Parallelization with Different API on Multicore Architecture

Georg Rempfer
Institute for Computational Physics, University of Stuttgart
University of Stuttgart, 2013


   title={A Lattice based Model for Electrokinetics},

   author={Rempfer, Georg},



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Soft matter as a research topic extends over fields from a multitude of disciplines. Biological systems are nearly exclusively composed of soft matter. Nearly everything that animals eat is considered soft matter. Large parts of chemistry deal with soft matter, such as the whole field of polymers. Many materials, expecially modern ones, are soft matter. Due to the wide spectrum of systems traditionally considered to be soft matter, it is impossible to find a concise and precise criterion for what exactly falls within that category. One characteristic that the majority of soft matter systems share is that neither energy, nor entropy completely dominates their dynamics. Similarily wide spread are the applications of soft matter systems. The most important application is probably the discovery and subsequent refinement of plastics, a material cheaper, easier to process, and more flexible in its application than any before. Also noteworthy are liquid crystals, and more recently e-ink displays, and of course, DNA sequencing using gel electrophoresis. Compared to other fields in physics, soft matter is notorious for the absence of powerful analytical methods to describe these systems. The underlying reason for this is the lack of symmetry, due to the entropically induced randomness. Statistical mechanics offer a framework often applicable to soft matter systems, however, this usually only includes powerful tools for systems in thermodynamic equilibrium. The lack of analytical tools makes soft matter systems prime candidates for computer simulations. While in the past, due to performance limitations, computer simulations of soft matter systems were limited to very crude models or very small system sizes, the continuously increased availability of high performance computing platforms for academic research and the advent of commodity hardware with considerable computational power has lead to the widespread development of software tools for modeling to soft matter systems and often freely available under open source licenses.
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