Summary: We are concerned with the efficient implementation of symplectic implicit Runge-Kutta (IRK) methods applied to systems of Hamiltonian ordinary differential equations by means of Newton-like iterations. We pay particular attention to time-symmetric symplectic IRK schemes (such as collocation methods with Gaussian nodes). For an \(s\)-stage IRK scheme used to integrate a \(d\)-dimensional system of ordinary differential equations, the application of simplified versions of Newton iterations requires solving at each step several linear systems (one per iteration) with the same \(sd \times sd\) real coefficient matrix. We propose a technique that takes advantage of the symplecticity of the IRK scheme to reduce the cost of methods based on diagonalization of the IRK coefficient matrix. This is achieved by rewriting one step of the method centered at the midpoint on the integration subinterval and observing that the resulting coefficient matrix becomes similar to a skew-symmetric matrix. In addition, we propose a C implementation (based on Newton-like iterations) of Runge-Kutta collocation methods with Gaussian nodes that make use of such a rewriting of the linear system and that takes special care in reducing the effect of round-off errors. We report some numerical experiments that demonstrate the reduced round-off error propagation of our implementation.