4 ms·
His key point is that AI workloads will switch to CPU as training becomes a smaller portion of the pie. If this is true then Nvidia is not the market leader, be
by HDThoreaun 3y ago
His key point is that AI workloads will switch to CPU as training becomes a smaller portion of the pie. If this is true then Nvidia is not the market leader, because their CPU offerings are non existent.
- rhdunn 3y agoFor ML/neural networks, the vector/matrix/tensor acceleration is still valuable. Thus, running them on GPUs or specialist hardware will make them faster to complete -- such as generating images from stable diffusion. GPUs are also currently best suited to this due to being able to parallelize the calculations across the CUDA and specialist tensor cores. The other issue is the memory needed to run the models. NVidia's NVLink is useful for this to share memory in a combined space across the GPUs.