On the 20th of April 2013 there was an interesting discussion between Jan Gray and David Kanter. Jan is a specialist in C++ and FPGAs (twitter, homepage). David is a specialist in CPU and GPU architectures (twitter, homepage). Both know their ways well in the field of semiconductors. It is always a joy to follow their short discussions when they happen, but there was something about this one that made me want to share it with special attention.
OpenCL on ARM: Growth-expectation of GFLOPS/Watt of mobile GPUs exceeds Moore’s law. That’s incredible!
Jan Gray: .@OpenCLonARM GFLOPS/W more a factor of almost-over Dennard Scaling. But plenty of waste still to quash. http://www.fpgacpu.org/papers/Gray_AutumnOfMooresLaw_SingularityUniversity_11-06-23.pdf …
Jan Gray: .@openclonarm Scratch Dennard tweet: reduced capacitance of yet smaller devices shd improve GFLOPS/W even as we approach end of Vdd scaling.
David Kanter: @jangray @OpenCLonARM I think some companies would argue Vdd scaling isn’t dead…
Jan Gray: @TheKanter @openclonarm it’s not dead, but slowing, we’ve gone from 5V to 1V (25x power savings) and have maybe several hundred mVs to go.
David Kanter: @jangray I reckon we have at least 400mV, so ~2X; slower than ideal, but still significant
Jan Gray: @TheKanter We agree, I think.
David Kanter: @jangray I suspect that if GPU scaling > Moore’s Law then they are just spending more area or power; like discrete GPUs in the last decade
David Kanter: @jangray also, most positive comment I’ve heard from industry folks on mobile GPU software and drivers is “catastrophically terrible”
Jan Gray: @TheKanter Many ways to reduce power, soup to nuts. For ex HMC DRAM on interposer for lower energy signaling. I’m sure many tricks to come.
In a nutshell, all the reasons they think mobile GPUs can outpace Moore’s law while staying under a certain power-usage.
It needs some background-info, so let’s start the background of the first tweet, and then explain what has been said. Continue reading “Scaling mobile GPUs to 1000 GFLOPS”


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