Moore’s Law, Web Scale, and the Mess We’re In
In 1965, Gordon Moore wrote a three-page paper that described both the
consolidation of the electronics market toward integrated circuits, and the
doubling of the number of components in an integrated circuit every year for
at least a decade. In 1975, he revised this prediction to state that the number
of components on an integrated circuit would double every two years. This
prediction more or less held true until just recently — around 2012.
Several companies foresaw this slowdown in the rate Moore’s law predicted
and began to investigate alternative ways to increase computing power. As
the saying goes, necessity is the mother of innovation, and so it was in this
way that multicore processors were born.
This looked like a clever way to solve the bounding problems of Moore’s
law, but computer scientists soon found themselves facing down the limits of
another law: Amdahl’s law, named after computer architect Gene Amdahl.
Amdahl’s law describes a way in which to model the potential performance
gains from implementing the solution to a problem in a parallel manner.
Simply put, it states that the gains are bounded by how much of the program
must be written in a sequential manner.
For example, imagine you were writing a program that was largely GUI
based: a user is presented with an interface, clicks on some buttons, and stuff
happens. This type of program is bounded by one very large sequential
portion of the pipeline: human interaction. No matter how many cores you
make available to this program, it will always be bounded by how quickly the
user can interact with the interface.
Now consider a different example, calculating digits of pi. Thanks to a class
of algorithms called spigot algorithms, this problem is called embarrassingly
parallel, which — despite sounding made up — is a technical term which
means that it can easily be divided into parallel tasks. In this case, significant
gains can be made by making more cores available to your program, and your
new problem becomes how to combine and store the results.
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