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The Graphics Processing Units (GPU) were originally designed for downloading 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…mehr

Produktbeschreibung
The Graphics Processing Units (GPU) were originally designed for downloading 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.
Autorenporträt
Mr Allan MANN acquired his MSc. at the National Cheng Kung University in Taiwan . He is now working as Advanced process development engineer at SRAM LLC in Taichung (Taiwan). He previously worked as process development engineer at Actuator Solutions Gmbh in Taoyuan (Taiwan).