Acceleration of the myelin water fraction (MWF) mapping at R=6 using a Global and Local Deep Dictionary Learning Network (GLDDL) is demonstrated in this study. The global and the local spatiotemporal correlations in the relaxations are learned simultaneously. The global temporal encode-decoder layers are utilized to reduce the computational complexity of the local DL network and improve the denoising performance. The deep DL network utilizes the merits of traditional DL and deep learning to improve the reconstruction. The high-quality MWF maps obtained from the GLDDL network has demonstrated the feasibility to accelerate the whole brain MWF mapping in 1 minute.