7 ms·

Gains in instructions-per-clock start to flatten out. And that's where the gains were coming from in the last years. Some time ago a paper was posted here that

Gains in instructions-per-clock start to flatten out. And that's where the gains were coming from in the last years. Some time ago a paper was posted here that showed how even if you have an infinite amount of transistors, you will still be limited in the range of 3-10 instructions-per-clock for typical programs. Clock speeds seem to have leveled and IPC will only see another gain of 50-100%. Single threaded performance is close to the limit. What after that? Is this the end?

ido 9y ago
When was the last time we saw a 50-100% performance gain in cars? airplanes? spacecraft? Was it the end of those industries? Welcome to mature technology.
- meric 9y ago
  > spacecraft Economically? I think this or last year.
  - kuschku 9y ago
    Economically, SpaceX is about 3% cheaper than Arianespace. That's not a 50% or 100% improvement. Maybe they'll get that improvement once they run recycled rockets all the time, but not before that.
    - mlvljr 9y ago
      Will anyone debunk the above? :)
    - kuschku 9y ago
      @mlvljr: Your account seems to be shadowbanned, I can’t reply to your comment. Currently, SpaceX has prices around 56-62 million USD per launch of a normal satellite (with a weight and orbit where they can recover the first stage). Arianespace launches such lighter satellites in pairs, always two at once, at a price of around 60 million USD per satellite. The Chinese launchers offer the same at around 70 million USD per launch. So, the prices aren’t that different. But, for launches from reused rockets, SpaceX is damn cheap. The first launch on a reused rocket cost below 30 million USD. So, to recap: Today, in best case, SpaceX is between 4 and 13% cheaper than the next competitor. But in a few years, once they launch mostly reused rockets, they’ll be around 50 to 60% cheaper than the next competitor.
      - njarboe 9y ago
        I imagine that, while SpaceX will continue to improve their cost/kg to orbit and reach a launch expense of half the current cost with re-usables pretty quickly, until someone else can compete, they could just increase their profit per launch enormously. Musk needs some serious capital for his Mars plans. I hope his global satellite internet provider concept works (I can't wait to have a option other than AT&T or Comcast) and brings in the big bucks. Then he won't need to make money on launches and can drop the launch price on launches to close to cost to help all space activities. Maybe even start selling re-usable rockets to other launch companies. Can't wait to see that day. Long term, Musk is shooting for a ~100x reduction in launch costs to make a Mars colony feasible. Hope he makes it.
nostrademons 9y ago
GPUs: http://michaelgalloy.com/2013/06/11/cpu-vs-gpu-performance.html http://michaelgalloy.com/2013/06/11/cpu-vs-gpu-performance.h... http://www.anandtech.com/show/7603/mac-pro-review-late-2013/3 http://www.anandtech.com/show/7603/mac-pro-review-late-2013/... This is behind much of the interest in machine learning these days. Deep learning provides a way to approximate any computable function as the composition of matrix operations with non-linearities. It does this at the cost of requiring many, many times the computing power. But much of this computing cost can be parallelized and accelerated effectively on the GPU, so with GPU cores still increasing exponentially, at some point it's likely to become more effective than CPUs.
- dom0 9y ago
  I don't think GPUs are a particularly good solution for these, they aren't the future and won't be around for mass-deployment that much longer.
  - heavenlyblue 9y ago
    It seems the author is down the 'deep learning' rabbit hole. >> It does this at the cost of requiring many, many times the computing power. But much of this computing cost can be parallelized and accelerated effectively on the GPU, so with GPU cores still increasing exponentially, at some point it's likely to become more effective than CPUs. So can be any matrix. Sadly, there aren't as many algorithms that are efficiently represented by one.
  - chillydawg 9y ago
    That's quite a statement - what will replace GPUs for the ever increasing amount of ML work being done?
    - bitL 9y ago
      TPU-like chips; though they can be (partially) included on GPUs as well as is the case with the latest NVidia/AMD GPUs.
rphlx 9y ago
> Gains in instructions-per-clock start to flatten out. And that's where the gains were coming from in the last years. This is commonly claimed but it's actually false for x86_64 desktop parts. For a single core scalar integer workload the IPC boost from i7-2700k to i7-7700k was maybe 20-25% on a great day, but the base frequency increase was a further 20%, and max boost freq increase ~15%. The frequency increase is of similar importance as the IPC increase.
Boothroid 9y ago
Memory and storage. Still big gains to be had there. Imagine if your whole hard drive was RAM speed. Also more specialised cores e.g. DSP, and customisable hardware i.e. FPGA.
- dr_zoidberg 9y ago
  I distinctly remember a benchmark (which my google-fu is currently unable to find) between Intel chips with and without the Iris chip. On similar conditions (clock base/turbo and core count), the Iris chip had about a 20% performance advantage. It wasn't explained in the benchmark, but the only reason I could imagine was the Iris chip worked as an L4 cache because the benchmark was not doing graphics stuff. That is what the Iris chip does, it sits right there in the socket with a whole bunch of memory available for the iGPU or work as L4 cache if available. It's also a great way to do (almost) zero cost transfers from main memory to (i)GPU memory -- you'd do it at the latency of the L3/L4 boundary. With intel, that unlocks a few GFLOPs of processing power -- in theory, your code would have to be adapted to work this in a reasonable way, of course. To sum things up, I agree with you, memory is a path that holds big speedups for processors. Don't know if "the Iris way" is the best path, but it indeed showed promise. Shame that Intel decided to lock it up for the ultrabook processors mostly.
  - noir_lord 9y ago
    I think the end point will be a massive chip with fast interconnects and a (relatively) huge amount of on die memory talking over a fast bus to something like nvme on steroids. My new Thinkpad has nvme and the difference is huge compared to my very fast desktop at work which has SATA connected SSD's.
chrisseaton 9y ago
> Some time ago a paper was posted here that showed how even if you have an infinite amount of transistors, you will still be limited in the range of 3-10 instructions-per-clock for typical programs. Do you know what papers that was? I would have thought that with infinite transistors you could speculatively execute all possible future code paths and memory states at the same time and achieve speedup that way.
- twoodfin 9y ago
  Oldie but goodie: http://www.hpl.hp.com/techreports/Compaq-DEC/WRL-93-6.pdf http://www.hpl.hp.com/techreports/Compaq-DEC/WRL-93-6.pdf Speculation can only take you so far. How do you speculatively execute something like: a = a + b[x]; ? You can't even speculatively fetch the second operand until you have real values for b and x. Trying to model all possible values explodes so much faster than all possible control paths that it's only of very theoretical interest.
jimbokun 9y ago
Isn't this an even further argument for cloud computing? If cost savings all come from having more cores at the same price, but end user devices can't put all those cores to work, having more of the compute intensive work happen on the back end amortized over many end users seems like the only way to benefit from improvements in cores per chip.
pcwalton 9y ago
It's not the end, if we as software developers can stop counting on the hardware folks to improve performance and do the hard work necessary to parallelize our apps. (This includes migrating components to use SIMD and/or GPUs as appropriate.)

ido 9y ago

When was the last time we saw a 50-100% performance gain in cars? airplanes? spacecraft? Was it the end of those industries? Welcome to mature technology.

meric 9y ago
> spacecraft Economically? I think this or last year.
- kuschku 9y ago
  Economically, SpaceX is about 3% cheaper than Arianespace. That's not a 50% or 100% improvement. Maybe they'll get that improvement once they run recycled rockets all the time, but not before that.
  - mlvljr 9y ago
    Will anyone debunk the above? :)
  - kuschku 9y ago
    @mlvljr: Your account seems to be shadowbanned, I can’t reply to your comment. Currently, SpaceX has prices around 56-62 million USD per launch of a normal satellite (with a weight and orbit where they can recover the first stage). Arianespace launches such lighter satellites in pairs, always two at once, at a price of around 60 million USD per satellite. The Chinese launchers offer the same at around 70 million USD per launch. So, the prices aren’t that different. But, for launches from reused rockets, SpaceX is damn cheap. The first launch on a reused rocket cost below 30 million USD. So, to recap: Today, in best case, SpaceX is between 4 and 13% cheaper than the next competitor. But in a few years, once they launch mostly reused rockets, they’ll be around 50 to 60% cheaper than the next competitor.
    - njarboe 9y ago
      I imagine that, while SpaceX will continue to improve their cost/kg to orbit and reach a launch expense of half the current cost with re-usables pretty quickly, until someone else can compete, they could just increase their profit per launch enormously. Musk needs some serious capital for his Mars plans. I hope his global satellite internet provider concept works (I can't wait to have a option other than AT&T or Comcast) and brings in the big bucks. Then he won't need to make money on launches and can drop the launch price on launches to close to cost to help all space activities. Maybe even start selling re-usable rockets to other launch companies. Can't wait to see that day. Long term, Musk is shooting for a ~100x reduction in launch costs to make a Mars colony feasible. Hope he makes it.

nostrademons 9y ago

GPUs: http://michaelgalloy.com/2013/06/11/cpu-vs-gpu-performance.html http://michaelgalloy.com/2013/06/11/cpu-vs-gpu-performance.h... http://www.anandtech.com/show/7603/mac-pro-review-late-2013/3 http://www.anandtech.com/show/7603/mac-pro-review-late-2013/... This is behind much of the interest in machine learning these days. Deep learning provides a way to approximate any computable function as the composition of matrix operations with non-linearities. It does this at the cost of requiring many, many times the computing power. But much of this computing cost can be parallelized and accelerated effectively on the GPU, so with GPU cores still increasing exponentially, at some point it's likely to become more effective than CPUs.

dom0 9y ago
I don't think GPUs are a particularly good solution for these, they aren't the future and won't be around for mass-deployment that much longer.
- heavenlyblue 9y ago
  It seems the author is down the 'deep learning' rabbit hole. >> It does this at the cost of requiring many, many times the computing power. But much of this computing cost can be parallelized and accelerated effectively on the GPU, so with GPU cores still increasing exponentially, at some point it's likely to become more effective than CPUs. So can be any matrix. Sadly, there aren't as many algorithms that are efficiently represented by one.
- chillydawg 9y ago
  That's quite a statement - what will replace GPUs for the ever increasing amount of ML work being done?
  - bitL 9y ago
    TPU-like chips; though they can be (partially) included on GPUs as well as is the case with the latest NVidia/AMD GPUs.

rphlx 9y ago

> Gains in instructions-per-clock start to flatten out. And that's where the gains were coming from in the last years. This is commonly claimed but it's actually false for x86_64 desktop parts. For a single core scalar integer workload the IPC boost from i7-2700k to i7-7700k was maybe 20-25% on a great day, but the base frequency increase was a further 20%, and max boost freq increase ~15%. The frequency increase is of similar importance as the IPC increase.

Boothroid 9y ago

Memory and storage. Still big gains to be had there. Imagine if your whole hard drive was RAM speed. Also more specialised cores e.g. DSP, and customisable hardware i.e. FPGA.

dr_zoidberg 9y ago
I distinctly remember a benchmark (which my google-fu is currently unable to find) between Intel chips with and without the Iris chip. On similar conditions (clock base/turbo and core count), the Iris chip had about a 20% performance advantage. It wasn't explained in the benchmark, but the only reason I could imagine was the Iris chip worked as an L4 cache because the benchmark was not doing graphics stuff. That is what the Iris chip does, it sits right there in the socket with a whole bunch of memory available for the iGPU or work as L4 cache if available. It's also a great way to do (almost) zero cost transfers from main memory to (i)GPU memory -- you'd do it at the latency of the L3/L4 boundary. With intel, that unlocks a few GFLOPs of processing power -- in theory, your code would have to be adapted to work this in a reasonable way, of course. To sum things up, I agree with you, memory is a path that holds big speedups for processors. Don't know if "the Iris way" is the best path, but it indeed showed promise. Shame that Intel decided to lock it up for the ultrabook processors mostly.
- noir_lord 9y ago
  I think the end point will be a massive chip with fast interconnects and a (relatively) huge amount of on die memory talking over a fast bus to something like nvme on steroids. My new Thinkpad has nvme and the difference is huge compared to my very fast desktop at work which has SATA connected SSD's.

chrisseaton 9y ago

> Some time ago a paper was posted here that showed how even if you have an infinite amount of transistors, you will still be limited in the range of 3-10 instructions-per-clock for typical programs. Do you know what papers that was? I would have thought that with infinite transistors you could speculatively execute all possible future code paths and memory states at the same time and achieve speedup that way.

twoodfin 9y ago
Oldie but goodie: http://www.hpl.hp.com/techreports/Compaq-DEC/WRL-93-6.pdf http://www.hpl.hp.com/techreports/Compaq-DEC/WRL-93-6.pdf Speculation can only take you so far. How do you speculatively execute something like: a = a + b[x]; ? You can't even speculatively fetch the second operand until you have real values for b and x. Trying to model all possible values explodes so much faster than all possible control paths that it's only of very theoretical interest.

jimbokun 9y ago

Isn't this an even further argument for cloud computing? If cost savings all come from having more cores at the same price, but end user devices can't put all those cores to work, having more of the compute intensive work happen on the back end amortized over many end users seems like the only way to benefit from improvements in cores per chip.

pcwalton 9y ago

It's not the end, if we as software developers can stop counting on the hardware folks to improve performance and do the hard work necessary to parallelize our apps. (This includes migrating components to use SIMD and/or GPUs as appropriate.)