RadioLensfit: an HPC Tool for Accurate Galaxy Shape Measurement with SKA
  The new generation radio telescopes, such as the Square Kilometre Array
(SKA), are expected to reach sufficient sensitivity and resolution to provide
large number densities of resolved faint sources, and therefore to open weak
gravitational lensing observations to the radio band. In this paper we present
RadioLensfit, an open-source tool for an efficient and fast galaxy shape
measurement for radio weak lensing shear. It performs a single source model
fitting in the Fourier domain, after isolating the source visibilities with a
sky model and a faceting technique. This approach makes real sized radio
datasets accessible to an analysis in this domain, where data is not yet
affected by the systematics introduced by the non-linear imaging process. We
detail the implementation of the code and discuss limitations of the source
extraction algorithm. We describe the hybrid parallelization MPI+OpenMP of the
code, implemented to exploit multi-node HPC infrastructures for accelerating
the computation and dealing with very large datasets that possibly cannot
entirely be stored in the memory of a single processor. Finally, we present
performance results both in terms of measurement accuracy and code scalability
on SKA-MID simulated datasets. In particular, we compare shape measurements of
1000 sources at the expected source density in SKA Phase 1 with the ones
obtained from the same dataset in a previous work by a joint fitting of the raw
visibility data, and show that results are comparable while the computational
time is highly reduced.
