Parallel GPU-based data-dependent triangulations

In this paper we introduce a new technique for data-dependent triangulation which is suitable for implementation on a GPU. Our solution is based on a new parallel version of the well known Lawson's optimization process and is fully compatible with restrictions of the GPU hardware. We test and compare the quality of our solution in an image reconstruction problem. In comparison with the standard implementations we achieve significant speed-up (eight times on average) with comparable quality of the reconstructed image. Further, several other improvements and optimizations are introduced and tested, and the results are discussed in detail.