Structured Adaptive Mesh Refinement (Structured AMR) enables simulations to adapt the domain resolution to save computation and storage, and has become one of the dominant data representations used by scientific simulations; however, efficiently rendering such data remains a challenge. We present an efficient approach for volume- and iso-surface ray tracing of Structured AMR data on GPU-equipped workstations, using a combination of two different data structures. Together, these data structures allow a ray tracing based renderer to quickly determine which segments along the ray need to be integrated and at what frequency, while also providing quick access to all data values required for a smooth sample reconstruction kernel. Our method makes use of the RTX ray tracing hardware for surface rendering, ray marching, space skipping, and adaptive sampling; and allows for interactive changes to the transfer function and implicit iso-surfacing thresholds. We demonstrate that our method achieves high performance with little memory overhead, enabling interactive high quality rendering of complex AMR data sets on individual GPU workstations.

While k-d trees are known to be effective for spatial indexing of sparse 3-d volume data, full reconstruction, e.g. due to changes to the alpha transfer function during rendering, is usually a costly operation with this hierarchical data structure. In a recent publication we showed how to port a clever state of the art k-d tree construction algorithm to a multi-core CPU architecture and by means of thorough optimization we were able to obtain interactive reconstruction rates for moderately sized to large data sets. The construction scheme is based on maintaining partial summed-volume tables that fit in the L1 cache of the multi-core CPU and that allow for fast occupancy queries. In this work we propose a GPU implementation of the parallel k-d tree construction algorithm and compare it with the original multi-core CPU implementation. We conduct a thorough comparative study that outlines performance and scalability of our implementation.

While fast spatial index construction for triangle meshes has gained a lot of attention from the research community in recent years, fast tree construction algorithms for volume data are still rare and usually do not focus on real-time processing. We propose a linear time bounding volume hierarchy construction algorithm based on a popular method for surface ray tracing of triangle meshes that we adapt for direct volume rendering with sparse volumes. We aim at interactive to real-time construction rates and evaluate our algorithm using a GPU implementation.

BACKGROUND: The massive amounts of data from next generation sequencing (NGS) methods pose various challenges with respect to data security, storage and metadata management. While there is a broad range of data analysis pipelines, these challenges remain largely unaddressed to date. RESULTS: We describe the integration of the open-source metadata management system iRODS (Integrated Rule-Oriented Data System) with a cancer genome analysis pipeline in a high performance computing environment. The system allows for customized metadata attributes as well as fine-grained protection rules and is augmented by a user-friendly front-end for metadata input. This results in a robust, efficient end-to-end workflow under consideration of data security, central storage and unified metadata information. CONCLUSIONS: Integrating iRODS with an NGS data analysis pipeline is a suitable method for addressing the challenges of data security, storage and metadata management in NGS environments.

BACKGROUND: Recent cancer genome studies on many human cancer types have relied on multiple molecular high-throughput technologies. Given the vast amount of data that has been generated, there are surprisingly few databases which facilitate access to these data and make them available for flexible analysis queries in the broad research community. If used in their entirety and provided at a high structural level, these data can be directed into constantly increasing databases which bear an enormous potential to serve as a basis for machine learning technologies with the goal to support research and healthcare with predictions of clinically relevant traits. RESULTS: We have developed the Cancer Systems Biology Database (CancerSysDB), a resource for highly flexible queries and analysis of cancer-related data across multiple data types and multiple studies. The CancerSysDB can be adopted by any center for the organization of their locally acquired data and its integration with publicly available data from multiple studies. A publicly available main instance of the CancerSysDB can be used to obtain highly flexible queries across multiple data types as shown by highly relevant use cases. In addition, we demonstrate how the CancerSysDB can be used for predictive cancer classification based on whole-exome data from 9091 patients in The Cancer Genome Atlas (TCGA) research network. CONCLUSIONS: Our database bears the potential to be used for large-scale integrative queries and predictive analytics of clinically relevant traits.

The development and production of consumer goods is increasingly affected by a world-wide distribution and specialization of development and production locations. Efficient IT tools are required for synchronizing decision makers, developer teams and production planners. In this paper we present the

Since the original paper of Lacroute and Levoy (1994), where the shear-warp factorization was also shown for perspective projections, a lot of work has been carried out using the shear-warp factorization with parallel projections. However, none of it has proved or improved the algorithm for the perspective projection. Also in Lacroute's Volpack library, the perspective shear-warp volume rendering algorithm is missing. This paper reports on an implementation of the perspective shear-warp algorithm, which includes enhancements for its application in immersive virtual environments. Furthermore, a mathematical proof for the correctness of the permutation of projection and warp is provided, so far a basic assumption of the shear-warp perspective projection.

The problems and advantages of integrating scientific computations and visualization into one common program system are examined. An important point is the direct feedback of information from the visualization into an ongoing simulation. Some strong and weak points of the varying approaches in different software packages are shown. The visualization component of the authors' program system and the advantages of its integration into the overall system are explained. The weak points in their system and the work remaining to deal with them are described.>