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Warning At SC13 That Supercomputing Will Plateau Without a Disruptive Technology

Posted by Unknown on from the series-of-nanotubes dept.

dcblogs writes "At this year's supercomputing conference, SC13, there is worry that supercomputing faces a performance plateau unless a disruptive processing tech emerges. 'We have reached the end of the technological era' of CMOS, said William Gropp, chairman of the SC13 conference and a computer science professor at the University of Illinois at Urbana-Champaign. Gropp likened the supercomputer development terrain today to the advent of CMOS, the foundation of today's standard semiconductor technology. The arrival of CMOS was disruptive, but it fostered an expansive age of computing. The problem is 'we don't have a technology that is ready to be adopted as a replacement for CMOS,' said Gropp. 'We don't have anything at the level of maturity that allows you to bet your company on.' Peter Beckman, a top computer scientist at the Department of Energy's Argonne National Laboratory, and head of an international exascale software effort, said large supercomputer system prices have topped off at about $100 million 'so performance gains are not going to come from getting more expensive machines, because these are already incredibly expensive and powerful. So unless the technology really has some breakthroughs, we are imagining a slowing down.'" Although carbon nanotube based processors are showing promise (Stanford project page; the group is at SC13 giving a talk about their MIPS CNT processor).

17 of 118 comments (clear)

  1. MIPS CNT... by motd2k · · Score: 5, Funny

    MIPS CNT... how do you pronounce that?

  2. Does disruptive mean affordable? by UnknownSoldier · · Score: 4, Interesting

    We've had Silicon Germanium cpus that can scale to 1000+ GHz for years. Graphene is also another interesting possibility.

    The question is that "At what price can you make the power affordable?"

    For 99% of people, computers are good enough. For the other 1% they never will be.

    1. Re:Does disruptive mean affordable? by fuzzyfuzzyfungus · · Score: 4, Informative

      Even if you are willing to burn nigh unlimited power, thermals can still be a problem (barring some genuinely exotic approaches to cooling), because ye olde speed of light says that density is the only way to beat latency. There are, of course, ways to suck at latency even more than the speed of light demands; but there are no ways to suck less.

      If your problem is absolutely beautifully parallel (and, while we're dreaming, doesn't even cache-miss very often), horrible thermals would be a problem that could be solved by money: build a bigger datacenter and buy more power. If there's a lot of chatter between CPUs, or between CPUs and RAM, distance starts to hurt. If memory serves, 850nm light over 62.5 micrometer fiber is almost 5 nanoseconds/meter. That won't hurt your BattleField4 multiplayer performance; but when even a cheap, nasty, consumer grade CPU is 3GHz, there go 15 clocks for every meter, even assuming everything else is perfect. Copper is worse, some fiber might be better.

      Obviously, problems that can be solved by money are still problems, so they are a concern; but problems that physics tells us are insoluble are even less fun.

  3. on the nature of disruptive... by schlachter · · Score: 4, Insightful

    my intuition tells me that disruptive technologies are precisely that because people don't anticipate them coming along nor do they anticipate the changes that will follow their introduction. not that people can't see disruptive tech ramping up, but often they don't.

    --
    My God can beat up your God. Just kidding...don't take offense. I know there's no God.
    1. Re:on the nature of disruptive... by fuzzyfuzzyfungus · · Score: 4, Interesting

      my intuition tells me that disruptive technologies are precisely that because people don't anticipate them coming along nor do they anticipate the changes that will follow their introduction. not that people can't see disruptive tech ramping up, but often they don't.

      Arguably, there are at least two senses of 'disruptive' at play when people talk about 'disruptive technology'.

      There's the business sense, where a technology is 'disruptive' because it turns a (usually pre-existing, even considered banal or cheap and inferior) technology into a viable, then superior, competitor to a nicer but far more expensive product put out by the fat, lazy, incumbent. This comment, and probably yours, was typed on one of those(or, really, a collection of those.)

      Then there's the engineering/applied science sense, where it is quite clear to everybody that "If we could only fabricate silicon photonics/achieve stable entanglement of N QBits/grow a single-walled carbon nanotube as long as we want/synthesize a non-precious-metal substitute for platinum catalysts/whatever, we could change the world!"; but nobody knows how to do that yet.

      Unlike the business case (where the implications of 'surprisingly adequate computers get unbelievably fucking crazy cheap' were largely unexplored, and before that happened people would have looked at you like you were nuts if you told them that, in the year 2013, we have no space colonies, people still live in mud huts and fight bush wars with slightly-post-WWII small arms; but people who have inadequate food and no electricity have cell phones), the technology case is generally fairly well planned out (practically every vendor in the silicon compute or interconnect space has a plan for, say, what the silicon-photonics-interconnect architecture of the future would look like; but no silicon photonics interconnects, and we have no quantum computers of useful size; but computer scientists have already studied the algorithms that we might run on them, if we had them); but application awaits some breakthrough in the lab that hasn't come yet.

      (Optical fiber is probably a decent example of a tech/engineering 'disruptive technology' that has already happened. Microwave waveguides, because those can be tacked together with sheet metal and a bit of effort, were old news, and the logic and desireability of applying the same approach to smaller wavelengths was clear; but until somebody hit on a way to make cheap, high-purity, glass fiber, that was irrelevant. Once they did, the microwave-based infrastructure fell apart pretty quickly; but until they did, no amount of knowing that 'if we had optical fiber, we could shove 1000 links into that one damn waveguide!' made much difference.)

  4. SOLUTION for CMOS "band gap" by kdawson+(3715) · · Score: 3, Interesting

    I suggest we go back a few levels and back to the 1970's when TTL was being replaced because of it's higher voltages. Remember back when core memory was replaced but before CMOSS? These were the TTL eras made by similar but NOT THE SAME transistors.

    1. Silicone bandgap of CMOSS is higher than TTL
    2. Gate length is more fabricable. (Fabricate the gates in Mexico; say they were made in USA)
    3. Drain has "quantum clogging" problems in TTL but not CMOSS
    4. Dopant levels make GaAs less commercially feasible.
    5. Wafer sizes still dominated by "silicon" technology. It is not cheaper to go to more e-toxic and alien technologies. Far cheaper to stick with the wafers commercially produced today. GaAs and Indium Phosphate are like communion wafers!!!
    6. Investors. We need to keep money at the fore front. Global depression is iminint. Must make cheep and available components with "WHAT WE HAVE" allready!!

    TTL. I think its a good idea.

    -KD

  5. Re:Work smarter, not harder. by mlts · · Score: 3, Interesting

    I wonder if the next breakthrough would be using FPGAs and configuring the instruction set for the task at hand. For example, a core gets a large AES encryption task, so it gets set to an instruction set optimized for array shifting. Another core gets another job, so shifts to a set optimized for handling trig functions. Still another set deals with large amounts of I/O, so ends up having a lot of registers to help with transforms, and so on.

    Of course, fiber from chip to chip may be the next thing. This isn't new tech (the PPC 603 had this), but it might be what is needed to allow for CPUs to communicate closely coupled, but have signal path lengths be not as big an engineering issue. Similar with the CPU and RAM.

    Then there are other bottlenecks. We have a lot of technologies that are slower than RAM but faster than disk. Those can be used for virtual memory or a cache to speed things up, or at least get data in the pipeline to the HDD so the machine can go onto other tasks, especially if a subsequent read can fetch data no matter where it lies in that I/O pipeline.

    Long term, photonics will be the next breakthrough that propels things forward. That and the Holy Grail of storage -- holographic storage, which promises a lot, but has left many a company (Tamarak, InPhase) on the side of the road, broken and mutilated without mercy.

  6. Re:So what? by Anonymous Coward · · Score: 5, Insightful

    There are actually a half-decent number of 'supercomputers' -depending on how you define that term- in the private sector. From 'simple' ones that do rendering for animation companies to ones that model airflow for vehicles to ones that crunch financial numbers to.. well, lots of things, really. Are they as large as the biggest National faciltiies? Of course not - that's where the next generation of business-focused systems get designed and tested and models and methods get developed and tested.

    It is indeed the case that far simpler systems ran early nuclear weapon design, yes, but that's like saying far simpler desktops had 'car racing games' -- when, in reality, the quality of those applications has changed incredibly. Try playing an old racing game on a C64 vs. a new one now and you'd probably not get that much out of the old one. Try doing useful, region-specific climate models with an old system and you're not going to get much out of it. Put a newer model with much higher resolution, better subgrid models and physics options, and the ability to accurately and quickly do ensemble runs for a sensitivity analysis and, well, you're in much better territory scientifically.

    So, in answer to "So what?", I say: "Without improvements in our tools (supercomputers), our progress in multiple scientific -and business- endeavors slows down. That's a pretty big thing."

  7. Re:So what? by Kjella · · Score: 4, Interesting

    Of course these people are using talking about supercomputers and the relevance to supercomputers, but you have to be pretty daft to not see the implications for everything else. In the last years almost all the improvement have been in power states and frequency/voltage scaling, if you're doing something at 100% CPU load (and isn't a corner case to benefit from a new instruction) the power efficiency has been almost unchanged. Top of the line graphics cards have gone constantly upwards and are pushing 250-300W, even Intel's got Xeons pushing 150W not to mention AMD's 220W beast, though that's a special oddity. The point is that we need more power to do more and for hardware running 24x7 that's a non-trivial part of the cost that's not going down.

    We know CMOS scaling is coming to an end, maybe not at 14nm or 10nm but at the end of this decade we're approaching the size of silicon atoms and lattices. There's no way we can sustain the current rate of scaling in the 2020s. And it wouldn't be the end of the world, computers would go roughly the same speed they did ten or twenty years ago like cars and jet planes do. Your phone would never become as fast as your computer which would never become as fast as a supercomputer again. We could get smarter at using that power of course, but fundamentally hard problems that require a lot of processing power would go nowhere and it won't be terahertz processors, terabytes of RAM and petabytes of storage for the average man. It was a good run while it lasted.

    --
    Live today, because you never know what tomorrow brings
  8. Re:Didn't that boat sail with the Cray Y-MP? by timeOday · · Score: 3, Insightful

    All our really big supercomputers today are adding a bunch of individual not-even-Krypto-the-wonderdog CPUs together, and then calling it a supercomputer. Have we reached the limits in that scaling? No.

    This is wrong on both counts. First, the CPUs built into supercomputers today are as good as anybody knows how to make one. True, they're not exotic, in that you can also buy one yourself for $700 on newegg. But they represent billions of dollars in design and are produced only on multi-billion dollar fabs. There is no respect in which they are not lightyears more advanced than any custom silicon cray ever put out.

    Second, you are wrong that we are not reaching the limits of scaling these types of machines. Performance does not scale infinitely on realistic workloads. And budgets and power supply certainly do not scale infinitely.

  9. Re:Work smarter, not harder. by Jane+Q.+Public · · Score: 3, Interesting

    "Of course, fiber from chip to chip may be the next thing. This isn't new tech (the PPC 603 had this), but it might be what is needed to allow for CPUs to communicate closely coupled, but have signal path lengths be not as big an engineering issue. Similar with the CPU and RAM."

    Fiber from chip to chip is probably a dead end, unless you're just primarily taking advantage of the speed of serial over parallel buses.

    The problem is that you have to convert the light back to electricity anyway. So while fiber is speedier than wires, the delays (and expense) introduced at both ends limits its utility. Unless you go to actual light-based (rather than electrical) processing on the chips, any advantage to be gained there is strictly limited.

    Probably more practical would be to migrate from massively parallel to faster serial communication. Like the difference between old parallel printer cables to USB. Granted, these inter-chip lineswould have to be carefully designed and shielded (high freq.), but so do light fibers.

  10. Re:Didn't that boat sail with the Cray Y-MP? by Anonymous Coward · · Score: 4, Informative

    The problem is that there are many interesting problems which don't parallelize *well*. I epmhasize *well* because many of these problems do parallelize, it's just that the scaling falls off by an amount that matters the more thousands of processors you add. For these sorts of problems (of which there are many important ones), you can take Latest_Processor_X and use it efficiently in a cluster of, say, 1,000 nodes, but probably not 100,000. At some point the latency and communication and whatnot just takes over the equation. Maybe for a given problem of this sort you can solve it 10 days on 10,000 nodes, but the runtime only drops to 8 days on 100,000 nodes. It just doesn't make fiscal sense to scale beyond a certain limit in these cases. For these sorts of problems, single-processor speed still matters, because they can't be infinitely scaled by throwing more processors at the problem, but they can be infinitely scaled (well, within information-theoretic bounds dealing with entropy and heat-density) by faster single CPUs (which are still clustered to the degree it makes sense).

    CMOS basically ran out of real steam on this front several years ago. It's just been taking a while for everyone to soak up the "easy" optimizations that were laying around elsewhere to keep making gains. Now we're really starting to feel the brick wall...

  11. Re:Work smarter, not harder. by symbolset · · Score: 3, Funny

    Assume a spherical data center...

    --
    Help stamp out iliturcy.
  12. A lot of supercomputing motivated by bad science! by Theovon · · Score: 3, Interesting

    There are plenty of algorithms that benefit from supercomputers. But it turns out that a lot of the justification for funding super computer research has been based on bad math. Check out this paper:

    http://www.cs.binghamton.edu/~pmadden/pubs/dispelling-ieeedt-2013.pdf

    It turns out that a lot of money has been spent to fund supercomputing research, but the researchers receiving that money were demonstrating the need for this research based on the wrong algorithms. This paper points out several highly parallelizable O(n-squared) algorithms that researchers have used. It seems that these people lack an understanding of basic computational complexity, because there are O(n log n) approaches to the same problems that can run much more quickly, using a lot less energy, on a single-processor desktop computer. But they’re not sexy because they’re not parallelizable.

    Perhaps some honest mistakes have been made, it trends towards dishonestly as long as these researchers continue to use provably wrong methods.

  13. Re:Complete garbage by The+Master+Control+P · · Score: 4, Informative

    By definition, computers are scalable. Need more performance? Add more processing units/memory.

    BZZZT, WRONG.

    This is where you can stop reading, folks.

  14. Re:So what? by fuzzyfuzzyfungus · · Score: 3, Informative

    They have no choice in the matter, since nobody makes 500GHz CPUs; but there is a reason why (many, not all) 'supercomputers' lay out a considerable amount of their budget for very fast, very low latency, interconnects (myrinet, infiniband, sometimes proprietary fabrics for single-system-image stuff), rather than just going GigE or 10GigE and calling it a day, like your generic datacenter-of-whitebox-1Us does.

    There are problems where chatter between nodes is low, and separate system images are acceptable, and blessed are they, for they shall be cheap; but people don't buy the super fancy interconnects just for the prestige value.

  15. Tianhe-2? by therealobsideus · · Score: 3, Informative

    Totally off topic, but I ended up getting drunk with a bunch of people that are here in town for SC13 last night. Those boys can drink. But I'm surprised that there wasn't more talk about Tianhe-2 there, and how Chinese is going to kick the US off the top 25 in international supercomputing.