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Computational Fuel Economy
Why is power consumption so important, and what does it have to do
with reversibility? The chain of reasoning that links these concepts
is a fairly long and tangled one, but the individual steps are easy
enough to follow.
In the past two decades the performance of microprocessors has
improved by a factor of 1,000, but the trends that have made
computers more powerful have also made them more power-hungry. Some
chips dissipate more than 100 watts and require elaborate fans, heat
sinks and even liquid cooling. Designers would welcome another
thousandfold gain in performance, but they cannot cope with any
further increase in power density. Single chips that consume
electricity by the kilowatt are just not a practical option.
Where does all the energy go? Much power is lost because neither
conductors nor insulators are perfect; electrons meet resistance
where they ought to pass unopposed, and they leak through materials
where current ought to be blocked. Both of these problems will get
more severe as silicon devices continue to shrink. Another energy
drain is the need to accelerate and decelerate electric charges as
signals move through the circuitry; this cost goes up along with
processor speed. And it always takes energy to push electrons
"uphill" against a voltage gradient.
Some of the strategies for reducing the energy demands of a computer
are much like measures to improve the fuel economy of an automobile.
To get better gas mileage, you make a car lighter and
aerodynamically sleeker; likewise in digital circuits, you can
reduce inertia by using fewer electrons to represent each bit of
information, and you can cut resistive losses with better
conductors. In the car, you drive slower and more smoothly; in the
computer you operate at lower voltage and avoid abrupt swings in
voltage. For even greater savings in an automobile, you might try a
hybrid design, with a battery or a flywheel to recapture energy
invested in acceleration and hill-climbing; the electronic
counterpart is an experimental technology called charge recovery.
In the world of chipmaking, some of these energy-conserving measures
are already well-established tools, and others are likely to be
adopted soon. For example, copper is replacing aluminum in the metal
interconnections on some chips to improve conductivity. The voltage
levels of on-chip signals have fallen from 5 volts to as little as 1
volt. Further steps of the same general kind may well avert a
silicon energy crisis for another decade or two. But then what? If
the number of operations per second is to increase by a factor of
1,000 without raising power consumption, then the average energy per
operation must be reduced to a thousandth of its present value. Is
that possible, even in principle? What about a millionth?