2016/10/24 by Nicola Wadeson, Wadeson, Nicola, Mark Basham +1 · 1 citation
Computer Science · Engineering · Medicine · Physics and Astronomy · #Advanced X-ray Imaging Techniques #Advanced X-ray and CT Imaging #Computational Physics and Python Applications #Computer Vision and Pattern Recognition (cs.CV) #Databases (cs.DB) #Distributed #Distributed and Parallel Computing Systems #FOS: Computer and information sciences #Medical Imaging Techniques and Applications #Parallel #Reservoir Engineering and Simulation Methods #and Cluster Computing (cs.DC)
paper · pdf · doi:10.48550/arxiv.1610.08015
openalex publication_date 2016/10/24 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
Diamond Light Source (DLS), the UK synchrotron facility, attracts scientists from across the world to perform ground-breaking x-ray experiments. With over 3000 scientific users per year, vast amounts of data are collected across the experimental beamlines, with the highest volume of data collected during tomographic imaging experiments. A growing interest in tomography as an imaging technique, has led to an expansion in the range of experiments performed, in addition to a growth in the size of the data per experiment. Savu is a portable, flexible, scientific processing pipeline capable of processing multiple, n-dimensional datasets in serial on a PC, or in parallel across a cluster. Developed at DLS, and successfully deployed across the beamlines, it uses a modular plugin format to enable experiment-specific processing and utilises parallel HDF5 to remove RAM restrictions. The Savu design, described throughout this paper, focuses on easy integration of existing and new functionality, flexibility and ease of use for users and developers alike.