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Except that my fairly modest upper midrange desktop has ~1.2TB/sec of memory bandwidth... Cause, I just added the GPU and system RAM bandwidth numbers together

Except that my fairly modest upper midrange desktop has ~1.2TB/sec of memory bandwidth... Cause, I just added the GPU and system RAM bandwidth numbers together. Which is what needs to be kept in mind with much of this. Yes that is a lot of memory bandwidth and its hella useful for some subset of users, but its shared, and largely pointless for a lot of CPU bound tasks. But OTOH, may not be enough for many GPU bound ones. It also assumes that pretty much every other CPU manufacture on the planet are idiots for optimizing for latency and putting in large caches to compensate (aka the desktop parts from AMD/intel have only _two_ channels, vs the 8+ in the server/workstation parts) and price discriminating for the parts that have more CPU bandwidth. AKA, you can get amd machines in the same ballpark (or possibly faster depending on how fast you can get 24 channels of DDR5 to run). So, I'm not saying which is better because its likely workload dependent, but to claim its a blanket insurmountable advantage is questionable. Particularly since the price ranges we are talking about a similar machine is probably a 64 core threadripper plus a fat nvidia GPU or four and the shear core count and raw GPU compute is probably a win in most workloads.

USB5 3y ago
I just built a workstation with a 32 core Threadripper Pro, 128 GB ECC RAM, Thunderbolt 4, and an RTX 4090 for $6,500.
- sliken 3y ago
  Likely better on any workloads that are GPU heavy and fit in 24GB of vram. Two data points from Apple: a) M2 Ultra 24 cores, 128GB ram, 2TB storage = $5,200 b) M2 ultra 24 cores, 192GB ram, 4GB storage = $6,600 Likely 1/4th the size, 1/4th the power consumption, and 4x the ram bandwidth. Have you by chance played with any LLMs? Just saw a post that someone managed 5 tokens/sec with the llama 65B model.
  - USB5 3y ago
    I don't care about playing with LLMs, so this is simply meaningless to me.
    - kamranjon 3y ago
      But for many people training or running inference on large models is important and the apple approach actually makes that feasible in a desktop solution which is pretty awesome.
  - deleted 3y ago
    [deleted]
sliken 3y ago
Sure, but what if a normal C code needs more bandwidth? Or if a GPU code needs more than 12-16GB of memory (normal cards) or 24GB (if you get a 4090)? What I like about the apple approach is that low end laptops/desktops get 100GB/sec. Pay another $500 get 200GB/sec. Pay another $500 get 400GB/sec. Pay another $1000 get 800GB/sec and still fits in a small desktop. On the PC side with AMD/Intel you get the same memory bandwidth for the low, medium, and high end chips. Until you upgrade to a threadripper, which is a 280 watt chip, on an expensive motherboard, usually in a rather large PC case and makes the mac studio look cheap.
- deleted 3y ago
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- kcb 3y ago
  > Sure, but what if a normal C code needs more bandwidth? https://www.anandtech.com/show/17024/apple-m1-max-performance-review/2 https://www.anandtech.com/show/17024/apple-m1-max-performanc...
  - wtallis 3y ago
    Putting things in context, the 3-thread measured memory bandwidth measured there on the M1 Max is approximately equal to the maximum theoretical memory bandwidth available across all channels and chiplets of a current Ryzen Threadripper PRO. If the M1 Ultra doubles the achievable memory bandwidth by virtue of having twice as many CPU clusters, then an 8-thread test should still be able to match AMD's latest EPYC processors with 12-channel DDR5. (I don't know how well AMD's current processors do with utilizing the socket's full DRAM bandwidth from a limited number of chiplets, but I wouldn't be surprised if it's a more severe limitation than what M1 Max/Ultra show with their CPU clusters. It looks like only the 12-chiplet EPYC processors actually use all the links from the IO die to the CPU chiplets.) So the inability to use all the DRAM bandwidth from the CPU cores, while perhaps disappointing, isn't exactly a weakness for Apple's processors compared to the competition.
    - sliken 3y ago

USB5 3y ago

I just built a workstation with a 32 core Threadripper Pro, 128 GB ECC RAM, Thunderbolt 4, and an RTX 4090 for $6,500.

sliken 3y ago
Likely better on any workloads that are GPU heavy and fit in 24GB of vram. Two data points from Apple: a) M2 Ultra 24 cores, 128GB ram, 2TB storage = $5,200 b) M2 ultra 24 cores, 192GB ram, 4GB storage = $6,600 Likely 1/4th the size, 1/4th the power consumption, and 4x the ram bandwidth. Have you by chance played with any LLMs? Just saw a post that someone managed 5 tokens/sec with the llama 65B model.
- USB5 3y ago
  I don't care about playing with LLMs, so this is simply meaningless to me.
  - kamranjon 3y ago
    But for many people training or running inference on large models is important and the apple approach actually makes that feasible in a desktop solution which is pretty awesome.
- deleted 3y ago
  [deleted]

sliken 3y ago

Sure, but what if a normal C code needs more bandwidth? Or if a GPU code needs more than 12-16GB of memory (normal cards) or 24GB (if you get a 4090)? What I like about the apple approach is that low end laptops/desktops get 100GB/sec. Pay another $500 get 200GB/sec. Pay another $500 get 400GB/sec. Pay another $1000 get 800GB/sec and still fits in a small desktop. On the PC side with AMD/Intel you get the same memory bandwidth for the low, medium, and high end chips. Until you upgrade to a threadripper, which is a 280 watt chip, on an expensive motherboard, usually in a rather large PC case and makes the mac studio look cheap.

deleted 3y ago
[deleted]
kcb 3y ago
> Sure, but what if a normal C code needs more bandwidth? https://www.anandtech.com/show/17024/apple-m1-max-performance-review/2 https://www.anandtech.com/show/17024/apple-m1-max-performanc...
- wtallis 3y ago
  Putting things in context, the 3-thread measured memory bandwidth measured there on the M1 Max is approximately equal to the maximum theoretical memory bandwidth available across all channels and chiplets of a current Ryzen Threadripper PRO. If the M1 Ultra doubles the achievable memory bandwidth by virtue of having twice as many CPU clusters, then an 8-thread test should still be able to match AMD's latest EPYC processors with 12-channel DDR5. (I don't know how well AMD's current processors do with utilizing the socket's full DRAM bandwidth from a limited number of chiplets, but I wouldn't be surprised if it's a more severe limitation than what M1 Max/Ultra show with their CPU clusters. It looks like only the 12-chiplet EPYC processors actually use all the links from the IO die to the CPU chiplets.) So the inability to use all the DRAM bandwidth from the CPU cores, while perhaps disappointing, isn't exactly a weakness for Apple's processors compared to the competition.
  - sliken 3y ago