  We summarize the status of Deep Underground Neutrino Experiment (DUNE)
Offline Software and Computing program. We describe plans for the computing
infrastructure needed to acquire, catalog, reconstruct, simulate and analyze
the data from the DUNE experiment and its prototypes in pursuit of the
experiment's physics goals of precision measurements of neutrino oscillation
parameters, detection of astrophysical neutrinos, measurement of neutrino
interaction properties and searches for physics beyond the Standard Model. In
contrast to traditional HEP computational problems, DUNE's Liquid Argon Time
Projection Chamber data consist of simple but very large (many GB) data objects
which share many characteristics with astrophysical images. We have
successfully reconstructed and simulated data from 4% prototype detector runs
at CERN. The data volume from the full DUNE detector, when it starts
commissioning late in this decade will present memory management challenges in
conventional processing but significant opportunities to use advances in
machine learning and pattern recognition as a frontier user of High Performance
Computing facilities capable of massively parallel processing. Our goal is to
develop infrastructure resources that are flexible and accessible enough to
support creative software solutions as HEP computing evolves.
