MENUS-PGG: A mapping environment for unstructured and structured numerical parallel grid generation. MENUS-PGG is a problem solving environment (PSE) for developing parallel algorithms that generate structured and unstructured static and adaptive grids (or meshes) required for the implementation of scalable parallel partial differential equation (PDE) solvers based on domain decomposition methods. Whereas the first generation PSEs for the numerical solution of PDEs on distributed memory multiprocessor systems are based on the data mapping of sequentially generated grids and support only the data parallel programming model, MENUS-PGG generates and maintains grids on the processors of parallel/distributed systems and combines the most valuable aspects of the data parallel programming model with the flexibility of the taks parallel programming model. MENUS-PGG assumes a machine model that consists of homogeneous and heterogeneous clusters of processors operating in a distributed address space implemented on a remote memory modules via message passing through a high speed interconnection network. The major contribution of MENUS-PGG should be the reduction of the pre-processing overhead required by the data parallel PDE solvers and the efficient maintenance of the distributed data structures that support h, p, and hp- refinements. We present preliminary results indicating that the parallel grid generation results in a substandard reduction of the pre-processing overhead needed for the solution of the data mapping problem