Interesting that Maxwell's not mentioned in that slide but they show Fermi and Kepler... Wonder how this would rank, who knows, maybe very close to Pascal.

Maxwell doesn't have a card that has dedicated DP on it -- they are all cut down.

It's an estimated computing performance taken from slides from June 2015.

A slide from an Nvidia presentation is stirring some things on the web as it seems as some info on the Flagship GPUÂ*in the new 14nm Pascal architecture (likely GP100) would be able to perform numbers... Nvidia Slide reveals numbers on Single and Double precision for Flagship pascal GPU

From what I know Nvidia cripped or removed double precision form their consumer level Geforce cards so they didn't cut into lucrative sales of their way more expensive pro cards, but AMD did not do this. Hence my humble dual GPU HD7990 card has a DP performance of over 2000 whereas the Tesla K20X only has 1310 and how much is a Tesla K20X these days? Over two grand? and originally costing?

I think it's more apt to compare the HD7990 to the Titan Black, which was also $1000, is only ~150Gflops less DP performance, but ~100w less power - though it did launch a year later. Nvidia shifted away from DP performance because most of the HPC market shifted towards neural networks, which perform best in mixed precision. I mean yeah, differentiating their products was also probably a large factor, but it's not like Maxwell even had a DP card. That's why I'm kind of curious to see what they do with Pascal. They are going offer mixed (FP16) full (FP32) and Double (FP64). I wonder if they will come out with a card marketed specifically towards neural networks with FP16/32, a gaming card with FP32, and a workstation card with 32/64.

I dont know if your report is wrong, but is really a majority of the HPC market, so a majority of HPC servers are really dedicated on Neural Network analysis ? This a new growing market, but im not really sure that a majority of HPC servers are now dedicated to research about it. Big data, scientist market, medical research.. i mean, HPC servers are used in nearly one thousand of different " research " type. When discussing about it, on BY3d as example, if important in term of research, it was still a niche market in term of servers and center dedicated to it.

I mean it's the majority of the growing market. All kinds of companies, large and small, are getting into it, in all different types of disciplines. And I think it's pretty obvious that Nvidia has shifted it's attention. They wouldn't waste resources on redesigning their architecture specifically for Neural Networks if it was only 1/1000s of the market. It's obviously larger then that and has demand in the industry.

I mean it's the majority of the growing market. All kinds of companies, large and small, are getting into it, in all different types of disciplines. And I think it's pretty obvious that Nvidia has shifted it's attention. They wouldn't waste resources on redesigning their architecture specifically for Neural Networks if it was only 1/1000s of the market. It's obviously larger then that and has demand in the industry. Edit: You Keep editing your post. Neural Networks have been around for way longer then 2012.. There was CUDA accelerated Neural Network applications like Aquila since 2010. In fact I'm pretty sure Nvidia had people from Matlab talk about their Neural Network implementation when the Kepler variants of Tesla launched.

I'm going to ask this again since everyone has ignored it, but why is this article stating that Pascal is 14nm when every other news site has been claiming it's 16nm for months now?

Volta for me then.. pascal Looks more like a test hbm card for now, so even better later on since it will mature with volta.