review articles

C O L L A G E B Y A N D R I J B O R Y S A S S O C I A T E S / S H U T T E R S T O C K

THE IMPENDING DEMISE of Moore’s Law has begun to
broadly impact the computing research community. 38

Moore’s Law has driven the computing industry for many decades, with nearly every aspect of society benefiting from the advance of improved computing processors, sensors, and controllers. Behind these products has been a considerable research industry, with billions of dollars invested in fields ranging from computer science to electrical engineering.

Fundamentally, however, the exponential growth
in computing described by Moore’s Law was driven
by advances in materials science. 30, 37 From the start,
the power of the computer has been limited by the
density of transistors. Progressive advances in how
to manipulate silicon through advancing lithography
methods and new design tools have kept advancing
computing in spite of perceived limita-
tions of the dominant fabrication pro-
cesses of the time. 37
There is strong evidence that this
time is indeed different, and Moore’s
Law is soon to be over for good. 3, 38 Al-
ready, Dennard scaling, Moore’s Law’s
lesser known but equally important
parallel, appears to have ended. 11 Den-
nard’s scaling refers to the property
that the reduction of transistor size
came with an equivalent reduction of
required power. 8 This has real conse-
quences—even though Moore’s Law
has continued over the last decade,
with feature sizes going from ~65nm
to ~10nm; the ability to speed up pro-
cessors for a constant power cost has
stopped. Today’s common CPUs are
limited to about 4GHz due to heat gen-
eration, which is roughly the same as
they were 10 years ago. While Moore’s
Law enables more CPU cores on a chip
(and has enabled high power systems
such as GPUs to continue advancing),
there is increasing appreciation that
feature sizes cannot fall much further,
with perhaps two or three further gen-
erations remaining prior to ending.
Multiple solutions have been pre-
sented for technological extension of
Moore’s Law, 3, 33, 38, 39 but there are two
main challenges that must be ad-
dressed. For the first time, it is not im-
mediately evident that future materials
Neural
Algorithms
and Computing
Beyond
Moore’s Law
DOI: 10.1145/3231589

Advances in neurotechnologies are reigniting opportunities to bring neural computation insights into broader computing applications.

BY JAMES B. AIMONE

key insights

˽ While Moore’s Law is slowing down, neuroscience is experiencing a revolution, with technology enabling scientists to have more insights into the brain’s behavior than ever before and thus positioning the neuroscience field to provide a long-term source of inspiration for novel computing solutions.

˽ Extending the reach of brain-inspiration into computing will not only make current AI methods better, but looking beyond the brain’s sensory systems can also expand the reach of AI into new applications.

˽ Realizing the full potential of brain-inspired computing requires increased collaborations and sharing of knowledge between the neuroscience, computer science, and neuromorphic hardware communities.