  With the spread of multi- and many-core processors more and more typical task
is to re-implement some source code written originally for a single processor
to run on more than one cores. Since it is a serious investment, it is
important to decide how much efforts pays off, and whether the resulting
implementation has as good performability as it could be. The Amdahl's law
provides some theoretical upper limits for the performance gain reachable
through parallelizing the code, but it needs the detailed architectural
knowledge of the program code, does not consider the housekeeping activity
needed for parallelization and cannot tell how the actual stage of
parallelization implementation performs. The present paper suggests a
quantitative measure for that goal. This figure of merit is derived
experimentally, from measured running time, and number of threads/cores. It can
be used to quantify the used parallelization technology, the connection between
the computing units, the acceleration technology under the given conditions,
communication method within SoC, or the performance of the software
team/compiler.
