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The streaming algorithms approach is presented for high performance biological sequence alignment using Graphics processing units (GPUs). This helps in speedups of order of magnitude enables fast performance of the graphics processing units.

Sequence alignment is a common and often repeated task in molecular biology. Typical alignment operations consist of finding similarities between a pair of sequences (pairwise sequence alignment) or a family of sequences (multiple sequence alignment). The need for speeding up this treatment comes from the rapid growth rate of biological sequence databases: Every year their size increases by a factor of 1.5 to 2. In this paper we present a new approach to high-performance biological sequence alignment based on commodity PC graphics hardware. Using modern graphics processing units (GPUs) for high-performance computing is facilitated by their enhanced programmability and motivated by their attractive price/performance ratio and incredible growth in speed. To derive an efficient mapping onto this type of architecture, we have reformulated dynamic-programming-based alignment algorithms as streaming algorithms in terms of computer graphics primitives. Our experimental results show that the GPU-based approach allows speedups of more than one order of magnitude with respect to optimized CPU implementations. [ABSTRACT FROM AUTHOR]

Virtual Reality (VR) technology is one of the most important innovations for research, development, and industrial production. In dentistry, VR technology will be useful in providing better education through simulation and in enhancing working procedures that are conventionally limited, e.g., the mechanical articulator. It is the purpose of this article to present concepts and strategies for a future replacement of the mechanical articulator by a virtual one.

The lack of suited diagnostic tools providing insight into patient specific flow characteristics of the nasal airflow is one of the main problems in functional diagnosis. Diagnostic methods currently used do not provide the necessary information for flow analysis. But the flow distribution is essential for a physiological respiration, in particular for cleaning, moistening and tempering of the inhaled air as well as for the olfactory function of the nose. To overcome this current situation a cooperation project of the ENT surgeons and computer graphic engineers was established to develop the computer assisted planning system STAN (Simulation Tool for Airflow in the human Nose) combining Computer Fluid Dynamics (CFD) with advanced Computer Graphic Technology. The idea of the STAN system is to perform patient specific airflow simulations in the patient's nasal cavities. Therefore a geometrical model of the nasal airways is derived from the patient's tomography scans. A discretization of the surrounded flow volume is made by a computational grid. To establish the flow simulation Finite Element Methods are performed on the grid. A tailored visualization is offered to the surgeon that overlaps the flow pattern to the patient's tomography data shown in the coronal, sagittal and transversal plane. The surgeon can not only analyze the patient's current respiratory situation he has also the possibility to describe the planned surgical intervention. The goal is to simulate the flow distribution that can be expected after the surgical intervention and to offer a possibility to validate various surgical strategies. To verify the simulation results experimental investigations and measurements are made in nasal models. Silicon Models of patient's nose channels are made to analyze flow characteristics. The CT or MR scans of the same patients are used as input data for the simulation. The experimental outcome is compared to the simulation results to validate this diagnostic approach.