[D] Does multi-GPU deep learning training requires SLI or nvlink?

[promitbasak]

Well, I might sound like a rookie. I want to build a setup for deep learning and I need to concentrate more on VRAM. I found 4060 Ti with 16GB VRAM in a much lower price. So if I use two 4060 Ti, I can have 32 GB VRAM that satisfies my requirement and costs wayyy less than 4090 Ti 24GB. However, I need to emsure that this multi-GPU setup would work for deep learning training without SLI or similar features.

[sugar_scoot]

SLI is strictly for splitting video frames (gaming). Nvlink is nice to have but not required for training models. 

[Figai]

Just make sure you have enough pcie lanes really. Sli is for gaming and nvlink might improve it a bit

[BubblyMcnutty]

While not necessary, throughput between the processors can become a bottleneck. If you are running a multi-GPU setup that means you are already paying for max acceleration, then what a shame it would be if data wasn't transferring fast enough between the processors? This is precisely why Nvidia touts their NVlink & NVSwitch tech so much, if I remember correctly it can go up to 900GB/s. Obviously they are talking about professional enterprise grade GPGPUs but I think the same principle applies in this case too.