In this work we present the parallelisation of the global strategy with first least-connected node (GS-FLCN), which is a novel structural technique for the classification of unmeasured variables in process plant instrumentation design. The algorithm aims at partitioning the process' occurrence matrix to a specific block lower-triangular form. A parallel master-workers philosophy is employed to search for all the paths of a given length existing in the associated graph. The code was conceived for distributed environments and the implementation was carried out using the parallel virtual machine (PVM) library. The performance of the parallel algorithm was tested for industrial case studies and the results were compared with those yielded by the sequential version. The time savings achieved thanks to the parallelisation. were significant. Besides, in the parallel version, more paths can be explored per unit time. In practice, this implies greater robustness.