Description
Over the last decade, the SunPy ecosystem, a Python solar data analysis environment, has evolved organically to serve the needs of scientists analyzing solar physics data, mostly on desktop and laptop computers. However, modern solar observatories are producing data volumes in the tens of petabytes, necessitating the need for parallelized and out-of-core computation. HelioCloud is a cloud computing environment tailored for heliophysics research and colocated with many terabytes of solar physics data. In this talk, we will show how the SunPy ecosystem, combined with Dask on HelioCloud, can be used to efficiently process high-resolution solar data.