  Measures of complexity and entropy have not converged to a single
quantitative description of levels of organization of complex systems. The need
for such a measure is increasingly necessary in all disciplines studying
complex systems. To address this problem, starting from the most fundamental
principle in Physics, here a new measure for quantity of organization and rate
of self-organization in complex systems based on the principle of least
(stationary) action is applied to a model system - the central processing unit
(CPU) of computers. The quantity of organization for several generations of
CPUs shows a double exponential rate of change of organization with time. The
exact functional dependence has a fine, S-shaped structure, revealing some of
the mechanisms of self-organization. The principle of least action helps to
explain the mechanism of increase of organization through quantity accumulation
and constraint and curvature minimization with an attractor, the least average
sum of actions of all elements and for all motions. This approach can help
describe, quantify, measure, manage, design and predict future behavior of
complex systems to achieve the highest rates of self organization to improve
their quality. It can be applied to other complex systems from Physics,
Chemistry, Biology, Ecology, Economics, Cities, network theory and others where
complex systems are present.
