  We develop a recently proposed importance-sampling Monte Carlo algorithm for
sampling rare events and quenched variables in random disordered systems. We
apply it to a two dimensional bond-diluted Ising model and study the Griffiths
singularity which is considered to be due to the existence of rare large
clusters. It is found that the distribution of the inverse susceptibility has
an exponential tail down to the origin which is considered the consequence of
the Griffiths singularity.
