How well do STARLAB and NBODY compare? II: Hardware and accuracy
  Most recent progress in understanding the dynamical evolution of star
clusters relies on direct N-body simulations. Owing to the computational
demands, and the desire to model more complex and more massive star clusters,
hardware calculational accelerators, such as GRAPE special-purpose hardware or,
more recently, GPUs (i.e. graphics cards), are generally utilised. In addition,
simulations can be accelerated by adjusting parameters determining the
calculation accuracy (i.e. changing the internal simulation time step used for
each star).
  We extend our previous thorough comparison (Anders et al. 2009) of basic
quantities as derived from simulations performed either with STARLAB/KIRA or
NBODY6. Here we focus on differences arising from using different hardware
accelerations (including the increasingly popular graphic card
accelerations/GPUs) and different calculation accuracy settings.
  We use the large number of star cluster models (for a fixed stellar mass
function, without stellar/binary evolution, primordial binaries, external tidal
fields etc) already used in the previous paper, evolve them with STARLAB/KIRA
(and NBODY6, where required), analyse them in a consistent way and compare the
averaged results quantitatively. For this quantitative comparison, we apply the
bootstrap algorithm for functional dependencies developed in our previous
study.
  In general we find very high comparability of the simulation results,
independent of the used computer hardware (including the hardware accelerators)
and the used N-body code. For the tested accuracy settings we find that for
reduced accuracy (i.e. time step at least a factor 2.5 larger than the standard
setting) most simulation results deviate significantly from the results using
standard settings. The remaining deviations are comprehensible and explicable.
