In this paper, Coarse-Grained Reconfigurable Architectures (CGRAs) are capable of achieving both goals of high performance and flexibility. CGRAs not only improve performance by exploiting the features of repetitive computations, but also can adapt to diverse computations by dynamically changing configurations of an array of its internal Processing Elements (PEs) and their interconnections. This paper introduces approaches to mapping applications onto CGRAs supporting both integer and floating point arithmetic. After presenting an optimal formulation using integer linear programming, the authors present a fast heuristic mapping algorithm. Their experiments on randomly generated examples generate optimal mapping results using their heuristic algorithm for 97% through put. They observe similar results for practical examples from multimedia and 3-D graphics benchmarks.