That’s the core point though. If you do batches the cache and registers are already primed and ready. The model runs in steps/layers accessing different weights in VRAM along the way. When batching you take advantage of this.
I’m in agreement that RAM to VRAM is important too but I feel the key speed up for inference batching is my above point.
Obviously yes but NVIDIA Ampere/Hopper architecture has 64k 32-bit registers per SM. A100 has 108 SMs and H100 has 132 SMs so go figure - registers aren't a bottleneck.
That’s the core point though. If you do batches the cache and registers are already primed and ready. The model runs in steps/layers accessing different weights in VRAM along the way. When batching you take advantage of this.
I’m in agreement that RAM to VRAM is important too but I feel the key speed up for inference batching is my above point.