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[PCG]Nvidia CEO says Moore’s Law is dead and GPUs will replace CPUs

post #1 of 23
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Quote:
In case you were unaware, Moore's Law is no longer relevant, as GPUs are advancing at a much faster pace than CPUs. That was the message from Nvidia CEO Jensen Huang, who stated at the GPU Technology Conference (GTC) 2017 in Beijing, China that graphics processors are on track to replace CPUs, SegmentNext reports.

Moore's Law is the name given to an observation made by Intel co-founder Gordon Moore in 1965. Moore noticed that the number of transistors per square inch on integrated circuits had doubled every year, and he predicted that would be the case for the next decade. He later revised his prediction to every two years.

Usually when people talk about Moore's Law coming to an end, they're referring to technical roadblocks that stand in the way of cramming more transistors into smaller spaces, while maintaining the same leaps in performance. Huang partially agrees with that, at least as it pertains to CPU performance—he said that while CPU transistors have grown at a pace of 50 percent annually, performance only jumps by 10 percent.

The other reason Huang says Moore's Law is dead is because it can't keep pace with advancements in GPU design. Huang talked about GPUs growing in computational capacity over the years, and how they're the better suited for advancements in artificial intelligence.

Huang also said that GPUs will replace CPUs soon, adding that at this point, designers can hardly work out advanced parallel instruction architectures for CPUs.

Source
post #2 of 23

Interesting, well they already have the pricing model set lol. I've been wondering for some time when a GPU technology would take the lead in computing period for the very reason that they seem to be suited towards parallel workloads.

post #3 of 23
Hadn't they already?
Raw power compute wise, in many cases already GPUs are the default go-to for heavy tasks.
If you want an AI or any big datacenter compute system, you are going for a GPU more than CPU. Even intel's phi are losing market for GPUs already. Especially that even top pricy GPUs are cheaper than the phi processors.
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post #4 of 23
Quote:
Originally Posted by Ghoxt View Post

Interesting, well they already have the pricing model set lol. I've been wondering for some time when a GPU technology would take the lead in computing period for the very reason that they seem to be suited towards parallel workloads.

Yeah precisely. It's not so much that GPU's increase at a faster rate generationally that is the issue here. (although this is definitely true. We regularly see ~50% jumps in GPU technology from gen to gen at roughly equivalent prices, compared to the nonsensical 5-10% of CPU's. However it's debatable how much of this has been due to lack of competition for Intel who has been the only real choice for high performance CPU's in the past decade-ish; notice how we're finally seeing mainstream $300 chips move from 4 to 6 cores and see a massive knee-jerk 10 to 18 core HEDT jump now that we have actual AMD competition. These core increases certainly aren't as useful as the old 200nm to 100nm type large node jumps we used to see of course, but it still shows that Intel has been stonewalling and price gouging keeping gains as low as customers will accept without deciding not to buy)

The real issue is how GPU's are much better setup for parallel workflow. With all but the highest tier Xeons you are limited to one CPU, and adding a second E5/.E7 Xeon simply increases cores and increases latency by introducing "bottlenecks" like QPI linking and whatnot. There's "some" hope with things like Omni-Path, but honestly I don't see it making that big of a difference, as the future appears to be far more in line with OFFLOADING from the CPU rather than increasing network throughput and such. And unlike CPU's which are limited to 4 even on the most insane board, and STILL just increase latency for a higher core count and possible increase in hosts etc... GPU's can total 8 as of now and have PCI-E 4.0 around the corner as well as NVLink already allowing them to far surpass the latency limit between dual-CPU systems.

So offloading work to a Octave of Tesla V100's etc.. is far more effective than anything traditional CPU's are capable of. Deep learning dedicated systems like the Nvidia DGX utilize a single or maybe dual Xeon's (usually not even necessary) with the eight Tesla/Quadro/TITANs for a reason.
Edited by DarkIdeals - 10/1/17 at 1:25pm
 
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post #5 of 23
Moore's law is just as relivant to GPUs as it is to CPUs. Nvidia's solution has been to increase die size. Monolithic dies are not the solution...
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post #6 of 23
You can most certainly avoid moores law if you get your customers to believe your low end is high end.
post #7 of 23
Sure! Let's compare apples to oranges more, Nvidia! Thanks! rolleyes.gif


EDIT:

Also... CPUs haven't improved gen to gen because Intel only JUST acquired a real competitor again. Competition drives innovation. tongue.gif
Edited by Imglidinhere - 10/1/17 at 2:08pm
     
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post #8 of 23
CPUs are about single-threaded performance.
GPUs are about parallel performance.

Until GPUs can match CPUs in single-threaded performance, CPUs aren't going away.

  • CPUs have stonewalled in single-threaded performance because they are hitting physical limits in IPC and frequency scaling as well as a lack of competition.
  • GPUs have been able to scale in parallel performance by simply increasing the number of cores/SMs.
post #9 of 23
Cpu stone wall themselves with patents and license refusal.

The anti competitive nature of intel caused the lack of innovation in this space.
post #10 of 23
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