This work compares two strategies to fit parameters of equations of state in parallel computers, emphasizing solutions that require few changes to existing sequential programs. One strategy uses the conventional Nelder-Mead algorithm coupled with parallel objective function evaluation (SSPO). The other strategy uses a parallel Nelder-Mead algorithm coupled with sequential objective function evaluation (PSSO). The PSSO strategy, which executes parallel one-dimensional searches during each iteration, is simpler to implement and converged to parameter sets with objective functions smaller than those obtained by the SSPO strategy. The SSPO strategy produced speedups consistent with the number of processes used and is more suitable when many processors are available. Both strategies are potentially useful and choosing between them is a matter of convenience, depending on the problem at hand. With parallel computers increasingly available, the easy implementation and convenience of these two strategies should appeal to developers and users of thermodynamic models.
Equations of state; Parallel; Message passing interface; Parameter fitting
