GPU-accelerated algorithm for asteroid shape modeling

Abstract

Abstract Modeling asteroid shapes from optical and radio telescope data is computationally expensive and current sequential-fit inversion algorithms are very slow, up until recently often taking days or weeks for larger models. The modeling process is comprised of many serialized independent calculations that can be parallelized with inexpensive and ubiquitous graphical processing unit (GPU) hardware. We have accelerated the SHAPE modeling algorithm (Hudson, 1994) with an Nvidia GPU and algorithm optimization while maintaining full backward compatibility, achieving speed boosts of 2.2x-19.3x over the established algorithm. The highest speed boosts achieved were for portions of the modeling process taking up a majority of processing time on the existing algorithm, moving the average speedup factor towards the upper end of the range. We use scale model asteroids to show that our method can model shapes that are both unique to the observed data and stable. High resolution complex vertex models benefit the most from the new algorithm because of its better scalability to problem size on GPU hardware. Specific algorithm changes include facet-parallel rendering, pixel-parallel delay-Doppler mapping, parallel reductions, and streamed frame operations.