AbstractIn this paper, we present a software system, OPAS (Optimal Allocation System), that incorporates the optimal allocation policy in the analysis of the time‐cost behaviour of parallel computations. OPAS assumes that the underlying system which supports the executions of parallel computations has a finite number of processors, that all the processors have the same speed and that the communication is achieved through a shared memory. OPAS defines the time cost as a function of the input, the algorithm, the data structure, the processor speed, the number of processors and the processing power allocation. In analysing the time cost of a computation, OPAS first uses the optimal allocation policy that we developed previously to determine the amount of processing power each node receives and then derives the computation's time cost. OPAS can evaluate different time‐cost behaviours, such as the minimum time cost, the maximum time cost, the average time cost and the time‐cost variance. It can also determine the speed‐up and efficiency, and plot the time‐cost curve and time‐cost distribution.
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