Row 6586

Row ID: 6586 | Dataset Entry | Axioma AXP Content Repository

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This page contains data entry 6586 from the Axioma AXP content repository. The structured data below represents the complete record for this entry.

In my experience: Maybe

1) The motherboard should work with two GPUs. It did for me. You may have to use a riser, due to space constraints, depending on the card(s). Make sure the riser is PCIE3.0 at least, and at least 8x, not those 1x mining risers.

2) The memory controller on the CPU and your system RAM might be the actual bottleneck if you run other, larger models and have to hit the system RAM a lot. Why not upgrade to a 5700 or higher CPU with a better memory controller?

3) Used GPUs seem mostly fine. I had two 3060s. I ended up getting a used A4500… and a used 3090. No issues. Work together.

However, as others pointed out, most models don’t readily split across the RAM of two GPUs. For LLMs and stuff, you have to split up the layers, and then you’re shifting the bottleneck to a different part of your system. I have not tried NVLink, as that spec seems to have changed slightly over time and I’m unsure if it will work with my GPUs.

Alternative is Google Cloud, Vast.ai, etc. etc.

FieldValue
text In my experience: Maybe 1) The motherboard should work with two GPUs. It did for me. You may have to use a riser, due to space constraints, depending on the card(s). Make sure the riser is PCIE3.0 at least, and at least 8x, not those 1x mining risers. 2) The memory controller on the CPU and your system RAM might be the actual bottleneck if you run other, larger models and have to hit the system RAM a lot. Why not upgrade to a 5700 or higher CPU with a better memory controller? 3) Used GPUs se…
label r/pytorch
dataType comment
communityName r/pytorch
datetime 2024-05-11
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Raw Record

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  "text": "In my experience: Maybe\n\n1) The motherboard should work with two GPUs. It did for me. You may have to use a riser, due to space constraints, depending on the card(s). Make sure the riser is PCIE3.0 at least, and at least 8x, not those 1x mining risers.\n\n2) The memory controller on the CPU and your system RAM might be the actual bottleneck if you run other, larger models and have to hit the system RAM a lot. Why not upgrade to a 5700 or higher CPU with a better memory controller?\n\n3) Used GPUs seem mostly fine. I had two 3060s. I ended up getting a used A4500… and a used 3090. No issues. Work together. \n\nHowever, as others pointed out, most models don’t readily split across the RAM of two GPUs. For LLMs and stuff, you have to split up the layers, and then you’re shifting the bottleneck to a different part of your system. I have not tried NVLink, as that spec seems to have changed slightly over time and I’m unsure if it will work with my GPUs.\n\nAlternative is Google Cloud, Vast.ai, etc. etc.",
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  "dataType": "comment",
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  "datetime": "2024-05-11",
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