generate inverted (inside-out) hexes from some inputs. Meshes are often created in serial on workstations, even when subsequent calculations over the mesh will be done in parallel on super-computers. This is both because of the limitation that most mesh generators are interactive, and because mesh generation runtime is typically insignificant compared to solver time. However, if the mesh is too large to fit in the memory of a single serial machine, or the mesh must be changed (adapted) during the simulation, meshing is done in parallel. Algebraic methods The grid generation by algebraic methods is based on mathematical interpolation function. It is done by using known functions in one, two or three dimensions taking arbitrary shaped regions. The computational domain might not be rectangular, but for the sake of simplicity, the domain is taken to be rectangular. The main advantage of the methods is that they provide explicit control of physical grid shape and spacing. The simplest procedure that may be used to produce boundary fitted computational mesh is the normalization transformation. For a nozzle, with the describing function the grid can easily be generated using uniform division in y-direction with equally spaced increments in x-direction, which are described by where denotes the y-coordinate of the nozzle wall. For given values of (, ), the values of (, ) can be easily recovered. Differential equation methods Like algebraic methods, differential equation methods are also used to generate grids. The advantage of using the partial differential equations (PDEs) is that the solution of grid generating equations can be exploited to generate the mesh. Grid construction can be done using all three classes of partial differential equations. Elliptic schemes Elliptic PDEs generally have very smooth solutions leading to smooth contours. Using its smoothness as an advantage Laplace's equations can preferably be used because the Jacobian found out to be positive as a result of maximum principle for harmonic functions. After extensive work done by Crowley (1962) and Winslow (1966) on PDEs by transforming physical domain into computational plane while mapping using Poisson's equation, Thompson et al. (1974) have worked extensively on elliptic PDEs to generate grids. In Poisson grid generators, the mapping is accomplished by marking the desired grid points on the boundary of the physical domain, with the interior point distribution determined through the solution of equations written below where, are the co-ordinates in the computational domain, while P and Q