Emerging next-generation sequencing technologies have opened up exciting new opportunities for genome sequencing by generating read data with a massive throughput. However, the generated reads are significantly shorter compared to the traditional Sanger shotgun sequencing method. This poses challenges for de novo assembly algorithms in terms of both accuracy and efficiency. And due to the continuing explosive growth of short read databases, there is a high demand to accelerate the often repeated long-runtime assembly task. In this paper, we present a scalable parallel algorithm to accelerate the de Bruijn graph-based genome assembly for high-throughput short read data.

We describe an approach to integrate multiple rendering back-ends under a common application layer for distributed systems. The primary goal was to find a practical and non-intrusive way to use potentially very different rendering back-ends in heterogeneous computing environments without impairing their strengths and without burdening the back-ends or the application with details of the cluster environment. Our approach is based on a mediator layer that can be plugged into the OpenSG infrastructure. This design allows us to elegantly extent OpenSG's low-level multithreading and clustering capabilities to our system. It also allows us to sync incremental changes very efficiently. We demonstrate results and problems with two case studies.

Searching protein sequence database is a fundamental and often repeated task in computational biology and bioinformatics. However, the high computational cost and long runtime of many database scanning algorithms on sequential architectures heavily restrict their applications for large-scale protein databases, such as GenBank. The continuing exponential growth of sequence databases and the high rate of newly generated queries further deteriorate the situation and establish a strong requirement for time-efficient scalable database searching algorithms. In this paper, we demonstrate how GPU clusters, powered by the Compute Unified Device Architecture (CUDA), OpenMP, and MPI parallel programming models can be used as an efficient computational platform to accelerate the popular BLASTP algorithm. Compared to GPU-BLAST 1.0-2.2.24, our implementation achieves speedups up to 1.6 on a single GPU and up to 6.6 on the 6 GPUs of a Tesla S1060 quad-GPU computing system. The source code is available at: http://sites.google.com/site/liuweiguohome/mpicuda-blastp

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 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 over one order of magnitude with respect to optimized CPU implementations.

Protein sequences with unknown functionality are often compared to a set of known sequences to detect functional similarities. Efficient dynamic programming algorithms exist for this problem, however current solutions still require significant scan times. These scan time requirements are likely to become even more severe due to the rapid growth in the size of these databases. In this paper, we present a new approach to bio-sequence database scanning using computer graphics hardware to gain high performance at low cost. To derive an efficient mapping onto this type of architecture, we have reformulated the Smith-Waterman dynamic programming algorithm in terms of computer graphics primitives. Our OpenGL implementation achieves a speedup of approximately sixteen on a high-end graphics card over available straightforward and optimized CPU Smith-Waterman implementations

Computer assisted operation planning systems win more and more recognition in the field of surgery. These systems offer new possibilities to prepare an intervention with the goal to shorten the expansive time in the operation room required for the intervention. The safest and most effective surgical approach should be selected. But often, it is difficult to transfer the output of the planning system to the intra-operative situation and so to consider the planning results in the real intervention. At the Fraunhofer Institute for Computer Graphics (IGD) in Darmstadt and the Centre for Advanced Media Technology (CAMTech) in Singapore, methods are developed to bridge the gap between the external planning session and the intra-operative case: augmented reality (AR) techniques are used to overlap preoperative scanned image data as well as results of the planning session to the operation field.

The use of virtual reality (VR) techniques for computer-aided diagnosis is revolutionizing the medical routing in various medical disciplines. Especially in the field of dentistry VR in combination with CAD/CAM technologies offers a high potential for implant planning/design resulting in a higher accuracy and a shorter therapy time period. The geometry of the teeth is recognisable and digitisable using an intraoral camera, the implant models can be designed with specialized CAD systems and the final implants are generated using a CNC machine. In this context the "Virtual Articulator" (VA) completes the digital manufacturing pipeline and offers the possibility to consider patient-specific jaw biomechanics in the implant generation process. The objective of this project is the development of a system for dental occlusion diagnosis. For this important diagnosis in today's dental routine the mechanical articulator is used. The VA simulates and augments the functionalities of the mechanical articulator. Therefore it takes a digital 3-D representation of the jaws as input data, generates a simulation of the jaw movements, and delivers a dynamical visualization of the occlusion points. The high technical demands to the system are given through the high accuracy necessary for dental applications and the large models that have to be handled in the system.

In today's automotive industry there is an increasing demand for VR technology, because it provides the possibility to switch from cost and time insensitive physical mock up's (PMU) to digital mock up's (DMU). Unfortunately many current VR applications are either limited in the way people can interact with them, or provide a large set of functions, which are hard to use. In this paper we present the design of a VR user interface for applications in the area of digital design review. The basic requirements of such an UI are the ease of use, and the ability to work simultaneously with a group of people on one system. Furthermore we investigate the functional requirements for this kind of application, including navigation, manipulation, examination and documentation of flaws in the design of the models. Documentation is stored as HTML and could therefore be easily transmitted between different parties. The design of the user interface is based on the basic interaction tasks (BIT'S), introduced by Foley et. al., which allow to build complex functionality on top of only a few interaction metaphors. Finally we evaluate the concept on a prototype implementation, done in cooperation with BMW AG.