The design for the deep learning server would be very similar to that of a mining rig, specifically using risers to stack as many GPU's onto the motherboard. The design is as follows:
CPU: AMD EPYC Rome 7302P
-128 Lanes PCIe 4.0
Mobo: AsRock Rack ROMED8-2T
-Supports 7 x PCIe 4.0 x16
GPUs can be any model
FIRST: Is it safe to say we can run 7 GPU's (max on mobo) and utilize ALL of them at max capacity? Are there any bottlenecks concerning the hardware?
7 gpus * x16 pcie speeds = 112 lanes
My question stems from a purely hardware design standpoint, and if there are any limitations to this design. I'm trying to maximize the GPU's without resorting to building more servers, using 10GB networking equipment. I know there are dual-socket server boards that can do 4 GPUs each, but not what I'm after.
SECOND: If I run the GPU's at a slower speed, say pcie x8, can we double the amount of GPU's theoretically, provided a motherboard had enough pcie x8 slots (x8 to x16 converter used)?
