Fine-grained visualization pipelines and lazy functional languages

The pipeline model in visualization has evolved from a conceptual model of data processing into a widely used architecture for implementing visualization systems. In the process, a number of capabilities have been introduced, including streaming of data in chunks, distributed pipelines, and demand-driven processing. Visualization systems have invariably built on stateful programming technologies, and these capabilities have had to be implemented explicitly within the lower layers of a complex hierarchy of services. The good news for developers is that applications built on top of this hierarchy can access these capabilities without concern for how they are implemented. The bad news is that by freezing capabilities into low-level services expressive power and flexibility is lost. In this paper we express visualization systems in a programming language that more naturally supports this kind of processing model. Lazy functional languages support fine-grained demand-driven processing, a natural form of streaming, and pipeline-like function composition for assembling applications. The technology thus appears well suited to visualization applications. Using surface extraction algorithms as illustrative examples, and the lazy functional language Haskell, we argue the benefits of clear and concise expression combined with fine-grained, demand-driven computation. Just as visualization provides insight into data, functional abstraction provides new insight into visualization

Unsteady Simulation of the Viscous Flow About a V-22 Rotor and Wing in Hover

Results of an unsteady thin-layer Navier-Stokes simulation of a 0.658-scale V-22 rotor and wing configuration in hover are presented. All geometric components of the flapped-wing and rotor test rig, including rotor blades, are accurately modeled. Rotor motion and rotor/airframe interference effects are simulated directly using moving body overset grid methods. Tiltrotor hover aerodynamics are visualized via unsteady particle trace images. Wing download predictive ability is demonstrated. Simulation results are compared with experimental data

Visualization of flow fields in the web platform

Visualization of vector fields plays an important role in research activities nowadays -- Web applications allow a fast, multi-platform and multi-device access to data, which results in the need of optimized applications to be implemented in both high-performance and low-performance devices -- Point trajectory calculation procedures usually perform repeated calculations due to the fact that several points might lie over the same trajectory -- This paper presents a new methodology to calculate point trajectories over highly-dense and uniformly-distributed grid of points in which the trajectories are forced to lie over the points in the grid -- Its advantages rely on a highly parallel computing architecture implementation and in the reduction of the computational effort to calculate the stream paths since unnecessary calculations are avoided, reusing data through iterations -- As case study, the visualization of oceanic currents through in the web platform is presented and analyzed, using WebGL as the parallel computing architecture and the rendering Application Programming Interfac

Visualisation of flow fields in the web platform

Visualization of vector fields plays an important role in research activities nowadays. Web applications allow a fast, multi-platform and multi-device access to data, which results in the need of optimized applications to be implemented in both high and low-performance devices. The computation of trajectories usually repeats calculations due to the fact that several points might lie over the same trajectory. This paper presents a new methodology to calculate point trajectories over a highly-dense and uniformly-distributed grid of points in which the trajectories are forced to lie over the points in the grid. Its advantages rely on a highly parallel computing implementation and in the reduction of the computational effort to calculate the stream paths since unnecessary calculations are avoided by reusing data through iterations. As case study, the visualization of oceanic streams in the web platform is presented and analyzed, using WebGL as the parallel computing architecture and the rendering engine

Helicopter Rotor Blade Computation in Unsteady Flows Using Moving Overset Grids

An overset grid thin-layer Navier-Stokes code has been extended to include dynamic motion of helicopter rotor blades through relative grid motion. The unsteady flowfield and airloads on an AH-IG rotor in forward flight were computed to verify the methodology and to demonstrate the method's potential usefulness towards comprehensive helicopter codes. In addition, the method uses the blade's first harmonics measured in the flight test to prescribe the blade motion. The solution was impulsively started and became periodic in less than three rotor revolutions. Detailed unsteady numerical flow visualization techniques were applied to the entire unsteady data set of five rotor revolutions and exhibited flowfield features such as blade vortex interaction and wake roll-up. The unsteady blade loads and surface pressures compare well against those from flight measurements. Details of the method, a discussion of the resulting predicted flowfield, and requirements for future work are presented. Overall, given the proper blade dynamics, this method can compute the unsteady flowfield of a general helicopter rotor in forward flight

Streamline Integration using MPI-Hybrid Parallelism on a Large Multi-Core Architecture

Streamline computation in a very large vector field data set represents a significant challenge due to the non-local and datadependentnature of streamline integration. In this paper, we conduct a study of the performance characteristics of hybrid parallel programmingand execution as applied to streamline integration on a large, multicore platform. With multi-core processors now prevalent in clustersand supercomputers, there is a need to understand the impact of these hybrid systems in order to make the best implementation choice.We use two MPI-based distribution approaches based on established parallelization paradigms, parallelize-over-seeds and parallelize-overblocks,and present a novel MPI-hybrid algorithm for each approach to compute streamlines. Our findings indicate that the work sharing betweencores in the proposed MPI-hybrid parallel implementation results in much improved performance and consumes less communication andI/O bandwidth than a traditional, non-hybrid distributed implementation

Visuelle Analyse großer Partikeldaten

Partikelsimulationen sind eine bewährte und weit verbreitete numerische Methode in der Forschung und Technik. Beispielsweise werden Partikelsimulationen zur Erforschung der Kraftstoffzerstäubung in Flugzeugturbinen eingesetzt. Auch die Entstehung des Universums wird durch die Simulation von dunkler Materiepartikeln untersucht. Die hierbei produzierten Datenmengen sind immens. So enthalten aktuelle Simulationen Billionen von Partikeln, die sich über die Zeit bewegen und miteinander interagieren. Die Visualisierung bietet ein großes Potenzial zur Exploration, Validation und Analyse wissenschaftlicher Datensätze sowie der zugrundeliegenden Modelle. Allerdings liegt der Fokus meist auf strukturierten Daten mit einer regulären Topologie. Im Gegensatz hierzu bewegen sich Partikel frei durch Raum und Zeit. Diese Betrachtungsweise ist aus der Physik als das lagrange Bezugssystem bekannt. Zwar können Partikel aus dem lagrangen in ein reguläres eulersches Bezugssystem, wie beispielsweise in ein uniformes Gitter, konvertiert werden. Dies ist bei einer großen Menge an Partikeln jedoch mit einem erheblichen Aufwand verbunden. Darüber hinaus führt diese Konversion meist zu einem Verlust der Präzision bei gleichzeitig erhöhtem Speicherverbrauch. Im Rahmen dieser Dissertation werde ich neue Visualisierungstechniken erforschen, welche speziell auf der lagrangen Sichtweise basieren. Diese ermöglichen eine effiziente und effektive visuelle Analyse großer Partikeldaten