The consequences of fixed time performance measurement

In measuring the performance of parallel computers, the usual method is to choose a problem and test the execution time as the processor count is varied. This model underlies definitions of `speedup,´ `efficiency,´ and arguments against parallel processing such as Ware´s (1972) formulation of Amdahl´s law (1967). Fixed time models use problem size as the figure of merit. Analysis and experiments based on fixed time instead of fixed size have yielded surprising consequences: the fixed time method does not reward slower processors with higher speedup; it predicts a new limit to speedup, which is more optimistic than Amdahl´s; it shows an efficiency which is independent of processor speed and ensemble size; it sometimes gives non-spurious superlinear speedup; it provides a practical means (the SLALOM benchmark) of comparing computers of widely varying speeds without distortion