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Diamond Light Source (DLS), the UK synchrotron facility, attracts scientistsfrom across the world to perform ground-breaking x-ray experiments. With over3000 scientific users per year, vast amounts of data are collected across theexperimental beamlines, with the highest volume of data collected duringtomographic imaging experiments. A growing interest in tomography as an imagingtechnique, has led to an expansion in the range of experiments performed, inaddition to a growth in the size of the data per experiment.  Savu is a portable, flexible, scientific processing pipeline capable ofprocessing multiple, n-dimensional datasets in serial on a PC, or in parallelacross a cluster. Developed at DLS, and successfully deployed across thebeamlines, it uses a modular plugin format to enable experiment-specificprocessing and utilises parallel HDF5 to remove RAM restrictions. The Savudesign, described throughout this paper, focuses on easy integration ofexisting and new functionality, flexibility and ease of use for users anddevelopers alike.

Savu: A Python-based, MPI Framework for Simultaneous Processing of Multiple, N-dimensional, Large Tomography Datasets