Static and Dynamic Finite Element Analysis Using Parallel Programming on GPU with OpenCL

Abstract

Modern engineering systems are becoming increasingly complex there is a need of more and more degrees of freedom to simulate their accurate behavior Due to the limitation in computing capabilities there is an urge of finding a new concept for simulating large problems The Graphics Processing Units (GPU) were originally designed for offloading graphical display but with the improved capabilities of GPU the use of GPU for General Purpose Programming (GPGPU) has been noticed Due to the parallel architecture which allows the concurrency of the tasks GPU can be used for solving large systems of equations Implementation of the Finite Element Method on GPU architecture is quite straightforward because this method deals with linear equations or ordinary differential equations and when a problem has a large number of degrees of freedom the use of GPU capabilities can significantly decrease the computation time Two specific examples are the transient analysis and the static analysis which can reach higher performance using parallel programming By using appropriate numerical methods and techniques for matrix-vectors operations such as the Conjugate Gradient method the solution of a linear system using an AMD HD 7970 can be found 11 times faster than using an Intel i7 By using an appropriate precondition matrix in the Preconditioned Conjugate Gradient method (PCG) the solution can be found 14 times faster for a problem involving 50000 degrees of freedom Transient analysis of 3D problems show that using the Newmark method of integration with about 50000 degrees of freedom the solution can be found 18 times faster on the AMD HD 7970 Such high levels of performance are unable with current processors (CPU) even the most powerful ones

Date of Award	2014 Jun 25
Original language	English
Supervisor	Siu-Tong Choi (Supervisor)