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Ask Jonathan Koomey About 'Koomey's Law'
A few weeks back, we posted a story here that described Koomey's Law, which (in the spirit of Moore's Law) identifies a long-standing trend in computer technology. While Moore's prediction centers on the transistor density of microprocessors, Jonathan Koomey focuses instead on computing efficiency — in a nutshell, computing power per watt, rather than only per square nanometer. In particular, he asserts that the energy efficiency of computing doubles every 1.5 years. (He points out that calling this a "law" isn't his idea, or his doing — but it's sure a catchy turn of phrase.) Koomey has agreed to respond to your questions about his research and conclusions in the world of computing efficiency. Please observe the Slashdot interview guidelines: ask as many questions as you want, but please keep them to one per comment.
What is your take on the interpretation of Futurists -- like Raymond Kurzweil -- in regards to extrapolating these 'laws' out to extreme distances?
My work here is dung.
Find an arbitrary pattern or trend, then name it after yourself.
Have gnu, will travel.
This one doesn't seem to have fundamental physical limits, so long as we eventually transition to reversible computing, in which the computer does not use up useful energy because every process it uses is fully reversible (i.e. the original state could be inferred).
All the limits on computation (except regarding storage) that you hear about (e.g. Landauer limit) are on irreversible computing, which is how current architecture works. It is the irreversibility of an operation that causes it to increase entropy.
Information theory is life. The rest is just the KL divergence.
A lot of consumer grade machines have begun focusing on multicore chips with a lower frequency to provide the same or better perceived computing performance than a high frequency single core chip. What happens when a technology like this subverts our craving for higher transistor density? Can you argue that your "law" is immune to researchers focusing on some hot new technology like a thousand core processor or a beefed up system on a chip in order to improve end user experience over pure algorithm crunching speed?
My work here is dung.
When we eventually hit the physical limits of atoms, will programmers eventually stop their autistic quest for more and more layers, more and more complexity and more and more languages to move a number from one address to another?
I would like to see not only the Babbage engine on your curve, but also the abacus and slide rule. Maybe the physical Rod, too, which used to be used in surveying. (Hey, you try calculating property area using pencil, paper, and a deed.)
I will create a sig when innovation restarts in the U.S.
How can anyone take these "laws" seriously anymore in the era of Cloud computing?
How well does Koomey's Law fit other kinds of computing? For instance, has the energy efficiency of cell phone microprocessors followed the same trend as desktop computers and servers? What about embedded systems like routers and car engine controllers, or specialized hardware like game consoles?
OK J.K here is the list of moral / ethical arguments about the path we're on, as seen in your law. You saw the path clearly enough to define a time based law. Are there any issues I'm not seeing on our current path?
1) Lower energy consumption at point of use
2) Higher energy consumption at manufacturing point
3) faster cpu = bigger programs = more bugs = lower quality of life
4) faster cpu = stronger DRM possibilities
5) Better processing * battery life = better medical devices
6) Better processing * battery life = better 1984 style totalitarian devices
7) Lower energy consumption = less air conditioning demand = decreasing average lattitude of data centers = population shifts or whatever or something?
8) More money required for both hw and sw development = good for big corps and bad for the little guy
"Science flies us to the moon. Religion flies us into buildings." - Victor Stenger
Hey J.K. have you run into a law relating battery capacity (either per Kg or L) vs proc speed over time? I bet there is some kind of interesting curve for mobile devices. Or, maybe not, donno thats why I'm asking a guy with previous success at data analysis in a closely related field...
"Science flies us to the moon. Religion flies us into buildings." - Victor Stenger
I have one:
Gates' Law: "The bloatedness of software keeps pace exactly with the increase in power of hardware, to ensure that no actual improvements occur in the end user experience."
This law originally having been proposed by Niklaus Wirth.
What do you think about the following observation: that every X years the amount of computing operations we use to perform basic calculations doubles (by virtue of doing those calculations with more complex software, slower languages...), so when you factor in Moore's law (and your own), the amount of useful calculations we do with computers remain more or less constant.
While sarcastic your question is an important one: as computing power has increased, the tendency of coders to just ride over badly coded underlayers rather than redesign them competently and efficiently has increased. Why bother cutting out bloat that causes an 80% penalty on system efficiency when you can just use a more efficient chipset to get the same result?
So my question is whether Koomey has put any thought into similarly quantifying the opposing software bloat factor, and what he sees the total balance of system works out to.
Someone had to do it.
Originally posted last week, re-worded and re-posted this week. Can we stop promoting re-posts?
Mr. Koomey, if we take your numbers from the attached article, which may not have been quoted correctly...
Feynman indicated that there was approximately 100 billion times efficiency improvement possible, and 40,000 times improvement has happened so far.
If we take Feynman's number at face value, this means that if computing efficiency improvements continue at the current rate (doubling every 18 months,) we will reach the theoretical maximum in 2043.
Based on that, do you believe that we will see a dramatic reduction in efficiency improvements in the next 10-20 years as we approach the theoretical limit, or do you think Feynman was conservative in his estimate?
Thanks!
There are limits to the management of heat output of microprocessors, so the efficiency scaling is always bound to follow the transistor density.
The Pentium M (which is powering the computer that I`m using to type this) came out eight years ago. Let`s call it 7.5 and make our "Koomey factor" 2^5=32. The ULV chip ran at 1.1GHz and ate 6.4W, and we can add on the power of the 855PM northbridge which would make the total 8.2W. I don`t see any products on the market that are anywhere close to a 32x improvement on performance per watt. Do you?
Holy FUCK! Did I just see a spammer fall for that? I'd have sworn all spammers were using bots by now...
What makes your law a non-trivial extension of moore's law which states that the transister count would double every 18 months due to an increase in density? E&M theory states that if you cut a wire's length in half, it's resistance cuts in half. Granted density in this case is a 2 dimensional expansion and wire resistance is a 1 dimensional formula, but what makes this different from what a freshman in college can infer from an R = (resistivity * length)/cross sectional area?
McKusick's theorum... (famed computer scientist of BSD fame)
"computing power to the fingertip has remained constant for the last few decades and probably will do so for more.
A tongue in cheek comment made in a 1992 lecture that in 1972 hitting a key resulted in a printed character echo with about 50 machine instructions where in 1992 it took many tens of thousands (with rendering etc).. now 2 decades further on, we can see that it has grown to tens of millions yet the result is still just a very pretty character echoed to the user.