Amdahl’s law is a model for the relationship between the expected speedup of parallelized implementations of an algorithm relative to the serial algorithm, under the assumption that the problem size remains the same when parallelized. For example, if for a given problem size a parallelized implementation of an algorithm can run 12% of the algorithm’s operations arbitrarily quickly while the remaining 88% of the operations are not parallelizable, Amdahl’s law states that the maximum speedup of the parallelized version is 1/1 – 0.12 = 1.136 times as fast as the non-parallelized implementation.
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