Abstract: In a data processing system for determining intersections between geometric objects, the work is split between a CPU and a stream processor. The intersection determination is controlled by the CPU. Data processing intensive parts of intersection algorithms, such as checking possible overlap of objects, checking overlap of normal fields of objects, approximating the extent of an object, approximating the normal fields of an object, or making conjectures for intersection topology and/or geometry between objects, are run on the stream processor. The results of the algorithmic parts run on the stream processor are used by the part of the algorithms run on the CPU. In cases where conjectures for the computational result are processed on the stream processor, the conjectures are checked for correctness by algorithms run on the CPU. If the correctness check shows that the result found is incomplete or wrong, additional parts of the algorithm are run on the CPU and possibly on the stream processor.

Abstract: The invention provides a method for spatially refining a computer generated l-dimensional (l>0) model in a computing environment, the l-dimensional model representing physical or geometrical properties, and where the l-dimensional model is represented by tensor product B-splines basis functions and l-dimensional coefficients, where the l-dimensional coefficients are in real or projective space, and the tensor product B-splines basis functions are spanning an r-variate spline space (r>0) having a parameter domain, the method comprising: a) inserting at least one axis parallel hyper rectangle degenerate in one dimension in said parameter domain, providing a splitting of a support of at least one of said tensor product B-spline basis functions; b) computing refined tensor product B-spline basis functions by subdivision on said at least one tensor product B-splines basis functions whose support is split, using at least one knot value of the at least one axis parallel hyper rectangle; and c) computing the re

Abstract: A computer apparatus is disclosed for determining high quality raster data generation of scalar fields or vector fields, represented by piecewise polynomials or piecewise rational functions. It comprise one or more CPUs operative to do portions of the raster data generation algorithm, initializing sub-algorithms thereof, control the sub-algorithms, and possibly read back the generated raster data or transfer the raster data to other processors in the system. The computer apparatus further comprises one or more stream processing units operative to receive parts of the raster data algorithm from the CPUs and to execute sub-algorithms of the raster data algorithm, resulting in raster data that can be directly visualized, read back to the CPU or transferred to other processors.

Abstract: The invention describes a method to convert geological response data to graphical raw data by using at least one stream processor for this purpose. The geological response data is pre-processed by a CPU and the preprocessed geological response data is fed into one or more stream processors. The stream processor then does the calculation intensive work on the preprocessed geological response data and returns the processing results back to the CPU which does some post-processing on the results coming from the stream processor Stream processors comprise single or multiple programmable GPUs, clusters/networks of nodes with one or several GPU's; cell processors (or processors derived from it) or a cluster of cell processor nodes, game computers (in the spirit of Sony's PlayStation, Nintendo's GameCube, etc.) or clusters of game computers.

Abstract: In a data processing system for determining intersections between geometric objects, the work is split between a CPU and a stream processor. The intersection determination is controlled by the CPU. Data processing intensive parts of intersection algorithms, such as checking possible overlap of objects, checking overlap of normal fields of objects, approximating the extent of an object, approximating the normal fields of an object, or making conjectures for intersection topology and/or geometry between objects, are run on the stream processor. The results of the algorithmic parts run on the stream processor are used by the part of the algorithms run on the CPU. In cases where conjectures for the computational result are processed on the stream processor, the conjectures are checked for correctness by algorithms run on the CPU. If the correctness check shows that the result found is incomplete or wrong, additional parts of the algorithm are run on the CPU and possibly on the stream processor.