  Robust measurements based on current large-scale structure surveys require
precise knowledge of statistical and systematic errors. This can be obtained
from large numbers of realistic mock galaxy catalogues that mimic the observed
distribution of galaxies within the survey volume. To this end we present a
fast, distributed-memory, planar-parallel code, L-PICOLA, which can be used to
generate and evolve a set of initial conditions into a dark matter field much
faster than a full non-linear N-Body simulation. Additionally, L-PICOLA has the
ability to include primordial non-Gaussianity in the simulation and simulate
the past lightcone at run-time, with optional replication of the simulation
volume. Through comparisons to fully non-linear N-Body simulations we find that
our code can reproduce the $z=0$ power spectrum and reduced bispectrum of dark
matter to within 2% and 5% respectively on all scales of interest to
measurements of Baryon Acoustic Oscillations and Redshift Space Distortions,
but 3 orders of magnitude faster. The accuracy, speed and scalability of this
code, alongside the additional features we have implemented, make it extremely
useful for both current and next generation large-scale structure surveys.
L-PICOLA is publicly available at https://cullanhowlett.github.io/l-picola
