Move Over Moore's Law, Make Way For Huang's Law (ieee.org)
Tekla Perry writes: Are graphics processors a law unto themselves? Nvidia's Jensen Huang says a 25-times speedup over five years is evidence that they are. He calls this the 'supercharged law,' and says it's time to start counting advances on multiple fronts, including architecture, interconnects, memory technology, and algorithms, not just circuits on a chip.
I didn't realize Moore's Law was about circuits on a chip. Can you please explain? I didn't read the article but they must be talking about "AI" processing.
Observe some trend and name it
Bitcoin's Law. It's all about hashes per second and still a pointless metric!
Anons need not reply. Questions end with a question mark.
I think the attractive aspect of Moore's law was that it was simple and everyone got the general gist. Some people like to argue about the details but they mostly don't have anything else to do with their time.
I don't think we need a Huang's law. If you asks what Huang's Law is, everyone will just say it's like Moore's law except applied to GPU's.
Same applies to all those other people who want to name things after themselves.
>> t's time to start counting advances on multiple fronts
Hobbiests have for a while, ever since last-generation AMD stumbled and Intel slowed down the processor speed increases for a while. Now that Ryzen is out, graphics chips are ruling desktops, and no one cares about Intel in the mobile space, we're finally seeing progress get back toward Moore's Law's long-term trend line.
I thought Moore's comments had to do with the impact of transistor counts on cost. Huang seems to be talking about increased performance without reference to cost. I'm not a gamer, but isn't there a lot of squawking about GPU costs? I wasn't at the talk, so maybe Huang addressed that as well. [Maybe he also assumed people would do the cost vs performance calculation in their heads.]
Moore's Law exclusively talked about transistor count. Speed aside:
GTX 770 in 2013 : 3.5bn transistors.
GTX 1070 in 2017: 7.2bn transistors
Moore's law is dead, but not because you defeated it, but because you failed to live up to it just like the CPU vendors did.
We have been counting advances on multiple fronts since the Intel Core architecture debuted 12 years ago, but welcome to the 21st century Jensen Huang.
Let's not call any and all predictions laws. They're not laws. They are functions fit on a short stretch of data that have no predictive power in the future. Not even experts can predict the future, a "law" has no chance here.
Sounds like wang.
Shouldn't we be calling them BPU's now?
"A person is smart. People are dumb, panicky dangerous animals and you know it." - K
Moore's law is really a statement about economics.
More or less fixed buying power.
More transistors you can fit into a widget the better and more powerful it can be.
More transistors produced the more costs are reduced via investments in production and economies of scale.
In effect a feedback loop between the two ideas.
GTX 580's run about $100 .. DGX-2's are in hundreds of thousands of dollar range. Any comparison in this regard is laughable.
Over the last year due to crypto mining cost of GPUs has doubled which effectively reduced the capabilities customers could afford. You could argue Moore's law effectively running backwards for GPUs if you were only focused on comparing two things rather than more general trend lines.
Micro events are really random one-off things which imply very little about the future. Yesterday it took 3 days to encode a 4k HEVC video. Now it takes 18 minutes because we implemented an ASIC. Does this mean tomorrow I'll be able to do the same in 18 seconds? Doubtful.
Yesterday some AI machination took a year to train, today some bizbang 4-bit massive PIM scheme did the same thing in 18 minutes.
There are no trends associated with tweaking hardware to address specific workloads. You do it once... get a massive jump then you get to wait in line for process improvements to come online like everyone else. Architectural changes generally yield diminishing returns.
The new law is a 5% downward adjustment on the Moore's law as it calls for an increase to 190% instead of 200% in a year. What's the fuss about?
1.9 ** 5 = 25
2.0 ** 5 = 32
So Quantum computers are roughly following Moore's Law in their power. Are we going to rename that to the Q's Law.?
The word "law" in this context is taken from science to describe an effect that always holds true. After watching Moore's Law break down, could we please name this new related observation for graphics cards something more accurate and realistic? How about Huang's Principle or Huang's Observation?
Lots of good names...
Huang's Stolen IP
Huang's Falsified Credentials
Huang's Bogus Data & Fake Research
Huang's Tiananmen Square Tank Man
Huang's Spies For China
While Moore's Law is a doubling in density every 18 months, this 25 times speedup in 5 years is achieved via a doubling every 13 months.
I have to say Supercharged Law is a ridiculous name.
The cost of the fab plants has also been growing exponentially. It hasn't been doubling every 18 months and we (consumers) haven't noticed because the cost of the fabs has been spread out over more chips being made. Unfortunately more and more manufacturers are now fabless. Meaning the actual manufacturing is more concentrated. However the bigger thing we should worry about is the end of exponential grow of chip demand. When that happens it won't just be an engineering problem to pack more transistors in but to do so economically. That will be the end of Moore's Law (prediction). I don't see that bloat of software ending anytime soon.
Everybody have fun tonite!
Except Intel.
The DGX-2 which is 500x faster than 2 GTX 580s is also 500 times more expensive!
https://www.nextplatform.com/2...
AmiMoJo forgot his password again.
Confucius say, "Find worm in apple - bad. Find half a worm - worse."
You are talking out of your ass on that point. Moore's Law had enormous predictive power for roughly 40 years. Furthermore the fundamental basis of this observation was very well understood: When you shrink IC feature size by half, overall circuit size reduces by 4X, due to the fact that IC designs are 2 dimensional.