Nvidia's Kepler to get compute cousin, says analyst
MOUNTAIN VIEW, Calif.--
Nvidia Corp. will likely announce a follow-up to its recently launched Kepler platform to better address upcoming compute products and the high performance computing (HPC) space later this year, according to an analyst.
David Kanter of Real World Technologies said the newly launched Kepler platform was specialized for high-end graphics, whereas more general purpose workloads would necessitate a differentiated version of the chip in order for Nvidia to remain competitive in the HPC space.
It will be a derivative of Kepler, to re-use as much of the engineering effort as possible, but with several significant changes, he said, hinting that a Kepler cousin could be announced as soon as May.
When it comes to different workload requirements, Kanter said it was clear that a graphics centric chip would not require much in the way of cross-system communication, whereas scientific computing did need it for algorithms to be efficient.
For purely graphical use, the pixel thats on the bottom left corner of your screen doesnt care what the pixel in the middle of the screen is doing at all, he explained, noting this wasnt the case when trying to accelerate flow calculations or other more complex HPC data.
Thus, said Kanter, the hardware for each specific purpose -- gaming or scientific-- would have to be slightly different.
Fermi had great resources for communicating between different parts of the application, but Kepler doesnt have nearly as much capability to communicate between various levels of the system, said Kanter, explaining that this would require a two-fold approach from Nvidia.
I dont believe Nvidia is abandoning HPC at all, its clear to me that the firm will continue on that path, because the area is really heating up, especially with AMDs new offerings in the space and Intel on track to release Knights Corner at the end of this year. Nvidia cant be trying to enter this market with one hand tied behind its back, he said.
On the other hand, said Kanter, Nvidia is also acutely aware that it had not done quite as well as its rival AMD in the last round of the graphics battle, namely because it had spent a lot of resources in terms of power and area on things that were more useful for compute but not useful for graphics.
Hence, Fermi was much more attractive in the HPC space than in the niche high-end gaming segment.
What Nvidia decided to do with Kepler was to scale it back, to really focus on graphics, said Kanter, noting that the Kepler follow-up would likely be a bit more separate and distinct to fine tune it for general purpose.
Compute specific GPU requirements
Compute products, said Kanter, require error-correcting code ECC memory to protect data, as well as double precision for more floating point accuracy, important for things that aren't graphics.
AMD had a much more graphics optimized chip in the last generation and so, rather than have one design to rule them all,
Nvidia will likely split Kepler into two families and reuse a lot of the same elements but have slightly different features for the separate workloads, he said.
The approach is somewhat similar to what Intel did with its server and client version of SandyBridge, though the firm effectively used the same core for both but simply added a lot more cache and memory bandwidth to the server version, which also had twice as many cores, more PCI express and QPI. Thats the ideal thing to do, said Kanter, though he said
Nvidias plan would be to build similar cores but not quite the same.
Nvidia has to scale it up to do the compute side, so it will probably be a much bigger chip, he said.
This variant on Kepler should make its official launch at Nvidias graphics technology conference (GTC) in May, with products likely to appear around the Q4 timeframe.
Kanter said the real issue was not necessarily whether Nvidia could design such a product, but whether its manufacturing partner TSMC could actually produce it with sufficient yields, especially as the 28-nm process was still so new.
Yields, said Kanter, typically only improved with time, and this, he said, is also the reason that Intel never started out on a new process technology with a large die.
By coming out first with the consumer graphics part, which is smaller at around 30-mm squared, Nvidia can wait for TSMCs yields to mature before coming out with Keplers larger compute cousin for which it will likely need a larger die size of around 500-mm squared range.
When asked, Nvidia said it had not spoken to Kanter about its compute solutions for Kepler but wouldnt comment further.