Computation partitionings (CP) for the data parallel statements in a program have a dramatic impact on its performance. Although the problem has been widely studied, previous approaches focus on improving spatial locality of the chosen CP. A time slicing optimization framework is presented, which integrates many important optimization strategies, to select optimal CPs for parallel loop constructs. In the framework, a CP is represented by a directed graph, which not only represents a mapping of the operations in aparallel state-ment into processprs,but also specifies the dependency constraints for operations in different processors.This approach is to evaluate the efficiency of each CP choice and to find the one with the best overall execution time.The evaluation method synthesizes the four aspects of load-balance,operation-independence between processors, spatial locality and temporal locality for each CP.The framework has been implemented in a HPF compiler p-HPF for FORALL construct.Experimental results show that the framework is of generality with desired speedups for a wide variety of data-parallel applications.With a very little modification,it can also be applied to many other kinds of data-parallel statement.