Profit-effective parallel computing

R esearchers widely use speedup, efficiency, and scalability1–3 to assess parallel-computing performance. These metrics encourage researchers to use any novel technique to design or improve a parallel system, without paying enough attention to the cost increase that such a technique incurs. However, as national-defense applications are downsizing, commercial applications are the dominant users of parallel systems. Customers and vendors are particularly concerned with whether a parallel system can make a profit. Customers and vendors frequently use the performance/cost ratio to compare systems.5 Based on this metric, David Wood and Mark Hill showed that parallel computing is more costeffective whenever the speedup is larger than the costup, a ratio of the parallel-computing cost to the sequential-computing cost.4 They also indicated that a cost-effective parallel computation does not necessarily require a linear speedup. In this article, we extend Wood and Hill’s work, from the profit point of view. Our major goal is to investigate financially justified parallel computing. To evaluate parallel computing’s effectiveness, we use a simple profitup metric to measure how performance, cost, and business production affect profit. We focus on investigating the relationship between cost-effective parallel computing and profit-effective parallel computing.