The numerical solution of ill-posed problems requires suitable regularization techniques. One possible option is to consider time integration methods to solve the Showalter differential equation numerically. The stopping time of the numerical integrator corresponds to the regularization parameter. A number of well-known regularization methods such as the Landweber iteration or the Levenberg- Marquardt method can be interpreted as variants of the Euler method for solving the Showalter dif- ferential equation. Motivated by an analysis of the regularization properties of the exact solution of this equation presented by (U. Tautenhahn, Inverse Problems 10 (1994) 1405-1418), we consider a variant of the exponential Euler method for solving the Showalter ordinary differential equation. We discuss a suitable discrepancy principle for selecting the step sizes within the numerical method and we review the convergence properties of (U. Tautenhahn, Inverse Problems 10 (1994) 1405-1418), and of our discrete version (M. Hochbruck et al., Technical Report (2008)). Finally, we present numerical experiments which show that this method can be efficiently implemented by using Krylov subspace methods to approximate the product of a matrix function with a vector. Mathematics Subject Classification. 65J20, 65N21, 65L05.