20160221, 22:21  #1 
Apr 2010
Over the rainbow
3^{2}·5·59 Posts 
Nvidia Pascal, a third of DP
http://www.techtimes.com/articles/13...singpower.htm
Based on a number of slides from an independent researcher, the Nvidia Pascal GPU100 features Stacked DRAM (1 TB/s) giving it as much as 12 TFLOPs of SinglePrecision (FP32) compute performance. The flagship GPU is purportedly able to provide four TFLOPs of DoublePrecision (FP64) compute performance as well. Last fiddled with by wblipp on 20160221 at 23:40 
20160222, 02:13  #2 
Romulan Interpreter
"name field"
Jun 2011
Thailand
9787_{10} Posts 
Yarrrr !!!

20160222, 04:04  #3  
Oct 2015
412_{8} Posts 
Quote:


20160222, 07:58  #4  
Einyen
Dec 2003
Denmark
2×7×227 Posts 
12 TFLOPS FP32 and 4 TFLOPS FP64 *drool* It will be hard to decide whether to run factoring or LL on it.
Quote:


20160222, 08:37  #5  
Romulan Interpreter
"name field"
Jun 2011
Thailand
9,787 Posts 
Quote:
Trial Factoring... (maybe.... you can use 8 of those to keep the precision of 80 to 88 bits, depending of content, but you will need about 72 multiplications to multiply those 8x8 "digits", with some karatsubalike stuff (edit: can it be done in 72 multiplications?? don't forget that you multiply 11 bits times 11 bits and get 11 bits result, not 22 bits), so you will only get a third of a teraflop, like a gtx 560 or so. OTOH, I assume they will make a kill at integer arithmetic too, so FP16 will not be the best choice for TF either ...) Last fiddled with by LaurV on 20160222 at 08:40 

20160222, 09:27  #6 
Jun 2003
3×17×101 Posts 
I am gonna go out on a limb and predict that there will be no consumer/prosumer version that offers 4 TFLOPS DP (i.e. not even a 1000$ Titan variety will offer 4 TFLOPS)

20160222, 12:23  #7 
Feb 2016
UK
2^{3}·5·11 Posts 
Looking at previous high rate DP cards and their release dates:
R9 280X, ~1 TFLOP, Oct. 2013 Titan ~1.5 TFLOP, Feb. 2013 Titan Black 1.7 TFLOP, Feb. 2014 Could they manage to get it up to 4 in 2 years? I think there's more than a possibility they can, if they want to, in a higher end card. Especially now they're finally moving onto smaller manufacturing process again. 
20160222, 12:43  #8 
Einyen
Dec 2003
Denmark
6152_{8} Posts 

20160222, 12:47  #9 
Jun 2003
3·17·101 Posts 

20160222, 15:19  #10  
"Marv"
May 2009
near the Tannhäuser Gate
1235_{8} Posts 
Quote:
http://www.mersenneforum.org/showpos...&postcount=604 Do you want 3 Tflops FP64 from an Nvidia board? It's been available for a year on their K80 Tesla! The catch is it costs 5,000 dollars and requires intense, cooling found in servers located in frigid computer rooms. You can bet your boots Pascal chips with gobs of FP64 are destined for Teslas and not for the great unwashed masses ( us ). Even Nvidia's expected April announcement will probably be a "tease" in that regard. BTW, FP16 is there for Deep Learning Neural Nets, which is the hottest thing in AI right now. Researchers have done some truly amazing things with these such as driving cars and beating a GO master. Nvidia has very nice libraries for these. They require zillions of small FP values for all the weights used during training. They can tolerate loss of precision FP16 provides and are willing to trade that for having twice as many in memory as FP32 values. 

20160222, 15:20  #11 
Feb 2016
UK
2^{3}×5×11 Posts 
Go on then, I'll take the optimistic route that they will put this in a consumer device, perhaps a future Titan something.
The fastest singlechip compute device they do is the K40, which appears to use the same chip as the Titan Black. They can still differentiate between the products in other ways. It's not like they're going to stand still in compute either, and they can't risk AMD not crippling their offering and looking bad. 
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