- The parallelization and implementation of Gauss-Seidel (G-S) algorithms for power flow analysis have been investigated previously. Numerous runs to demonstrate the speedup have been illustrated on a Sequent Balance shared-memory multi-instruction, multidata access (SM MIMD) machine. The authors extend the idea and investigate the effects of acceleration factors. It is shown on systems ranging from teens to thousands that when the acceleration factors are used, the implementation using colour-by-colour synchronization is more reliable and has better convergence rate, even though it takes longer time to synchronize. The authors also analyze the dependence of synchronization overhead in terms of system sizes, network connection and number of processors. Comparisons between G-S and fast decoupled load-flow algorithms are also made. The implications on nCUBE implementations are also discussed. It is also shown that the idea of parallel G-S algorithm can be easily extended to solve the transient stability problem which involves a set of algebraic differential equations.