There have been a few NVIDIA datacenter stories popping up over the last couple of months. A month or so after Google started integrating Pascal-based Tesla P100s into their cloud, Amazon announced Telsa V100s for their rent-a-server service. They have also announced Volta-based solutions available or coming from Dell EMC, Hewlett Packard Enterprise, Huawei, IBM, Lenovo, Alibaba Cloud, Baidu Cloud, Microsoft Azure, Oracle Cloud, and Tencent Cloud.
This apparently translates to boatloads of money. Eyeball-estimating from their graph, it looks as though NVIDIA has already made about 50% more from datacenter sales in their first three quarters (fiscal year 2018) than all last year.
They are also seeing super-computer design wins, too. Earlier this year, Japan announced that it would get back into supercomputing, having lost ground to other nations in recent years, with a giant, AI-focused offering. Turns out that this design will use 4352 Tesla V100 GPUs to crank out 0.55 ExaFLOPs of (tensor mixed-precision) performance.
As for product announcements, this one isn’t too exciting for our readers, but should be very important for enterprise software developers. NVIDIA is creating optimized containers for various programming environments, such as TensorFlow and GAMESS, with their recommended blend of driver version, runtime libraries, and so forth, for various generations of GPUs (Pascal and higher). Moreover, NVIDIA claims that they will support it “for as long as they live”. Getting the right container for your hardware is just filling out a simple form and downloading the blob.
NVIDIA’s keynote is available on UStream, but they claim it will also be uploaded to their YouTube soon.
That V100 is what Intel hired
That V100 is what Intel hired Raja to produce a competing GPU Compute/AI accelerator for Intel’s HPC/AI and enterprise market. And Raja is not going to have any time to think about gaming so Intel will source gaming GPUs from AMD in semi-custom form.
JHH is growing Nvidia’s revenues faster with the HPC/AI, enterprise markets, auto markets, and other non gaming related visual computing sorces. So as each business quarter passes look for gaming revenues to become of less and less importance for Nvidia as the revenue growth for non gaming sorces dwarfs Nvidia’s revenues from gaming.
AMD had Raja produce that Vega 10 compute/AI focused Vega 10 base die design for a reason and that reason is the same reason that Intel Hired Raja for and that’s GPUs for HPC/AI and the enterprise markets and not so much gaming. AMD’s Epyc HPC/AI and enterprose markets need that Vega 10 based Radeon Pro WX and Radeon Instinct MI25 SKUs for the same markets that JHH over that Nvidia is earning the great revenue growth on.
Gamers will have to do with the die bins for a little while longer from AMD and Nvidia is hardly going to be motivated to up its consumer game until AMD maybe fields a better Vega variant at that GF 12nm node that is more tuned for gaming. Intel, AMD, and Nvidia are really going after the HPC/AI and enterprose revenues and the new AI market just adds to the growing tide for revenue growth in the professional markets.
For GPUs gaming usage only workloads and revenues have been eclipsed by GPUs as compute/AI powerhouses and those revenues will dwarf any gaming revenues going forward.
PC sales have declined for
PC sales have declined for the past couple of years according to JPR.
Intel personal computing sector has declined 8% for the past few years and this year it looks to stay flat.
Having all this is good, but
Having all this is good, but not in a closed source system which is controlled by just one company.
Look, its the Fonz! Ayyyy
Look, its the Fonz! Ayyyy