[RantyDave]

Are Intel just delaying the inevitable? Is it safe to say (even today) that a slow GPU will crunch big matrices faster than a fast CPU? And that's before we get to price/performance. So all that's left is the bottleneck around PCIe which, in theory, leaves the CPU with an advantage only for small datasets - which we don't really care about anyway (because they happen quickly).

Maybe the tradeoff is somewhere interesting from a latency perspective - SDR or similar. I dunno, am I barking up the wrong tree?

[pjmlp]

AVX is the surviving heritage from Larrabee, the CPU that would outtake GPGPU and so far has failed to do so.

The only thing that Intel has going for their GPUs is that as typically happens with the underdog companies, they decided to play nice with FOSS drivers and with integrated GPUs they own the low budget laptop market.

Everyone that has done any serious 3D programming is painfully aware how bad their OpenGL drivers used to be, they even used to fake OpenGL queries confirming features as supported, when they were actually implemented in software, thus making some games unusable.

That is why they started the campaign about optimizing games for Intel GPUs, and how to make best use of Graphics Profile Analyser, which ironically in the old days was DirectX only.

The bottleneck you mention is only an issue when there isn't any shared memory available, if the hardware allows for unified memory models then there is no data transfer and the GPU can work right way, naturally there are some synchronization points that need to happen still.

[teruakohatu]

In the article they quote Linus speculating that the increased core count of CPUs will achieve the same thing as AVX512 without the problems. I have read comments on HN that if cores keep increasing on CPUs they might be able to replace GPUs for some of the tasks as GPUs (or CUDA in particular) have quirks that CPUs don't have.

AVX512 in particular has issues. Using it slows down the CPU so actual wall clock benefits depends heavily on how it is used.

[panpanna]

For general purpose computing maybe. For gaming the GPUs contain special operations for texture lookup and what not that would be very expensive in a CPU.

[IAmEveryone]

This may just be too obvious for you to mention, but GPUs only work well for (massively) parallel tasks such as matrix multiplication.

Of any day's computational workload, only graphics, (parts of) ML, and maybe space heating masquerading as financial innovation are amendable to be run in such a fashion. And those workloads are, as far as I can tell, already being run on GPUs (and similar) almost universally.

So I don't think there actually are major workloads that will shift away from Intel to GPUs in the near future?

[nix23]

Yes the future is probably ARM/RiscV with many cores + GPU + some AI/ML/FPGA/Whatever co-Processor.

[m0xte]

So what Apple are doing then.

[nix23]

What the actual fastest Supercomputer (Fugaku) already did, and all the Smartphones before ;)

[TinkersW]

What are you talking about?

Fugaku is the opposite of that, each CPU chip is 48 cores with 512 bit wide SVE(arm version of AVX512).

They deliberately went for something easier to program, that didn't require doing the CPU/GPU dance.

[nix23]

ARM/RiscV with many cores...that's what i wrote, if you don't need a gpu you don't need one, if you need SVE you integrate it or use a co-Processor :)

[gnufx]

SVE isn't in a co-processor, I guess is the point. There's a lot more to Fugaku than SVE (whether or not you think that's a version of avx512), though. No DDR is suggestive.

[m0xte]

That is true :)

[jfkebwjsbx]

CPUs does not win in smaller datasets but in small computations.