Title:
Parallel explicit FEM algorithms using GPU's

dc.contributor.advisor Will, Kenneth M.
dc.contributor.author Banihashemi, Seyed Parsa
dc.contributor.committeeMember Vuduc, Richard
dc.contributor.committeeMember Yavari, Arash
dc.contributor.committeeMember White, Donald W.
dc.contributor.committeeMember Goodno, Barry J.
dc.contributor.department Civil and Environmental Engineering
dc.date.accessioned 2016-01-07T17:25:25Z
dc.date.available 2016-01-07T17:25:25Z
dc.date.created 2015-12
dc.date.issued 2015-11-12
dc.date.submitted December 2015
dc.date.updated 2016-01-07T17:25:25Z
dc.description.abstract The Explicit Finite Element Method is a powerful tool in nonlinear dynamic finite element analysis. Recent major developments in computational devices, in particular, General Purpose Graphical Processing Units (GPGPU's) now make it possible to increase the performance of the explicit FEM. This dissertation investigates existing explicit finite element method algorithms which are then redesigned for GPU's and implemented. The performance of these algorithms is assessed and a new asynchronous variational integrator spatial decomposition (AVISD) algorithm is developed which is flexible and encompasses all other methods and can be tuned based for a user-defined problem and the performance of the user's computer. The mesh-aware performance of the proposed explicit finite element algorithm is studied and verified by implementation. The current research also introduces the use of a Particle Swarm Optimization method to tune the performance of the proposed algorithm automatically given a finite element mesh and the performance characteristics of a user's computer. For this purpose, a time performance model is developed which depends on the finite element mesh and the machine performance. This time performance model is then used as an objective function to minimize the run-time cost. Also, based on the performance model provided in this research and predictions about the changes in GPU's in the near future, the performance of the AVISD method is predicted for future machines. Finally, suggestions and insights based on these results are proposed to help facilitate future explicit FEM development.
dc.description.degree Ph.D.
dc.format.mimetype application/pdf
dc.identifier.uri http://hdl.handle.net/1853/54391
dc.language.iso en_US
dc.publisher Georgia Institute of Technology
dc.subject Finite element method
dc.subject GPU
dc.subject Parallel processing
dc.subject Explicit dynamic analysis
dc.subject High performance computing
dc.title Parallel explicit FEM algorithms using GPU's
dc.type Text
dc.type.genre Dissertation
dspace.entity.type Publication
local.contributor.corporatename School of Civil and Environmental Engineering
local.contributor.corporatename College of Engineering
relation.isOrgUnitOfPublication 88639fad-d3ae-4867-9e7a-7c9e6d2ecc7c
relation.isOrgUnitOfPublication 7c022d60-21d5-497c-b552-95e489a06569
thesis.degree.level Doctoral
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