NVIDIA Kepler speculation thread

Echelon is a system built on an architecture. Kepler is a continuation of Fermi on 28HP. So this means that Echelon is Maxwell.

No, this is beyond Maxwell. The slides show Maxwell as being about 15 GF/watt, so call it 4TF per GPU. The exaflop GPU design goal is another order of magnitude beyond that at 40TF/GPU, as seen by the slides.

Also the time scale on the slides show a projected 2016 production. NVidia's track record between major family updates is about 18-24 months. (G80 was early 2007, GT200 was mid 2008, GF100 was mid 2010).
 
20pJ for a DP FMA on 28nm excluding all overhead would mean than 5.5W/TF. That certainly puts things in perspective!
 
No, this is beyond Maxwell. The slides show Maxwell as being about 15 GF/watt, so call it 4TF per GPU. The exaflop GPU design goal is another order of magnitude beyond that at 40TF/GPU, as seen by the slides.

Also the time scale on the slides show a projected 2016 production. NVidia's track record between major family updates is about 18-24 months. (G80 was early 2007, GT200 was mid 2008, GF100 was mid 2010).



Ok so we have:

G80 (NV50), late 2006 (it was 2006 not 2007)
GT200 (NV55), mid 2008
Fermi (NV60), mid 2010
Kepler (NV65), late 2011
Maxwell (NV70), late 2013
unnamed Nvidia GPU for Echelon (NV80) - 2016
 
20pJ for a DP FMA on 28nm excluding all overhead would mean than 5.5W/TF. That certainly puts things in perspective!
Except that it's the overhead that makes things very costly, energy-wise (as you're well aware). And that getting the data where it's needed, costs much more energy (I think order(s) of magnitude here) compared to the calculation itself.
 
Except that it's the overhead that makes things very costly, energy-wise (as you're well aware). And that getting the data where it's needed, costs much more energy (I think order(s) of magnitude here) compared to the calculation itself.
Yes, my point was that this is a pretty good indication of the importance of architectural innovation :) If the ALU power was a much higher percentage, then it wouldn't be quite as critical. Clearspeed certainly had an extremely impressive architecture in terms of perf/w for HPC, but then again it was fairly restrictive.
 
The hierarchy of registers and customizable SRAM memory match Dally's earlier statements about minimizing data movement.
I'm curious what overheads are involved in making the memory so flexible as to allow it to subdivide itself into multiple levels of cache.
 
Almost OT but I guess there is no better place to ask, who are the companies competing to win this market (echelon)?
 
Your answer lies in the original article.

original article @ eetimes said:
Nvidia's Echelon system will compete with teams from Intel, MIT and Sandia National Labs, each taking different approaches to build power efficient exascale systems.
 
Are we certain that Kepler will be a refresh/improvement on the Fermi architecture or a whole new architecture altogether?
Well, the timing is most definitely right for the next major architecture from nVidia to be a refresh of Fermi. They haven't broken their new architecture->upgrade cycle yet.
 
So which physicist(s) cover G80 and GT200? And if there is only one name in NV DX10 generation what is the so called "middle life kicker"? What came before Tesla (which "physicist" and what chip was the last part of that family) and what after Tesla (this is an obvious one: Fermi and GF100).
 
So which physicist(s) cover G80 and GT200?

Why stop at G80 and GT200? Given that some folks round here have the really bizarre habit of wishing to map current and future NVIDIA architectures to the long-disused NVxx naming scheme (that was dropped long before NV likely even conceived of these new generations), why not do the reverse and assign physicist names to NVIDIA architectures all the way back to NV1?!

:p
 
So which physicist(s) cover G80 and GT200? And if there is only one name in NV DX10 generation what is the so called "middle life kicker"? What came before Tesla (which "physicist" and what chip was the last part of that family) and what after Tesla (this is an obvious one: Fermi and GF100).

G80 obviously didn't have something like this. G stands still for Geforce and there's nothing left besides the number. GT200 was Tesla (Geforce Tesla), the mid-life kicker supposedly GTX285, but there I am not sure, that everything went according to the original plans.

GF100 is Geforce Fermi, GKx00 (maybe they'll start with 100 again - they definitely should) will be Geforce Kepler, GMx00 Geforce Maxwell.

That at least is my interpretation.
 
I'm sure I've seen a list of NVidia's "scientist" codenames and they stretch back into the mists of time (pre-dating CUDA). Can't find it again though :???:
 

Unless my aging memory fails they've had scientists in there for a long time. It goes something like:

  • NV10 - Celsius
  • NV20 - Kelvin
  • NV30 - Rankine
  • NV40 - Curie
  • G80 (NV50) - Tesla
GT200 didn't get anything new because it was merely an evolution of the base Tesla arch, AFAIK. There's appendix A in "Computer Organization and Design" by Patterson & Hennessy, (probably ghost)written by John Nickolls and David Kirk where they specifically refer to the G80 as the Tesla compute architecture.

OT: Arguably, this is pretty good trolling material if one stops to think about it - NVIDIA cards are clearly designed for serious scientific stuff, just look at their codenames...unlike those ATI bums who use plants and islands, clearly gaming focused hippies they are! I'm quite amazed it hasn't been used yet, TBH.
 
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