What GP102 Could Mean for NVIDIA
Is Enterprise Ascending Outside of Consumer Viability?
So a couple of weeks have gone by since the Quadro P6000 (update: was announced) and the new Titan X launched. With them, we received a new chip: GP102. Since Fermi, NVIDIA has labeled their GPU designs with a G, followed by a single letter for the architecture (F, K, M, or P for Fermi, Kepler, Maxwell, and Pascal, respectively), which is then followed by a three digit number. The last digit is the most relevant one, however, as it separates designs by their intended size.
Typically, 0 corresponds to a ~550-600mm2 design, which is about as larger of a design that fabrication labs can create without error-prone techniques, like
multiple exposures (update for clarity: trying to precisely overlap multiple designs to form a larger integrated circuit). 4 corresponds to ~300mm2, although GM204 was pretty large at 398mm2, which was likely to increase the core count while remaining on a 28nm process. Higher numbers, like 6 or 7, fill back the lower-end SKUs until NVIDIA essentially stops caring for that generation. So when we moved to Pascal, jumping two whole process nodes, NVIDIA looked at their wristwatches and said “about time to make another 300mm2 part, I guess?”
The GTX 1080 and the GTX 1070 (GP104, 314mm2) were born.
NVIDIA already announced a 600mm2 part, though. The GP100 had 3840 CUDA cores, HBM2 memory, and an ideal ratio of 1:2:4 between FP64:FP32:FP16 performance. (A 64-bit chunk of memory can store one 64-bit value, two 32-bit values, or four 16-bit values, unless the register is attached to logic circuits that, while smaller, don't know how to operate on the data.) This increased ratio, even over Kepler's 1:6 FP64:FP32, is great for GPU compute, but wasted die area for today's (and tomorrow's) games. I'm predicting that it takes the wind out of Intel's sales, as Xeon Phi's 1:2 FP64:FP32 performance ratio is one of its major selling points, leading to its inclusion in many supercomputers.
Despite the HBM2 memory controller supposedly being actually smaller than GDDR5(X), NVIDIA could still save die space while still providing 3840 CUDA cores (despite disabling a few on Titan X). The trade-off is that FP64 and FP16 performance had to decrease dramatically, from 1:2 and 2:1 relative to FP32, all the way down to 1:32 and 1:64. This new design comes in at 471mm2, although it's $200 more expensive than what the 600mm2 products, GK110 and GM200, launched at. Smaller dies provide more products per wafer, and, better, the number of defective chips should be relatively constant.
Anyway, that aside, it puts NVIDIA in an interesting position. Splitting the xx0-class chip into xx0 and xx2 designs allows NVIDIA to lower the cost of their high-end gaming parts, although it cuts out hobbyists who buy a Titan for double-precision compute. More interestingly, it leaves around 150mm2 for AMD to sneak in a design that's FP32-centric, leaving them a potential performance crown.
Image Credit: ExtremeTech
On the other hand, as fabrication node changes are becoming less frequent, it's possible that NVIDIA could be leaving itself room for Volta, too. Last month, it was rumored that NVIDIA would release two architectures at 16nm, in the same way that Maxwell shared 28nm with Kepler. In this case, Volta, on top of whatever other architectural advancements NVIDIA rolls into that design, can also grow a little in size. At that time, TSMC would have better yields, making a 600mm2 design less costly in terms of waste and recovery.
If this is the case, we could see the GPGPU folks receiving a new architecture once every second gaming (and professional graphics) architecture. That is, unless you are a hobbyist. If you are? I would need to be wrong, or NVIDIA would need to somehow bring their enterprise SKU into an affordable price point. The xx0 class seems to have been pushed up and out of viability for consumers.
Or, again, I could just be wrong.