Efficient multi-dimensional template placement is crucial in computationally
intensive matched-filtering searches for Gravitational Waves (GWs). Here, we
implement the Neighboring Cell Algorithm (NCA) to improve the detection volume
of an existing Compact Binary Coalescence (CBC) template bank. This algorithm
has already been successfully applied for a binary millisecond pulsar search in
data from the Fermi satellite. It repositions templates from over-dense regions
to under-dense regions and reduces the number of templates that would have been
required by a stochastic method to achieve the same detection volume. Our
method is readily generalizable to other CBC parameter spaces. Here we apply
this method to the aligned--single-spin neutron-star--black-hole binary
coalescence inspiral-merger-ringdown gravitational wave parameter space. We
show that the template nudging algorithm can attain the equivalent
effectualness of the stochastic method with 12% fewer templates
