<story><title>Building unorthodox deep learning GPU machines</title><url>https://www.kyleboddy.com/2024/01/28/building-deep-learning-machines-unorthodox-gpus/</url></story><parent_chain></parent_chain><comment><author>kookamamie</author><text>Do note that, due to NVidia&amp;#x27;s absurd EULAs, you cannot run RTX 3090 in a data-center for compute purposes (&lt;a href=&quot;https:&amp;#x2F;&amp;#x2F;www.nvidia.com&amp;#x2F;content&amp;#x2F;DriverDownloads&amp;#x2F;licence.php?lang=us&amp;amp;type=GeForce&quot; rel=&quot;nofollow&quot;&gt;https:&amp;#x2F;&amp;#x2F;www.nvidia.com&amp;#x2F;content&amp;#x2F;DriverDownloads&amp;#x2F;licence.php?l...&lt;/a&gt;).&lt;p&gt;Should you care about the EULA? Not really, until you&amp;#x27;re a business of any significant scale.</text></comment>
<story><title>Building unorthodox deep learning GPU machines</title><url>https://www.kyleboddy.com/2024/01/28/building-deep-learning-machines-unorthodox-gpus/</url></story><parent_chain></parent_chain><comment><author>verditelabs</author><text>I think I recognize the author of this from &amp;#x2F;r&amp;#x2F;localllama, where plenty of other people are building similar frankenstein rigs. This post only mentions Intel setups, but AMD Epyc Milan and Rome based rigs are also very viable alternatives. They&amp;#x27;re a bit more expensive, but much better perf&amp;#x2F;watt, and the incremental price increase after factoring in a lot of GPUs is fairly slim. With 7 PCIE bifurcators on a motherboard such as the AsRock ROMED8-2T and a 14 risers, you can get up to 14 GPUs at PCIE 4.0x8.</text></comment>