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Saturday, March 20, 2010
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nVidia's GT300 is "smaller, faster than Larrabee"?



It looks like nVidia is dead set on calming the PR storm the competitors are releasing, and the mood in the company is more relaxed. nVidia is certain they have a winner on their hands, but only time will tell whether they managed to pull it through or not.

We already gave you details on the architectural side. GT300 or G300 or NV70 is consisted out of 512 cores [or Shader Processors, whatever you like], features a 512-bit memory controller connecting to GDDR5 memory and well, it is a beast. nVidia packed everything in around 2.4 billion transistors using TSMC's 40nm high-performance process [yes, the one with currently sucky yields]. Given that the original GT200 packed 240 shaders in 1.4 billion trannies, one could argue that nVidia did some heavy dieting on its own architecture and managed to get a body builder shader power in a size zero body. GT300 packs 512 MIMD-capable cores and yet it uses "just" one billion transistors extra. I'll be first to admit that I wondered how GT300 packs at least three billion transistors, but according to our highly confidential source, the 2.4 billion transistors are packed in just 495mm2.

Yes, you've read that correctly. 2.4 billion in less than 500mm2 will put sweat on both ATI and Intel's forehead, since this chip could be profitably manufactured and yet pack performance to potentially blew the competition out of the water. Each of original 65nm GT200 chips took 576mm2 of wafer space, while 55nm refresh GT206/GT200b eats up 490mm2.

In comparison, Intel's high-end Larrabee part is manufactured in 45nm and takes around 600mm2.

Now, if you are wondering why nVidia created a single-PCB GTX295, think again. This part is more than an engineering exercise - but let us put it in this perspective - if nVidia managed to put 2.4 billion transistors in less than 500mm2, with an interesting performance delta between GT200-GT300 in clock-per-clock comparison… we could say that Jen-Hsun definitely opened a can of whoop-ass on its competitors.



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Comments:

I agree with the General by: Gipsel on 5/14/2009
The die size isn't surprising.
(0.4/0.55) * 2.4/1.4 = 0.9
Factoring in the non ideal scalig and I would also expect a die size similar to the GT200b.

But you should consider something else. AMDs RV740 contains more than 800 million transistors (826 million if I remember right) and has a die size below 140 mm² That means they could produce a 2.4 billion transistor GPU with a 384 bit memory interface in roughly 400 mm².
Actually, I'm guessing RV870 to stay below 2 billion transistors and to have a die size of not much more than 300mm². Still, performance wise it could be right on the heels of GT300 (especially with aggressive pricing). The GT300 concept has to work better than the GT200 one, otherwise it won't help much financially.
Why's that a surprise? by: General Lee D. Mented on 5/12/2009
They've taken such a beating on cost I'd be surprised if they didn't aggressively come back with a squeezed die. Nvidia's strength was always when they listened to the market and fixed their biggest weakness (see Timeline: 3dfx Revisited, Aceshardware 2003).

As for transistor count figure 400-500k is carried over as the 512bit memory controller, its cache, and the ROPs and suddenly 1billion->2billion for 240->512 doesn't seem so improbable does it?

As for the die size... I dunno, check my math? 1.4 billion transistors in 576mm^2 = 411mm^2 per billion transistors. 2.4 billion in 490mm^2 = 204mm^2 per billion transistors. 411/204 = 2.015 so the area scaling factor is just over 2. 65^2 / 40^2 = 2.64x shrink. Theoretically 45nm should have been enough (2.09x), but obviously there's some margin there. If it were perfect then 2.4 billion transistors should be 373mm^2... maybe Nvidia's being a bit conservative? ;)

Anyway, die size does not say jack about power requirements, heat production, performance, or max clockspeed. So there's still a lot of variables in the air. Until working silicon goes toe to toe vs Larabee I'm unwilling to predict a winner in performance or even performance per dollar.
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