Performance Measuring Parameters and Issues of a Parallel System

The most widely accepted measure to evaluate the performance of a parallel system is speedup. Speedup (Sɴ) is defined as the ratio of the execution time (Tɴ) on a single processor, to the execution time (Tɴ) on N processors. Let’s discuss more about performance measuring parameters of parallel system.

The theoretical maximum speed that can be achieved with a parallel architecture of N identical processers working concurrently on a problem, is N. This is known as the ideal speedup.

In practice, the speedup is much less, since some architectures do not perform to the ideal level owing to conflicts over memory  access, communication delays, inefficient algorithms and mapping the natural concurrency in a computing problem.

But in some cases, the speedup can be obtained above the ideal speedup, due to anomalies in programming, compilation, architecture usage, etc.

For example, a single processor system may store all its data off-chip, whereas the multiprocessor system may processor system may store all its data off-chip, whereas the multiprocessor system may store all its data-on chip providing an unpredicted increase in performance.

Performance measuring parameters of parallel system

Another useful measure in evaluating the performance of a parallel system is efficiency (Eɴ) which can be defined as

Performance Measuring Parameters and Issues of a Parallel System

Performance Measuring Parameters of Parallel System

Efficiency can be interpreted as providing an indication of the average utilization of “N” processors, expressed as a percentage. Furthermore, this measure allows a uniform comparison of the various speedups obtained from a system containing different number of processors.

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