Fred Viezens

Visualization in Health Grid Environments: A Novel Service and Business Approach

Advanced visualization technologies are gaining major importance to allow presentation and manipulation of high dimensional data. Since new health technologies are constantly increasing in complexity, adequate information processing is required for diagnostics and treatment. Therefore, the German D-Grid initiative started to build visualization centers in 2008, which have recently been embedded into the existing compute and storage infrastructure. This paper describes an analysis of this infrastructure and the interplay with life science applications for 3D and 4D visualization and manipulation. Furthermore, the performance and business aspects regarding accounting, pricing and billing are investigated. The results show the viability and the opportunities for further optimization of this novel service approach and the possibilities for a sustainable business scenario.

Enabling Parallel Computing of a Brain Connectivity Map Using the MediGRID-Infrastructure and FSL

The non-invasive method to track fibers of the human brain by analyzing diffusion weighted magnetic resonance images improves research of human brain structures and becomes therefore increasingly important. With fiber tracking, a connectivity map which depicts the degree of connectivity of the single voxels can be generated and used to improve knowledge about the human brain. Several tools exist to produce connectivity maps. One of them is part of the FMRIB Software Library (FSL) and free for non-commercial purposes. Due to long and therefore impracticable computing time on small computer cluster solutions, a GUI and the necessary software were implemented for the German MediGRID infrastructure. This was achieved by using wrapper scripts and a workflow for the Generic Workflow Execution Service (GWES). The solution is about 15 times faster than a small local cluster installation, depending on the number of employed MediGRID resources. This enables processing of connectivity maps for practical use in biomedical research. By using the D-Grid infrastructure, this solution is also suitable for small institutes without compute center capacities. For usability reasons, the GUI ConBrain was developed.

An interdisciplinary practical course on the application of grid computing

This article gives an overview of the organization and realization of an interdisciplinary practical course on grid computing. Both the lecturers and the attendees came from diverse backgrounds and disciplines including computer science, physics, medicine, and the humanities. We describe the management of the course, the assignments, the infrastructure developed and experienced in this interdisciplinary practical course at the University of Göttingen. The challenges and issues, the benefits, the expectations and their fulfillment are discussed. The experiences of the course show that diverse disciplines can be brought together to convey the benefits of grid technology by experiencing varied grid applications in production-like grid environments.

A Prototype System for Advance Reservations in a Biomedical Grid Computing Visualization Infrastructure

The infrastructure of the German Grid Initiative is mainly used for computational jobs. A visualization infrastructure to process and visualize, among others, medical imaging and genome data, was set up for the German biomedical community. Interactive jobs like these require advance reservations, since they are used in combination with computational jobs. Thus, a reservation management system is needed. An evaluation of the existing scheduling system, and of solutions with other scheduling tools, showed that no existing approach fits all of the requirements. Therefore, a new solution had to be found. Within this work, the prototype of a database-based reservation management system, which uses the MediGRID portal as a user interface, is described. This system allows the advance reservation of time slots for visualization sessions. Challenges of this system, e.g. the combined use of resources with computational jobs and visualization sessions, are discussed.