Annotation: The technology progress today makes it possible to treat most of the problems of physical geodesy by means of numerical arrangements hardly imaginable earlier. Nevertheless, considering an evaluation of spheroidal (spherical and ellipsoidal) harmonic functions in our typical tasks, we still observe a huge performance gap between our demands and capabilities of common CPUs. Methods used for calculating associated Legendre functions are mostly recursive and thus sequential. Therefore, it is challenging, but feasible, to arrange the processing of Legendre functions in a way that reduces memory utilisation and admits massive parallelism. Following this aim, we developed a streaming-parallel algorithm for computing oblate spheroidal harmonic functions and their derivatives. The algorithm is free of assumptions concerning the func-tion arguments, maximal degree/order or number of computation points and can be utilised on any data type, like a vector or scalar float, double or even integer numbers. Besides, it solves floating-point issues in the numerical treatment of Legendre functions. We demonstrate its Open Computing Language (OpenCL) implementation on a general-purpose graphics processing unit (GPGPU), which is ideal for its inexpensive computational power of some TFlops. Added performance benchmarks lead to the conclusion that our implementation on a single GPGPU device substantially outperforms recent multi-core CPUs, free of any precision penalty. Furthermore, thanks to the OpenCL standard, we can benefit from an excellent portability and scalability over heterogeneous parallel platforms. Let us note finally, that the topic presented is a matter of importance in many other application fields, not only in physical geodesy.


Source: VIII Hotine-Marussi Symposium on Mathematical Geodesy Source document: VIII Hotine-Marussi Symposium on Mathematical Geodesy; ISSN: 0939-9585
Extent: 9 stran
Publication type: sbornikove prispevky

The record appears in these collections:
Strock revision > Deleted