One of the ways to execute a processing algorithm in high speed is parallel processing on multiple computing resources such as processors and functional units. To identify the minimum number of computing resources, the most important is the scheduling to determine when each operation in the processing algorithm is executed. Among feasible schedules satisfying all the data dependencies in the processing algorithm, an overlapped schedule can achieve the fastest execution speed for an iterative processing algorithm. In the case of processing algorithms with operations which are executed on some conditions, computing resources can be shared by those conditional operations. In this paper, we propose a scheduling method which derives an overlapped schedule where the required number of computing resources is minimized by considering the sharing by conditional operations.