Chip multiprocessing (or multiprocessor system-on-a-chip) is a technique that combines two or more processor cores on a single piece of silicon to enhance computing performance. An important problem to be addressed in executing applications on an on-chip multiprocessor environment is to select the most suitable number of processors to use for a given objective function (e.g., minimizing execution time or energy-delay product) under multiple constraints. Previous research proposed an ILP-based solution to this problem that is based on exhaustive evaluation of each nest under all possible processor sizes. In this paper, we take a different approach and propose a pure runtime strategy for determining the best number of processors to use at run-time. This approach is more general than static techniques and can be applicable in situations where the latter cannot be.