Cost and time-cost effectiveness of multiprocessing

Speedup and efficiency, two measures for performance of pipelined computers, are now used to evaluate performance of parallel algorithms for multiprocessor systems. However, these measures consider only the computation time and number of processors used and do not include the number of the communication links in the system. The author defines two new measures, cost effectiveness and time-cost effectiveness, for evaluating performance of a parallel algorithm for a multiprocessor system. From these two measures two characterization factors for multiprocessor systems are defined and used to analyze some well-known multiprocessor systems. It is found that for a given penalty function, every multiprocessor architecture has an optimal number of processors that produces maximum profit. If too many processors are used, the higher cost of the system reduces the profit obtained from the faster solution. On the other hand, if too few processors are used, the penalty paid for taking a longer time to obtain the solution reduces the profit