This talk presents the iteration-complexity of a Jacobi-type non-Euclidean proximal alternating direction method of multipliers (ADMM) variant for solving (i.e., finding approximate stationary points of) multi-block linearly constrained non-convex programs. Since the subproblems of this ADMM variant can be solved in parallel, the variant has great potential to solve large scale multi-block linearly constrained non-convex programming instances. Also, our analysis allows the Lagrange multiplier to be updated with a relaxation parameter in the interval (0, 2), and hence extends other previous works which only allow the parameter to chosen in the interval (0,1.618).