high performance computing on graphics processing units: hgpu.org

Modern radio telescopes, such as the Low Frequency Array (LOFAR) in the north of the Netherlands, process the signal from the sky in software rather than expensive special purpose hardware, This gives the astronomers an unprecedented flexibility to perform a vast amount of various scientific experiments. However, designing the actual software that would give optimal performance for many different experiments, possibly also running on different hardware is a challenging task. Since optimizing the software by hand to fit the various experiments and hardware is unfeasible, we employ a technique called parameter auto-tuning to find the optimal solution. Auto-tuning is based on a construction of a more generic software which has the ability to explore its parameter space and choose the values optimal for the experiment and hardware at hand. In our work we devise a systematic approach for auto-tuning signal processing pipelines which is not limited to radio astronomy and can be easily extended to other fields as well. Since the computations in radio astronomy are suitable candidates for parallelization, we exploit the power of GPUs. For that purpose we use the OpenCL programming standard. Furthermore, we combine OpenCL with Java to gain the advantages of higher level programming language such as greater productivity and code portability.