  In numerical simulations of many charged systems at the micro/nano scale, a
common theme is the repeated solution of the Poisson-Boltzmann equation. This
task proves challenging, if not entirely infeasible, largely due to the
nonlinearity of the equation and the high dimensionality of the physical and
parametric domains with the latter emulating the system configuration. In this
paper, we for the first time adapt a mathematically rigorous and
computationally efficient model order reduction paradigm, the so-called reduced
basis method (RBM), to mitigate this challenge. We adopt a finite difference
method as the mandatory underlying scheme to produce the {\em truth
approximations} of the RBM upon which the fast algorithm is built and its
performance is measured against. Numerical tests presented in this paper
demonstrate the high efficiency and accuracy of the fast algorithm, the
reliability of its error estimation, as well as its capability in effectively
capturing the boundary layer.
