Paper Info
Title
Savu: A Python-based, MPI Framework for Simultaneous Processing of Multiple, N-dimensional, Large Tomography Datasets.
Abstract
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. 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.
Year
Venue
Field
2016
arXiv: Distributed, Parallel, and Cluster Computing
Hierarchical Data Format,Tomographic reconstruction,Computer graphics (images),Computer science,Usability,Real-time computing,Tomography,Computational science,Modular design,Plug-in,Light source,Python (programming language)
DocType
Volume
Citations 
Journal
abs/1610.08015
1
PageRank 
References 
Authors
0.36
0
2
Name
Order
Citations
PageRank
Nicola Wadeson110.36
Mark Basham212.05