I never could see any fundamental reason why "integrated" should mean "underpowered." Apple is turning things around, and is touting the benefits of high-performance integrated graphics.
I never could see any fundamental reason why "integrated" should mean "underpowered." Apple is turning things around, and is touting the benefits of high-performance integrated graphics.
Sure. It'd be tough to be the top performing chip in the market, but you can get pretty close.
Not really wrong. Memory bandwidth is only a limitation for a very narrow subset of problems.
I've gone back and forth between server-grade AMD hardware with 4-channel and 8-channel DDR4 and consumer-grade hardware with 2-channel DDR4. For most of my work (compiling, mostly) the extra memory bandwidth didn't make any difference. The consumer parts are actually faster for compilation because they have a higher turbo speed, despite having only a fraction of the memory bandwidth.
Memory bandwidth does limit certain classes of problems, but we mostly run those on GPUs anyway. Remember, the M1 Max memory bandwidth isn't just for the CPU. It's combined bandwidth for the GPU and CPU.
It will be interesting to see how much of that memory can be allocated to a M1 Max. It might be the most accessible way to get a lot of high-bandwidth RAM attached to a GPU for a while.
Your compute anecdotes have no bearing on (i)GPU bottlenecks.
Do you have a source for this?
So the M1 Max is not as fast as a high end desktop GPU. Still, it is incredible that you are getting a GPU that performs slightly less than a last generation 2080 desktop GPU at just 50-60 watts.
There was always one reason: limited memory bandwidth. You simply couldn't cram enough pins and traces for all the processor io plus a memory bus wide enough to feed a powerful GPU. (at least not in a reasonable price)
Edit: Found answer here. GPU core is not the same thing as a CUDA core. https://www.reddit.com/r/hardware/comments/73i3ne/why_do_app...
NVIDIA defines any SIMD lane to be a core. They recently have gotten more creative with definition, they were able to double FP32 executions per unit (versus previous gen) and hence in marketing materials, doubled the number of "CUDA cores".
But no, I don't think they did.
My impression was that it was still the hardware holding things back: Everything but the latest desktop CPUs still using the older Vega architecture. And even those latest desktop CPUs are essentially PS5 chips that got binned out.
In the wider picture, gpu compute in general on PC also failed to become mainstream enough to sway consumer choices. Development experience for GPUs is still crap vs the cpu, the languages are mostly bad, there's massive sw platform fragmentation among os vendors and gpu vendors, driver bugs causing OS crashes left and right, etc.
Re your impression, yes, AMD shifted focus more toward cpu from gpu in their SoCs after a while when their initiatives failed to take off outside consoles. But it's been an ok place to be, just keeping the gpu somewhat ahead of Intel competition and getting some good successes in the cpu side.