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There is now a CONTENT FREEZE for Mercury while we switch to a new platform. It began on Friday, March 10 at 6pm and will end on Wednesday, March 15 at noon. No new content can be created during this time, but all material in the system as of the beginning of the freeze will be migrated to the new platform, including users and groups. Functionally the new site is identical to the old one. webteam@gatech.edu
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School of Civil and Environmental Engineering
Ph.D. Thesis Defense Announcement
Parallel Explicit FEM Algorithms Using GPU's
By:
Seyed Parsa Banihashemi
Advisors:
Dr. Kenneth M. Will (CEE), Dr. Richard Vuduc (CSE)
Committee Members:
Dr. Barry J. Goodno (CEE), Dr. Donald W. White (CEE), Dr. Arash Yavari (CEE)
Date & Time: Thursday, October 22, 2015, at 1:00pm
Location: Sustainable Education Building, 122
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 variation 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 dependent 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.
