Performance Evaluation of Cloud-Based High Performance Computing for Finite Element Analysis

2015 ◽  
Author(s):  
Dazhong Wu ◽  
Xi Liu ◽  
Steve Hebert ◽  
Wolfgang Gentzsch ◽  
Janis Terpenny
Keyword(s):  
Finite Element Analysis ◽  
Cloud Computing ◽  
Finite Element ◽  
High Performance Computing ◽  
High Performance ◽  
Interactive Effects ◽  
Element Analysis ◽  
Computing Paradigm ◽  
Run Time ◽  
Performance Computing

Cloud computing is an innovative computing paradigm that can potentially bridge the gap between increasing computing demands in computer aided engineering (CAE) applications and limited scalability, flexibility, and agility in traditional computing paradigms. In light of the benefits of cloud computing, high performance computing (HPC) in the cloud has the potential to enable users to not only accelerate computationally expensive CAE simulations (e.g., finite element analysis), but also to reduce costs by utilizing on-demand and scalable cloud computing resources. The objective of this research is to evaluate the performance of running a large finite element simulation in a public cloud. Specifically, an experiment is performed to identify individual and interactive effects of several factors (e.g., CPU core count, memory size, solver computational rate, and input/output rate) on run time using statistical methods. Our experimental results have shown that the performance of HPC in the cloud is sufficient for the application of a large finite element analysis, and that run time can be optimized by properly selecting a configuration of CPU, memory, and interconnect.

scholarly journals Parallel high-performance computing algorithm to generate FEM-compliant volumetric mesh representations of biomolecules at atomic scale

2019 ◽  
Author(s):  
Jorge López ◽  
Salvador Botello ◽  
Rafael Herrera ◽  
Mauricio Carrillo-Tripp
Keyword(s):  
Finite Element ◽  
High Performance Computing ◽  
Mesh Generation ◽  
High Performance ◽  
Computational Study ◽  
Atomic Scale ◽  
Element Analysis ◽  
Performance Computing ◽  
Mesh Models ◽  
Memory Efficient

AbstractThe computational study of biomolecules has been undermined by the lack of models that accurately represent the structure of big complexes at the atomic level. In this work, we report the development of an algorithm to generate a volumetric mesh of a biomolecule, of any size and shape, based on its atomic structure. Our mesh generation tool leverages the octree algorithm properties with parallel high-performance computing techniques to produce a discretized hexahedral model faster than previous methods. The reported algorithm is memory efficient and generates volumetric meshes suitable to be used directly in Finite Element Analysis. We tested the algorithm by producing mesh models of different biomolecule types and complex size, and also performed numerical simulations for the largest case. The Finite Element results show that our mesh models reproduce experimental data.

Evaluation of Compressive Strengths of HPS Plate Systems Stiffened with Trapezoidal Stiffeners

2013 ◽  
Vol 671-674 ◽  
pp. 1025-1028
Author(s):  
Dong Ku Shin ◽  
Kyungsik Kim
Keyword(s):  
Finite Element Analysis ◽  
Finite Element ◽  
High Performance ◽  
Nonlinear Finite Element ◽  
Linear Strain ◽  
Element Analysis ◽  
Geometric Imperfections ◽  
Eurocode 3 ◽  
Initial Geometric Imperfections ◽  
Plate System

The ultimate compressive strengths of high performance steel (HPS) plate system stiffened longitudinally by closed stiffeners have been investigated by the nonlinear finite element analysis. Both conventional and high performance steels were considered in models following multi-linear strain hardening constitutive relationships. Initial geometric imperfections and residual stresses were also incorporated in the analysis. Numerical results have been compared to compressive strengths from Eurocode 3 EN 1993-1-5 and FHWA-TS-80-205. It has been found that although use of Eurocode 3 EN 1993-1-5 and FHWA-TS-80-205 may lead to highly conservative design strengths when very large column slenderness parameters are encountered

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