7 ms·

Transistors Will Stop Shrinking in 2021, Moore’s Law Roadmap Predicts

77 points by dbcooper 10y ago

heisenbit 10y ago
This is 5 years from now that transistors won't shrink anymore. Computers stopped a while ago having higher clock speeds. More integration, wider data paths compensated to some degree. The discussed alternatives like vertical sound in my ears fairly exotic for an industry that has been shrinking, shrinking and shrinking the nodes as the main mode of technical progress. The potential impact is game-changing. I really wonder how this is going to shape where investments in IT go.
- pjmlp 10y ago
  The problem is that the gap between what the hardware guys are able to offer and what software can explorer is getting bigger and bigger. Hence why the explosion in IoT nowadays, that is nothing new. Everyone with some EE background has been playing with microcontrolers since the early 2000. However we have reached a point where to make such tiny computers, more powerful than any of my PCs at the university, is ridiculously cheap. A computer like the Arduino used to cost more than 100 euros back in the day, now I can buy one for 5 euros and who cares if it burns. On the other side of the spectrum we have CPUs like the Nvidia Titan X, which 99% of the computing population can barely make it get out of idle state. So unless one is an heavy gamer, doing Fintech, VR or AI research there is hardly anything new processors can offer over the existing computing workloads. So I guess it isn't stop shrinking as such, but also if it will still be economically viable to continue that route until a new computing paradigm emerges (e.g. Quantum or whatever)
- userbinator 10y ago
  I really wonder how this is going to shape where investments in IT go. Hopefully we'll start to see even more emphasis on optimisation, possibly revived interest in Asm while compilers catch up... and then realise just how efficient software can really be.
  - mtrn 10y ago
    I really hope for that. Working with Unix tools a lot, I appreciate these programs, that were already useful over thirty years ago. The developer mindset needs to change as well. I seldom here people wondering about the sheer computing power of the systems they use. Many developers also seem to get a kick out of building complex systems (with (most of the time too) many abstraction layers burning cpu cycles) - because they seem to believe building complex things somehow means having control over complexity - but I'm not sure about that.
  - ant6n 10y ago
    Or C++N, which gives you abstractions for not very expensive. I wish we had a better, higher level, cross-platform access to SIMD.
    - maga 10y ago
      Your wish will soon be granted: SIMD is a stage 3 proposal for JavaScript, already implemented in nightly versions of FF and Edge, coming to Chrome as well. https://developer.mozilla.org/en-US/docs/Web/JavaScript/Reference/Global_Objects/SIMD https://developer.mozilla.org/en-US/docs/Web/JavaScript/Refe...
Rexxar 10y ago
Does anybody know why the 2015 prevision go faster to 10nm than the 2013 one ? They take some delay at 14/16 nm but they want to keep the 10nm target for 2021 ?
ghshephard 10y ago
Note that they bury an important concept deeper in the article: The new report embraces these trends, predicting an end to traditional scaling—the shrinking of chip features—by the early 2020’s. But the idea that we’re now facing an end to Moore’s Law “is completely wrong,” Gargini says. ... If a company really wanted to, Gargini says, it could continue to make transistors smaller well into the 2020s, “but it’s more economic to go 3-D. That’s the message we wanted to send.”
- tim333 10y ago
  Moore's law has always been down to economics - it was worth the industry's investment to develop more transistors per chip area for the next year. If that stops then it stops. Computers will keep getting faster and more powerful though by whatever means makes economic sense.
  - ghshephard 10y ago
    Right - but the subtle, and easy to miss message here, isn't that its not longer possible, or even economical to continue to increase density of transistors absent other opportunities, but that with the advent of 3D technologies, increasing the number of transistors per chip can be done more efficiently using 3D approaches. It may be, that once that approach has run it's course, the industry switches back to increasing density again.
    - ci5er 10y ago
      Ultimately you hit a 2D density wall. I'd imagine it's harder to get more dense than one bit per several atoms. A silicon atom itself is 0.2nm, so ... not that far off of where we already are. That pretty much maxes out the thin-film 2D approach, and to pack in more, we'll need to go vertical. And to do that, we'll need to create novel fabrication technologies (unless they come up with some photo-lithography magic that I can't imagine right now), and, problematically, they'll need to deal with heat. This is not to say that I am disagreeing with you on the switch-back-to-2d front, but I don't think we have much further to go on the 2d-density front.
proc0 10y ago
Dat paradigm shift tho.
azeirah 10y ago
As a computer engineering student, I don't understand how adding more transistors to a cpu makes it faster, gpu's, sure. If I wire an 8-bit adder circuit, adding more transistors will definitely not make it process those bits faster.
- farresito 10y ago
  More instructions, bigger caches, longer pipelines...
- deleted 10y ago
  [deleted]
- Kenji 10y ago
  There are many ways to create adders [0]. And other circuits for that matter. If you are willing to expend more transistors, you can decrease the propagation delay [1], that is, the delay until all outputs have settled to a stable value. Basically the propagation delay is the "longest path" from any input to any output and is a constraint on how fast the clock can go without messing up the calculations. Other ways to make a CPU faster, which costs transistors, is improved branch prediction and parallelism (modern CPUs execute a lot in parallel, even single cores. If there is a conditional branch and it guessed wrong, it has to flush all the wrong stuff it calculated. But there are still speed gains if the branch prediction is okay.) [0] https://en.wikipedia.org/wiki/Adder_(electronics) https://en.wikipedia.org/wiki/Adder_(electronics) [1] https://en.wikipedia.org/wiki/Propagation_delay https://en.wikipedia.org/wiki/Propagation_delay
- markus2012 10y ago
  Your 8-bit adder will have to wait ~225 CLKs (possibly x 2) to get the data it needs to add. Add a ton of transistors to intelligently prefetch and cache will in some cases decrease those 225 CLKs. A great deal of transistors are added to cache and cache intelligence to get around the terrible latency of DRAM.
- pharrington 10y ago
  If you had more transistors, you could make a 16-bit adder circuit! The difficulty is in getting all the features you want within the space provided while adhering to the laws of physics.
Nokinside 10y ago
Moore's law was the result of constant development in the lowest level of integrated circuits - lithography and chemistry. Moore's law made most higher level hardware architecture innovation almost meaningless. Developing new kinds of parallel computers (Gray, Thinking Machines) was dead end when conventional computers made from Intel chips reached the same level in few years without specialized software. Things have already changed. First specialized Graphics processors and now GPGPU are the first break from the normal. GPGPU's technology is one level up from lithography and silicon chemistry. It's different architecture and different programming paradigm. This will be the first time Intel is not going to shake it off with faster GPU. We should expect more higher level hardware innovations. Integrating GPU functions into DRAM chips might be the next step.
- rasz_pl 10y ago
  Micron had ram integrated state machine for some time now, nothing came out of that :( http://www.micronautomata.com/ http://www.micronautomata.com/ They might be missing the boat by not releasing cheap entry level hardware platform, ~$20 ddr3/4 stick.
  - agumonkey 10y ago
    Considering how often the RAM bottleneck was mentioned in computer performances talks I'm still surprised simple logic / arith instructions didn't hit mainstream RAM modules.
    - lomnakkus 10y ago
      I'm obviously just speculating and handwaving wildly here[1], but ISTM that -- currently -- the limitation here lies mainly in programming languages and semantics. AFAICT all of the non-traditional machine models require radically different programming paradigms[2] and we still aren't quite at that point where gaining more performance is painful enough that the necessary research/innovation will happen. That's assuming that it's even possible. Obviously, any model of computation places some limitations on what can happen and all information transfer (thus computation) is still limited by the speed of light. Some things are just going to remain out of reach forever and not even Quantum Computers are going to help. [1] As I suppose we all are. C'mon we're talking about predicting the future here. [2] If you want a practical example, look at the PS/3 Cell processor. I can't claim to have done any 'native' programming for the PS/3, but I've heard (from very clever people that I trust) that it was quite alien and required radically different program structure from what one is used to. And that architecture isn't even that different from 'normal' architectures.
LittleSpider 10y ago
It seems in the article there is a discussion that uses two different definitions for Moore's Law - number of transistors per "space" (and by proxy, size of each transistor) and overall computing power per "space." When Mr. Moore put his law out there 50+ years ago, perhaps the concept of number/size of transistors was effectively a proxy for computing power, or perhaps even more true, no one saw a difference, or cared to see a difference between the two. Since Mr. Moore is still around, I would love to have his feedback about this- I guess, like Woody Allen's character pulling in Marshall McLuhan in Annie Hall. Enough of the aside, though: since 1965, much has been learned on the hardware and software sides, industries have grown and shrunk, and we are now able to have debates that - at least somewhat - bifurcate the issue of size/density of hardware from the issue of the somewhat more intangible computing power.
- Zardoz84 10y ago
  Moore was talking explicit about transistors, not computing power.
  - LittleSpider 10y ago
    Agreed that he said that in his 1965 paper; research indicates he was asked what would happen in the semiconductor industry (which I see as "the hardware side." He was Director of R&D at Fairchild at the time). Per several areas I have read, it was after Mr. Moore reviewed his thoughts in 1975 that David House made reference to an 18-month doubling of performance of circuits. This leads to my question about proxy regarding what the thoughts were (or weren't) 10+ years earlier. Was there any awareness, in 1965, of a difference between transistor count and operating performance, or did this awareness come about later on as industries matured? I tend to think that without any history to define a difference, they would have been viewed as one and the same in 1965. I theorize that at that time Mr. Moore - as a young, 35-36 year old, Director of semiconductor R&D and quite intelligent, undoubtedly - focused on the question as solely about circuits, and not necessarily taking a wider view in his article about overall performance (however performance would have been defined at the time, if it was considered as anything different from transistor size/count/density) when he was asked to write an article about future projections in the semiconductor industry.
pier25 10y ago
How long until quantum computing will be available in consumer equipment?
- sandworm101 10y ago
  You will have to redefine what "consumer equipment" means. I don't see in-home cyro-chilled machines being a thing anytime soon. But perhaps such things will be available at co-location facilities and easily accessed by conventional home machines.
  - pier25 10y ago
    I meant laptops, mobile devices, etc. Sure, these things are huge today, but we have now in our pockets more power than was available in a Cray super computer from the 80s.
    - sandworm101 10y ago
      Quantum computing isn't just a faster tech. It's a very different means of answering very specific questions. I cannot see how it would ever be useful for something like a GPU running a game, or a CPU running a macro on a large spreadsheet file. I could see a use for a quantum computing module attached to a computer much like a graphics card, but I cannot see how a quantum processor would do the role of a CPU. Given that, I don't see a market for it in everyday computing.
      - pier25 10y ago
        Could you expand on that? Is it a matter of efficiency like running graphics calculations on a CPU?
kylehotchkiss 10y ago
What in consumer computing needs too much more power than we have now? It seems like the next steps are really battery life and covering more of the plantet with reliable, fast internet service.
- hughperkins 10y ago
  machine learning

77 points by dbcooper 10y ago

This is 5 years from now that transistors won't shrink anymore. Computers stopped a while ago having higher clock speeds. More integration, wider data paths compensated to some degree. The discussed alternatives like vertical sound in my ears fairly exotic for an industry that has been shrinking, shrinking and shrinking the nodes as the main mode of technical progress. The potential impact is game-changing. I really wonder how this is going to shape where investments in IT go.

pjmlp 10y ago
The problem is that the gap between what the hardware guys are able to offer and what software can explorer is getting bigger and bigger. Hence why the explosion in IoT nowadays, that is nothing new. Everyone with some EE background has been playing with microcontrolers since the early 2000. However we have reached a point where to make such tiny computers, more powerful than any of my PCs at the university, is ridiculously cheap. A computer like the Arduino used to cost more than 100 euros back in the day, now I can buy one for 5 euros and who cares if it burns. On the other side of the spectrum we have CPUs like the Nvidia Titan X, which 99% of the computing population can barely make it get out of idle state. So unless one is an heavy gamer, doing Fintech, VR or AI research there is hardly anything new processors can offer over the existing computing workloads. So I guess it isn't stop shrinking as such, but also if it will still be economically viable to continue that route until a new computing paradigm emerges (e.g. Quantum or whatever)
userbinator 10y ago
I really wonder how this is going to shape where investments in IT go. Hopefully we'll start to see even more emphasis on optimisation, possibly revived interest in Asm while compilers catch up... and then realise just how efficient software can really be.
- mtrn 10y ago
  I really hope for that. Working with Unix tools a lot, I appreciate these programs, that were already useful over thirty years ago. The developer mindset needs to change as well. I seldom here people wondering about the sheer computing power of the systems they use. Many developers also seem to get a kick out of building complex systems (with (most of the time too) many abstraction layers burning cpu cycles) - because they seem to believe building complex things somehow means having control over complexity - but I'm not sure about that.
- ant6n 10y ago
  Or C++N, which gives you abstractions for not very expensive. I wish we had a better, higher level, cross-platform access to SIMD.
  - maga 10y ago
    Your wish will soon be granted: SIMD is a stage 3 proposal for JavaScript, already implemented in nightly versions of FF and Edge, coming to Chrome as well. https://developer.mozilla.org/en-US/docs/Web/JavaScript/Reference/Global_Objects/SIMD https://developer.mozilla.org/en-US/docs/Web/JavaScript/Refe...

Rexxar 10y ago

Does anybody know why the 2015 prevision go faster to 10nm than the 2013 one ? They take some delay at 14/16 nm but they want to keep the 10nm target for 2021 ?

ghshephard 10y ago

Note that they bury an important concept deeper in the article: The new report embraces these trends, predicting an end to traditional scaling—the shrinking of chip features—by the early 2020’s. But the idea that we’re now facing an end to Moore’s Law “is completely wrong,” Gargini says. ... If a company really wanted to, Gargini says, it could continue to make transistors smaller well into the 2020s, “but it’s more economic to go 3-D. That’s the message we wanted to send.”

tim333 10y ago
Moore's law has always been down to economics - it was worth the industry's investment to develop more transistors per chip area for the next year. If that stops then it stops. Computers will keep getting faster and more powerful though by whatever means makes economic sense.
- ghshephard 10y ago
  Right - but the subtle, and easy to miss message here, isn't that its not longer possible, or even economical to continue to increase density of transistors absent other opportunities, but that with the advent of 3D technologies, increasing the number of transistors per chip can be done more efficiently using 3D approaches. It may be, that once that approach has run it's course, the industry switches back to increasing density again.
  - ci5er 10y ago
    Ultimately you hit a 2D density wall. I'd imagine it's harder to get more dense than one bit per several atoms. A silicon atom itself is 0.2nm, so ... not that far off of where we already are. That pretty much maxes out the thin-film 2D approach, and to pack in more, we'll need to go vertical. And to do that, we'll need to create novel fabrication technologies (unless they come up with some photo-lithography magic that I can't imagine right now), and, problematically, they'll need to deal with heat. This is not to say that I am disagreeing with you on the switch-back-to-2d front, but I don't think we have much further to go on the 2d-density front.

proc0 10y ago

Dat paradigm shift tho.

azeirah 10y ago

As a computer engineering student, I don't understand how adding more transistors to a cpu makes it faster, gpu's, sure. If I wire an 8-bit adder circuit, adding more transistors will definitely not make it process those bits faster.

farresito 10y ago
More instructions, bigger caches, longer pipelines...
deleted 10y ago
[deleted]
Kenji 10y ago
There are many ways to create adders [0]. And other circuits for that matter. If you are willing to expend more transistors, you can decrease the propagation delay [1], that is, the delay until all outputs have settled to a stable value. Basically the propagation delay is the "longest path" from any input to any output and is a constraint on how fast the clock can go without messing up the calculations. Other ways to make a CPU faster, which costs transistors, is improved branch prediction and parallelism (modern CPUs execute a lot in parallel, even single cores. If there is a conditional branch and it guessed wrong, it has to flush all the wrong stuff it calculated. But there are still speed gains if the branch prediction is okay.) [0] https://en.wikipedia.org/wiki/Adder_(electronics) https://en.wikipedia.org/wiki/Adder_(electronics) [1] https://en.wikipedia.org/wiki/Propagation_delay https://en.wikipedia.org/wiki/Propagation_delay
markus2012 10y ago
Your 8-bit adder will have to wait ~225 CLKs (possibly x 2) to get the data it needs to add. Add a ton of transistors to intelligently prefetch and cache will in some cases decrease those 225 CLKs. A great deal of transistors are added to cache and cache intelligence to get around the terrible latency of DRAM.
pharrington 10y ago
If you had more transistors, you could make a 16-bit adder circuit! The difficulty is in getting all the features you want within the space provided while adhering to the laws of physics.

Nokinside 10y ago

Moore's law was the result of constant development in the lowest level of integrated circuits - lithography and chemistry. Moore's law made most higher level hardware architecture innovation almost meaningless. Developing new kinds of parallel computers (Gray, Thinking Machines) was dead end when conventional computers made from Intel chips reached the same level in few years without specialized software. Things have already changed. First specialized Graphics processors and now GPGPU are the first break from the normal. GPGPU's technology is one level up from lithography and silicon chemistry. It's different architecture and different programming paradigm. This will be the first time Intel is not going to shake it off with faster GPU. We should expect more higher level hardware innovations. Integrating GPU functions into DRAM chips might be the next step.

rasz_pl 10y ago
Micron had ram integrated state machine for some time now, nothing came out of that :( http://www.micronautomata.com/ http://www.micronautomata.com/ They might be missing the boat by not releasing cheap entry level hardware platform, ~$20 ddr3/4 stick.
- agumonkey 10y ago
  Considering how often the RAM bottleneck was mentioned in computer performances talks I'm still surprised simple logic / arith instructions didn't hit mainstream RAM modules.
  - lomnakkus 10y ago
    I'm obviously just speculating and handwaving wildly here[1], but ISTM that -- currently -- the limitation here lies mainly in programming languages and semantics. AFAICT all of the non-traditional machine models require radically different programming paradigms[2] and we still aren't quite at that point where gaining more performance is painful enough that the necessary research/innovation will happen. That's assuming that it's even possible. Obviously, any model of computation places some limitations on what can happen and all information transfer (thus computation) is still limited by the speed of light. Some things are just going to remain out of reach forever and not even Quantum Computers are going to help. [1] As I suppose we all are. C'mon we're talking about predicting the future here. [2] If you want a practical example, look at the PS/3 Cell processor. I can't claim to have done any 'native' programming for the PS/3, but I've heard (from very clever people that I trust) that it was quite alien and required radically different program structure from what one is used to. And that architecture isn't even that different from 'normal' architectures.

LittleSpider 10y ago

It seems in the article there is a discussion that uses two different definitions for Moore's Law - number of transistors per "space" (and by proxy, size of each transistor) and overall computing power per "space." When Mr. Moore put his law out there 50+ years ago, perhaps the concept of number/size of transistors was effectively a proxy for computing power, or perhaps even more true, no one saw a difference, or cared to see a difference between the two. Since Mr. Moore is still around, I would love to have his feedback about this- I guess, like Woody Allen's character pulling in Marshall McLuhan in Annie Hall. Enough of the aside, though: since 1965, much has been learned on the hardware and software sides, industries have grown and shrunk, and we are now able to have debates that - at least somewhat - bifurcate the issue of size/density of hardware from the issue of the somewhat more intangible computing power.

Zardoz84 10y ago
Moore was talking explicit about transistors, not computing power.
- LittleSpider 10y ago
  Agreed that he said that in his 1965 paper; research indicates he was asked what would happen in the semiconductor industry (which I see as "the hardware side." He was Director of R&D at Fairchild at the time). Per several areas I have read, it was after Mr. Moore reviewed his thoughts in 1975 that David House made reference to an 18-month doubling of performance of circuits. This leads to my question about proxy regarding what the thoughts were (or weren't) 10+ years earlier. Was there any awareness, in 1965, of a difference between transistor count and operating performance, or did this awareness come about later on as industries matured? I tend to think that without any history to define a difference, they would have been viewed as one and the same in 1965. I theorize that at that time Mr. Moore - as a young, 35-36 year old, Director of semiconductor R&D and quite intelligent, undoubtedly - focused on the question as solely about circuits, and not necessarily taking a wider view in his article about overall performance (however performance would have been defined at the time, if it was considered as anything different from transistor size/count/density) when he was asked to write an article about future projections in the semiconductor industry.

pier25 10y ago

How long until quantum computing will be available in consumer equipment?

sandworm101 10y ago
You will have to redefine what "consumer equipment" means. I don't see in-home cyro-chilled machines being a thing anytime soon. But perhaps such things will be available at co-location facilities and easily accessed by conventional home machines.
- pier25 10y ago
  I meant laptops, mobile devices, etc. Sure, these things are huge today, but we have now in our pockets more power than was available in a Cray super computer from the 80s.
  - sandworm101 10y ago
    Quantum computing isn't just a faster tech. It's a very different means of answering very specific questions. I cannot see how it would ever be useful for something like a GPU running a game, or a CPU running a macro on a large spreadsheet file. I could see a use for a quantum computing module attached to a computer much like a graphics card, but I cannot see how a quantum processor would do the role of a CPU. Given that, I don't see a market for it in everyday computing.
    - pier25 10y ago
      Could you expand on that? Is it a matter of efficiency like running graphics calculations on a CPU?

kylehotchkiss 10y ago

What in consumer computing needs too much more power than we have now? It seems like the next steps are really battery life and covering more of the plantet with reliable, fast internet service.

hughperkins 10y ago
machine learning