Simulations of light scattering from nano-structured surface areas require substantial amount of computing time. The emergence of General Purpose Graphics Processing Units (GPGPUs) as affordable PC SIMD arithmetic coprocessors brings the necessary computing power to modern desktop PCs. In this paper we examine how the computation time of the Finite-Difference Time-Domain (FDTD), a classic numerical method for computing a solution to Maxwell's equations, can be reduced by leveraging the massively parallel architecture of GPGPUs cards. 2008 11th IEEE International Conference on Computational Science and Engineering 978-0-7695-3193-9/08 $25.00

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Die Mikro-und Nanotechnologie gehört zu den Schlüsseltechnologien des 21. Jahrhunderts mit hohen Wachstumsprognosen, wie auch die im Auftrag des BMBF durchgeführte Studie "Nanotechnologie als wirtschaftlicher Wachstumsmarkt" von 2004 ausführlich darstellt. Aus diesem Trend resultiert ein steigender Bedarf an Messsystemen, die Nanostrukturen prozessnah bzw. im Fertigungsprozess charakterisieren können. Virtuelle Messgeräte liefern Erkenntnisse zur Entwicklung neuartiger Messsysteme, Analyse und Optimierung bestehender Verfahren sowie die Bestimmung der Messunsicherheit und modellbasierten Korrektur systematischer Fehler. Der virtuelle Messprozess umfasst neben dem Messmittel auch die Probe und die Wechselwirkungen zwischen beiden. In diesem Beitrag werden virtuelle Messgeräte vorgestellt sowie deren Anwendung diskutiert. Schlagwörter: Virtuelle Messtechnik, Simulation, Messunsicherheit Virtual Measuring Instruments Definition and Development StatusMicro-and nanotechnology experienced a high economic growth in recent years. This yields in a growing demand for measuring instruments which are closely linked to the production process. Virtual measuring instruments provide knowledge for the development of new systems, the analysis and optimization of established devices as well as the determination of the uncertainty in measurement. The virtual measuring process consists of the measuring instrument, the sample, and the interaction between both. In this article examples of current developments of virtual instruments are presented and their way of utilization is discussed.

Modern massively parallel graphics cards (GPGPUs) offer a promise of dramatically reducing computation times of numerically-intensive dataparallel algorithms. As cards that are easily integrated into desktop PCs, they can bring computational power previously reserved for computer clusters to the office space. High performance rates make GPGPUs a very attractive target platform for scientific simulations. In this paper we present the lessons learned during the parallelization of a finite-difference time-domain method, an inherently data-parallel algorithm frequently used for numerical computations, on the state of the art graphics hardware.