of computational models defined on some discrete geometric data structures (i.e., meshes, grids) is the so called geometry decomposition or splitting approach. Compared to the sequential processing of such models, the geometry splitting parallel methodology requires an additional computational phase. It consists of the decomposition of the associated geometric data structure into a number of balanced subdomains that satisfy a number of conditions that ensure the load balancing and minimum communication requirement of the underlying computations on a parallel hardware platform. It is well known that the implementation of the mesh decomposition phase requires the solution of a computationally intensive problem. For this reason several fast heuristics have been proposed. In this paper we explore a decomposition approach which is part of a parallel adaptive finite element mesh procedure. The proposed integrated approach consists of five steps. It starts with a coarse background mesh that is optimally decomposed by applying well known heuristics. Then, the initial mesh is refined in each subdomain after linking the new boundaries introduced by its decomposition. Finally, the decomposition of the new refined mesh is improved so that it satisfies the objectives and conditions of the mesh decomposition problem. Extensive experimentation indicates the effectiveness and efficiency of the proposed parallel mesh and decomposition approach. 11.
Performance evaluation of MPI implementations and MPI based parallel ELLPACK solvers
 In 2 nd MPI Developers Coneference
, 1996
"... In this study, we are concerned with the parallelizationof finite element mesh generation and its decomposition, and the parallel solution of sparse algebraic equations which are obtained from the parallel discretization of second order elliptic partial differential equations (PDEs) using finite dif ..."
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Cited by 4 (0 self)
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In this study, we are concerned with the parallelizationof finite element mesh generation and its decomposition, and the parallel solution of sparse algebraic equations which are obtained from the parallel discretization of second order elliptic partial differential equations (PDEs) using finite difference and finite element techniques. For this we use the Parallel ELLPACK (//ELLPACK) problem solving environment (PSE) which supports PDE computations on several MIMD platforms. We have considered the ITPACK library of stationary iterative solvers which we have parallelized and integrated into the //ELLPACK PSE. This Parallel ITPACK package has been implemented using the MPI, PVM, PICL, PARMACS, nCUBE Vertex and Intel NX message passing communication libraries. It performs very efficiently on a variety of hardware and communication platforms. To study the efficiency of three MPI library implementations, the performance of the Parallel ITPACK solvers was measured on several distributed memory architectures and on clusters of workstations for a testbed of elliptic boundary value PDE problems. We present a comparison of these MPI library implementationswith PVM and the native communication libraries, based on their performance on these tests. Moreover we have implemented in MPI, a parallel mesh generator that concurrently produces a semi–optimal partitioning of the mesh to support various domain decomposition solution strategies across the above platforms. The results indicate that the MPI overhead varies among the various implementations without significantly affecting the algorithmic speedup even on clusters of workstations.
EPPOD: A problemsolving environment for parallel electronic prototyping of physical objects design
 J. Paral. Distr. Comput
, 1997
"... One of the next “Grand Challenges ” for computer applications is the creation of a system for the design and analysis of physical objects. This system will provide accurate computer simulations of physical objects coupled with powerful design optimization tools to allow prototyping and final design ..."
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Cited by 2 (1 self)
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One of the next “Grand Challenges ” for computer applications is the creation of a system for the design and analysis of physical objects. This system will provide accurate computer simulations of physical objects coupled with powerful design optimization tools to allow prototyping and final design of a broad range of items. We refer to such software environment as Electronic Prototyping for Physical Object Design (EPPOD). The deep challenges in building such systems is in software “integration”, in utilizing “massively parallelism ” to satisfy their large computational requirements, in incorporating “knowledge ” into the entire electronic prototyping process, in creating “intelligent ” user interfaces for such systems, and in advancing the “algorithmic infrastructure ” needed to support the desired functionality. In this paper we address the issues related to parallel processing of the computationally intensive components of the EPPOD system and present an architecture of a EPPOD system for the optimum design of physical “parts ” on message passing parallel machines. The parallel methodology adopted
Parallel (If) ELLPACK: A Problem Solving Environment for PDE Based Applications on Multicomputer Platforms
, 1996
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Parallel ELLPACK Elliptic PDE Solvers
, 1995
"... Parallel ELLPACK [35, 61] is a machine independent problem solving environment (PSE) that supports PDE (partial di erential equations) computing across many hardware platforms. In this paper we review parallel methodologies based on the \divide and conquer" computational paradigm and their ..."
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Parallel ELLPACK [35, 61] is a machine independent problem solving environment (PSE) that supports PDE (partial di erential equations) computing across many hardware platforms. In this paper we review parallel methodologies based on the \divide and conquer&quot; computational paradigm and their infrastructure for solving general elliptic PDEs. Particularly, we describe those that have been implemented and tested in the parallel ELLPACK PSE. Moreover, we describe two parallel frameworks that allow the reuse of the discretization part of the sequential elliptic PDE solvers. Numerical results indicate the e ectiveness of the reuse frameworks implemented. 1
Parallel Reuse Methodologies for Elliptic Boundary Value Problems
, 1996
"... We describe two parallel frameworks that allow the reuse of the discretization part of sequential general elliptic PDE (partial differential equation) solvers. These parallel reuse methodologies are based on the "divide and conquer " computational paradigm. They have been integrated into ..."
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We describe two parallel frameworks that allow the reuse of the discretization part of sequential general elliptic PDE (partial differential equation) solvers. These parallel reuse methodologies are based on the "divide and conquer " computational paradigm. They have been integrated into the Parallel ELLPACI ( problem solving environment that supports PDE computing across many hardware platforms. Experimental results indicate the effectiveness of the reuse frameworks implemented. We also evaluate the performance of the Parallel ITPACK library of stationary iterative solvers. This package has been implemented using several message passing communication libraries. We consider the parallel solution of sparse algebraic equations obtained from the discretization of second order elliptic PDEs using finite difference and finite element techniques. The performance of the Parallel ITPACK solvers is measured on many distributed memory platforms including clusters of workstations. 1 1