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Comment by coobird | Hacker News Reader

Less than a couple months ago, Intel seemed to be very enthusiastic and showcasing a bunch of testimonials from partners:

https://riscv.org/blog/2022/12/intel-pathfinder-for-risc-v-n...

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Nothing new here, I was at Intel's talk in GDCE 2009 about how Larrabee was going to change the world of graphics programming.

See also Edison, StrongARM,...

I get the feeling internally Intel is following the unfortunately popular paradigms and ideas that Agile (note the capital A instead of lower) enables.

Commitments to work without anyone asking for it

When someone does ask for work, the requirements go through N number of middle management layers blurring them every step of the way like Chinese Whispers

Projects must continue even when it is clear it's going to be a failure because the people running it haven't heard of the phrase "sunk cost fallacy"

Of the few genuinely good ideas that are produced, they are again strangled by incompetent middle management who are only interested on working on a project to get their next promotion and then quickly "moving on" (abandoning it) when they do get promoted (this seems to be one of the largest complaints from insiders at Google)

See the history of ISPC, and how it was rescued, it touches on some of those points.

https://pharr.org/matt/blog/2018/04/18/ispc-origins

> So there was #pragma simd, which sort of worked, unless you called an external function; that problem never got solved. They never understood why someone would want to write a large system that ran completely using all of the vector lanes and couldn’t imagine it was an important use case. (The attentive reader may realize that this execution model precisely describes GPUs.)

Fuck, that must have been an infuriating experience dealing with the hardware team.

Canceling Larrabee was such a stupid looking decision in hindsight, given CUDA and ARC.

IIRC, Larrabee eventually morphed into the Phi accelerators (knights mill, bridge, etc.). They hung out in the market for a while, and I think the last iteration was shifted to be more deep learning focused, but I don't think they ever got much traction.

I agree, it's unfortunate - I'd love it if someone could challenge NVidia's dominance of ML at least a bit.

Honestly, the Xeon Phi wasn't a bad decision if you wanted to challenge NVidia/CUDA. Giving people a "normal" platform like that could have worked if they had pushed the software ecosystem around it and kept up on performance.

A late reply, but I totally agree. Phi was a super interesting platform, and they probably could've done more with it if they'd invested in the software (and hardware).

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