Reinhard Hemmerling

Relational Growth Grammars --- A Parallel Graph Transformation Approach with Applications in Biology and Architecture

We present the formalism of relational growth grammars. They are a variant of graph grammars with a principal application for plant modelling, where they extend the well-established, but limited formalism of L-systems. The main property is the application of rules in parallel, motivated by the fact that life is fundamentally parallel. A further speciality is the dynamic creation of right-hand sides on rule application. Relational growth grammars have been successfully used not only for plant modelling, but also to model general 3D structures or systems of Artificial Life. We illustrate these applications at several examples, all being implemented using our programming language XL which extends Java and provides an implementation of relational growth grammars.

Accelerating batch processing of spatial raster analysis using GPU

Batch processing of raster data performed by geographic information systems (GIS) is a time consuming procedure. Modern high performance GPUs are able to perform hundreds of arithmetical operations in parallel. These GPUs can help to reduce the computing time of such operations. In addition, most of the commonly used raster operations are I/O-bounded. Memory transfer between hard disk and RAM takes up more time than computations. The scope of this paper is to present an efficient two-level caching strategy for raster data and an acceleration of selected raster operations using the GPU, which were implemented as a plugin for the open source software GRASS. An example data flow based on a real world use-case will be presented and the obtainable and practically expectable speedup will be measured and discussed.

Modelling of Spatial Light Distribution in the Greenhouse: Description of the Model

In Dutch greenhouse horticulture, use of additional assimilation light in the form of lamps plays an important role. So far, little is known about the effect of lamp positions, types, and spectra, on light distribution per se and on light interception by the crop canopy in relation to the arrangement and architecture of different crops. We present here a new model of a SON-T assimilation lamp, implemented using the interactive modelling platform GroIMP. A set of virtual lamps is positioned in a simulated 3D greenhouse, which latter exhibits main geometric features and semitransparent surface textures imitating glass and construction elements. Here we show results of the simulation of spatial distribution of light. The application of such virtual lamps for the simulation of light interception in static virtual crops of rose and tomato is briefly illustrated and the extension of this model to other lamp types, such as LED, is discussed.

A programming language tailored to the specification and solution of differential equations describing processes on networks

We present an extension to the graph-transformation based programming language XL that allows easy specification and solution of differential equations on graphs.

Stochastic path tracing on consumer graphics cards

We present a path tracer using the GPU of a consumers graphics card to render images. It is implemented in Java and GLSL using GroIMP as modelling platform and runtime environment. The path tracer is capable of rendering primitives like sphere, cone, cylinder, box, plane and parallelogram. Procedurally generated materials as well as textures can be applied to those objects. The resulting image is rendered in HDR (high dynamic range).

Growing virtual plants for virtual worlds

As plants are an inevitable part of our world, virtual plants are an expected part of a virtual environment. We present a method for creating, growing and visualization of virtual plants in the virtual world. Plants are created in the open-source 3D modelling platform GroIMP, which is based on growth grammars implemented as the programming language XL (eXtended L-system language). Textures created from photographs of the plants are used to enhance realism of the models.