Does anyone have experience with using a machine for training Deep Learning models (R-CNNs for semantic segmentation), using multiple GPUs and powering it with more that one PSU? E.g. one PSU for motherboard and one GPU only, and another PSU for a second (and more?) GPU connected to the same motherboard.

  • 1
    This is certainly possible. Are you looking for something professional like what you'd find in a rendering server, or something "hacky" that could be done with normal desktop PSUs?
    – Romen
    Sep 22 at 18:05
  • I will definitely start with something hacky! I may even go for an "open box", just a frame without enclosing walls.
    – Fabio
    Sep 25 at 10:02

1 Answer 1


for consumer home pc style ATX power supplies, you would not use more than one to a motherboard. They have the 24-pin ATX motherboard connector, for connecting to only one motherboard. If this is the kind of rig you are looking to do multiple gpu's you simply buy a 1000w or 1200w psu that supplies 4 pcie 6 or 8 pin power connectors for gpu's.

There is the enterprise route that uses rack mount type chassis and rack mount power supplies. For example a Dell R940xa, 4U in height, has 4 x 1600w power supplies; it runs on 208/240v power. They along with Supermicro you can peruse their websites to look at their offerings to get an idea of how it's done, where they can support I think up to 10 nvidia-V100 type gpgpu's (double width, like a consumer grade RTX3090, having 1x or 2x 6 or 8 pin power connectors per card)

a home built pc, using a full size tower with an ATX or extended ATX size motherboard, will accomodate 2 typical RTX-3090 cards, you just need a common ATX power supply in the 800w plus range that will provide the necessary pcie power cables to the graphics card(s). you would never use 2 psu's on one motherboard for a home pc type rig, you would get one PSU providing enough power for the hardware to be used.

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