Re:M2 Ultra can run 128 streams of Llama 2 7B in parallel
by cyber_kinetist on Wednesday October 11, 2023 @10:12PM
(#37852725)
What Apple Silicon brings to the table is not simply just performance, but a large amount of unified memory that can be used by the GPU (which are needed for inference of large deep neural networks like LLMs).
A top-of-the-line Mac Studio will give you 192 GB of unified RAM in less than $7000. Meanwhile a H100 from NVIDIA with 80 GB of VRAM will cost you like $30000...
Re:M2 Ultra can run 128 streams of Llama 2 7B in parallel
by api on Thursday October 12, 2023 @09:21AM
(#37856787)
If the software were a little better Apple Silicon would be by far the best rig for DIY LLM research or training.
192GiB RAM is enough to train or inference Falcon 180B in RAM at 8-bit resolution.
The Apple Silicon is great at really low power work, but if you dial desktop or server GPU power limits down they also become quite efficient. The marginal cost of electricity is cheaper than buying more hardware, so nVidia and others run their parts deep into the diminishing returns part of the curve to maximize performance at the expense of power efficiency.