[tyrfing]

Discrete GPUs have historically been a relatively small and volatile niche compared to CPUs, it's only in the last few years that the market has seen extreme growth.

edit: the market pretty much went from gaming as the primary pillar to gaming + HPC, which makes it far more attractive since you'd expect it to be much less cyclical and less price sensitive. Raja Koduri was hired in late 2017 to work on GPU related stuff, and it seems like the first major products from that effort will be coming out this year. That said, they've obviously had a lot of failures in the acelerator and graphics area (consider Altera) and Koduri has stated on Twitter that Gelsinger is the first CEO to actually treat graphics/HPC as a priority.

[michaelt]

CUDA came out in 2007. Wikipedia puts the start of the GPU-driven 'deep learning revolution' in 2012 [1] and people have been putting GPUs into their supercomputers since 2012 as well [2]

I find it strange that Intel has basically just left the entire market to nvidia, despite having 10-15 years warning and running their own GPU division the whole time.

[1] https://en.wikipedia.org/wiki/Deep_learning#Deep_learning_re... [2] https://en.wikipedia.org/wiki/Titan_(supercomputer)

[ksec]

Competing with Nvidia on Gaming GPU wasn't something Intel were keen to do after their failure with i740. The Gaming market wasn't as big, and you are ultimately competing on Driver optimisation, not on actual hardware.

CUDA and Deep Learning may have started in 2007 and 2010. But their usage, or their revenue potential was unclear back then. Even in 2015, Datacenter revenue was less than one eighth of gaming revenue. And rumours of Google AI Processor ( now known as TPU ) started back in 2014 when they started hiring. In 2021, Datacenter is roughly equal to Gaming revenue, and are expected to exceed them in 2022.

Intel sort of knew GPGPU could be a threat by 2016 / 17 already. That is why they started assembling a team, and hired Raja Koduri in late 2017. But as with everything Intel in post Pat Gelsinger era, Intel was late to react. From Smartphone to Foundry Model and now GPGPU.

[jml7c5]

They created the Xeon Phi[1] for that niche. It was spun out of Larabee[2]. I presume they will be taking advantage of their coming GPU architecture for more going forward.

[1]: https://en.wikipedia.org/wiki/Xeon_Phi

[2]: https://en.wikipedia.org/wiki/Larrabee_(microarchitecture)

[pastaguy1]

They tried to check many, some, maybe possibly more of the boxes with the Xeon Phi, and it kinda seems like things simply didn't go their way.

Cuda wasn't as flexible, and the payoff wasn't as big in 2010 or so as it is now.

I've never used a phi, but i can see where they were coming from i think. No need for a full rewrite like Cuda (maybe). The hardware is also more flexible than a GPU, but that turned out to be less important than they thought it might be.

[shaklee3]

this isn't true. the phi was extremely complex to program for, and it was not simply a port of standard x86 code. it required you to pay attention to multiple levels of memory hierarchy, just as the GPU did.