Abstract: Simulating the thermodynamics of protein molecules is a computationally demanding task. Therefore, it is essential to have efficient simulation algorithms. Here, a few Monte Carlo algorithms are tested for simulating the thermodynamics of a short peptide in terms of an all-atom protein model. The methods are given a certain amount of CPU time and their efficiency is measured by the statistical error in estimated expected energy. Three methods, simulated tempering, reduced dynamical excluded volume and the multicanonical algorithm are found to be more efficient than the standard Metropolis algorithm. The results further indicate that for this system, simulated tempering is the most efficient method of the ones that were tested. It reduces the simulation time by a factor 7 compared with the Metropolis method.