The authors present a rank-two relaxed parallel splitting version of the augmented Lagrangian method (ALM) for multiple-block separable convex programming problems with linear equality constraints. The new algorithm adjusts the direct parallel splitting version of the ALM by both proximal regularization and relaxation techniques. It maintains a step size in $(0,2)$ for further relaxing the primal and dual variable to ensure its convergence. This paper is well written and structured, it advances science and may serve to support practical applications and future research as well.