Parallel Optimization Based Electronic Prototyping of Physical Parts

Wu, Po‐Ting; Houstis, Elias N.

doi:10.1080/10637199608915579

Cited by 2 publications

(5 citation statements)

References 15 publications

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“…Figure 12 depicts the performance of seven partitioning heuristics considered. These are well-known strategies defined in many related papers including [28,30]. The data obtained so far suggest that the partitioning schemes considered based on some form of coordinate axis splittings combined with some local optimality process gives the best performance with respect to five optimality criteria listed in Fig.…”

Section: Performance Evaluation Of Parallel Eppod Infrastructurementioning

confidence: 94%

“…Figure 1 indicates the two-level approach in relation with the rest of the electronic prototyping components. In [29], we present the detailed formulation of the two-level scheme. For the solution of the local and global optimization problems, we utilize the sequential ADS (automated design synthesis) [18,[21][22][23] software package build primarily to handle shape optimization applications.…”

Section: The Parallel Shape Optimization Frameworkmentioning

confidence: 99%

“…1 we define the EPPOD system utilizing a parallel framework defined by the geometric decomposition assumed. Its architecture is based on the two-level (local and global) formulation of the shape optimization problem described in [29]. It is worth noticing that part of the shape optimization phase is incorporated in the modeling phase.…”

Section: The Parallel Electronic Prototyping Process Implemented In Tmentioning

confidence: 99%

“…Note. In these runs we used the Cartesian coordinate splitting combined with a local optimum algorithm [30]. The data for a single processor are the execution times for the sequential mesh generator on the corresponding parallel platform.…”

Section: Performance Evaluation Of Parallel Eppod Infrastructurementioning

confidence: 99%

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EPPOD: A Problem Solving Environment for Parallel Electronic Prototyping of Physical Object Design

Houstis

1997

Journal of Parallel and Distributed Computing

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One of the grand challenges for computer applications is the creation of a system that will provide accurate computer simulations of physical objects coupled with powerful design optimization tools to allow optimum prototyping and the final design of a broad range of physical objects. We refer to such a software environment as electronic prototyping for physical object design (EPPOD). The research challenges in building such systems are in software integration, in utilizing massive 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 issues related to the parallel processing of the computationally intensive components of the EPPOD problem solving environment on message passing parallel machines and present its software architecture. The parallel methodology adopted to map the underlying computations to parallel machines is based on the optimal decomposition of continuous and discrete geometric data associated with the physical object. One of the main goals of this methodology is the reuse of existing software parts while implementing various components of the EPPOD system on parallel computational environments. Finally, some performance data of the parallel algorithmic infrastructured developed are listed and discussed.

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Section: Performance Evaluation Of Parallel Eppod Infrastructurementioning

confidence: 94%

Section: The Parallel Shape Optimization Frameworkmentioning

confidence: 99%

Section: The Parallel Electronic Prototyping Process Implemented In Tmentioning

confidence: 99%

Section: Performance Evaluation Of Parallel Eppod Infrastructurementioning

confidence: 99%

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EPPOD: A Problem Solving Environment for Parallel Electronic Prototyping of Physical Object Design

Houstis

1997

Journal of Parallel and Distributed Computing

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“…Mter the refined mesh decomposition, the linking routine connects the new boundary for each subdomain before proceeding with the final mesh generation in parallel. This is accomplished by separating the outer boundary polygon from the hole polygon(s) [9] using the element-element adjacency list to identify the boundary element and the node-element adjacency list to locate the next boundary element.…”

Section: Subdomain Boundary Linking Phasementioning

confidence: 99%

Parallel adaptive mesh generation and decomposition

Houstis

1996

Engineering with Computers

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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.

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Parallel Optimization Based Electronic Prototyping of Physical Parts

Cited by 2 publications

References 15 publications

EPPOD: A Problem Solving Environment for Parallel Electronic Prototyping of Physical Object Design

EPPOD: A Problem Solving Environment for Parallel Electronic Prototyping of Physical Object Design

Parallel adaptive mesh generation and decomposition

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