  We present numerical simulations that allow us to compute the number of ways
in which $N$ particles can pack into a given volume $V$.
  Our technique modifies the method of Xu et al. (Phys. Rev. Lett. 106, 245502
(2011)) and outperforms existing direct enumeration methods by more than 200
orders of magnitude. We use our approach to study the system size dependence of
the number of distinct packings of a system of up to 128 poly-disperse soft
disks. We show that, even though granular particles are distinguishable, we
have to include a factor $1/N!$ to ensure that the entropy does not change when
exchanging particles between systems in the same macroscopic state. Our
simulations provide strong evidence that the packing entropy, when properly
defined, is extensive. As different packings are created with unequal
probabilities, it is natural to express the packing entropy as $S=-\sum_i
p_i\ln p_i -\ln N!$, where $p_i$ denotes the probability to generate the $i$-th
packing. We can compute this quantity reliably and it is also extensive. The
granular entropy thus (re)defined, whilst distinct from the one proposed by
Edwards assumed (J. Phys.: Condens.Matter 2, SA63(1990)), does have all the
properties Edwards assumed.
