Amdahl's law, named after computer architect Gene Amdahl, states that if F is the fraction of a calculation that is sequential, and (1-F) is the fraction that can be parallelised, then the maximum speedup that can be achieved by using P processors is 1 / (F + (1-F)/P). In the limit, as P tends to infinity, the maximum speedup tends to 1/F. In practice, price/performance ratio falls rapidly as P is increased once (1-F)/P is small compared to F.

As an example, if F is only 10%, the problem can be sped up by only a maximum of a factor of 10, no matter how large the value of P used. For this reason, parallel computing is only useful for either small numbers of processors, or problems with very low values of F: so-called embarrassingly parallel problems.

A great part of the craft of parallel programming consists of attempting to reduce F to the smallest possible value.

References:

• Gene Amdahl, "Validity of the Single Processor Approach to Achieving Large-Scale Computing Capabilities", AFIPS Conference Proceedings, (30), pp. 483-485, 1967.

External links

• Reevaluating Amdahl's Law