The state of the art in Grid style data management is to achieve increased
resilience of data via multiple complete replicas of data files across multiple
storage endpoints. While this is effective, it is not the most space-efficient
approach to resilience, especially when the reliability of individual storage
endpoints is sufficiently high that only a few will be inactive at any point in
time. We report on work performed as part of GridPP\cite{GridPP}, extending the
Dirac File Catalogue and file management interface to allow the placement of
erasure-coded files: each file distributed as N identically-sized chunks of
data striped across a vector of storage endpoints, encoded such that any M
chunks can be lost and the original file can be reconstructed. The tools
developed are transparent to the user, and, as well as allowing up and
downloading of data to Grid storage, also provide the possibility of
parallelising access across all of the distributed chunks at once, improving
data transfer and IO performance. We expect this approach to be of most
interest to smaller VOs, who have tighter bounds on the storage available to
them, but larger (WLCG) VOs may be interested as their total data increases
during Run 2. We provide an analysis of the costs and benefits of the approach,
along with future development and implementation plans in this area. In
general, overheads for multiple file transfers provide the largest issue for
competitiveness of this approach at present.Comment: 21st International Conference on Computing for High Energy and
Nuclear Physics (CHEP2015
