791–800 of 1001 posts
Earlier quoted context omitted.
I maintain that this was to avoid the lack of support for 32-bit games being blamed on the Apple Silicon.
There was only a 15-year transition period away from a seriously technically inferior architecture (for both performance and security.)
"Apple’s Commitment to the Environment" > Today, Apple is carbon neutral for global corporate operations, and by 2030, plans to have net-zero climate impact across the entire business, which includes manufacturing supply chains and all product life cycles. This also means that every chip Apple creates, from design to manufacturing, will be 100 percent carbon neutral. But what they won't do is put the chip in an expan…
> It's not the chip, it's the packaging that is massively unfriendly to the environment, stupid. Who are you calling stupid? If you're going to call someone or something stupid, don't do it in a stupid way.
Earlier quoted context omitted.
this is mostly wrong. The real issue has always been memory bandwidth. the highest end consumer x86 CPU has about the same memory bandwidth as a dGPU from 10 years ago. The M1 is extremely competitive with modern dGPUs, only a bit behind a 6900 XT.
>The M1 is extremely competitive with modern dGPUs, only a bit behind a 6900 XT. Do you have a source for this?
Earlier quoted context omitted.
Video playback is accelerated by essentially custom ASIC processing built into the CPU, so it's one of the most efficient things you can do now. Most development workloads are far more compute intensive.
Might be less computationally expensive. But video playback constantly refreshes screen which uses up battery
Earlier quoted context omitted.
I thought the memory was one of the more interesting bits here. My 2-year-old Intel MBP has 64 GB, and 8 GB of additional memory on the GPU. True, on the M1 Max you don't have to copy back and forth between CPU and GPU thanks to integrated memory, but the new MBP still has less total memory than my 2-year-old Intel MBP. And it seems they just barely managed to get to 64 GiB. The whole processor chip is surrounded by…
Just some genuine honest curiosity here; how many workloads actually require 64gb of ram? For instance, I'm an amateur in the music production scene, and I know that sampling heavy work flows benefit from being able to load more audio clips fully into RAM rather than streaming them from disk. But 64g seems a tad overkill even for that. I guess for me I would prefer an emphasis on speed/bandwidth rather than size, but…
I always thought it was strange that "integrated graphics" was, for years, was synonymous with "cheap, underperforming" compared to the power of a discrete GPU. 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.
Still confused how 32 core M1 Max competes with Nvidia's thousands-of-cores GPUs. Certainly there are some things that are nearly linear with core count, or otherwise they wouldn't keep adding cores, right? 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...
Earlier quoted context omitted.
The software side hasn't been there on x86 GP platforms, even though AMD tried. It's worked out better on consoles.
What software is missing? I figured the AMD G-series CPUs used the same graphics drivers and same codepaths in those drivers for the same (Vega) architecture. 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.
Prediction for Mac Pros and iMac Pros: several SoCs on the mainboard, interconnected with a new bus, 16 CPU cores for each SoC, 4 SoCs max. The on SoC RAM will act as a L4 Cache and they will share normal, User replaceable DDR5 RAM for „unified“ access.
Earlier quoted context omitted.
1. If you're a gamer, this seems comparable to a 3070 Laptop, which is comparable to a 3060 Desktop. 2. If you're a ML researcher you use CUDA (which only works on NVIDIA cards), they have basically a complete software lock unless you want to spend an undefined number of X hundreds of hours fixing and troubleshooting compatibility issues.
There has been an M1 fork of Tensorflow almost since the chip launched last year. I believe Apple did the leg work. It’s a hoop to jump through, yes, and no ones training big image models or transformers with this, but I imagine students or someone sandboxing a problem offline would benefit from the increased performance over CPU only. https://blog.tensorflow.org/2020/11/accelerating-tensorflow-...
How do they get 200/400GB per second RAM bandwidth? Isn't that like 4/8 channel DDR5. 4/8 times as fast as current Intel/AMD CPUs/APUs? (E.g. https://www.intel.com/content/www/us/en/products/sku/201837/... with 45.8GB/s) Laptop/desktop have 2 channels. High-end desktop can have 4 channels. Servers have 8 channels. How does Apple do that? I was always assuming that having that many channels is prohibitive in terms of…