<?xml version="1.0" encoding="utf-8" standalone="yes"?>
<rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom">
  <channel>
    <title>Project on Hullabalooing</title>
    <link>https://cruver.ai/tags/project/</link>
    <description>Recent content in Project on Hullabalooing</description>
    <generator>Hugo</generator>
    <language>en</language>
    <lastBuildDate>Mon, 02 Mar 2026 00:00:00 -0700</lastBuildDate>
    <atom:link href="https://cruver.ai/tags/project/index.xml" rel="self" type="application/rss+xml" />
    <item>
      <title>GPU/AI</title>
      <link>https://cruver.ai/gpu-ai/</link>
      <pubDate>Mon, 02 Mar 2026 00:00:00 -0700</pubDate>
      <guid>https://cruver.ai/gpu-ai/</guid>
      <description>&lt;p&gt;Running local AI inference on AMD Instinct MI60 GPUs - a budget-friendly path to 70B parameter models at home.&lt;/p&gt;&#xA;&lt;h2 id=&#34;overview&#34;&gt;Overview&lt;a class=&#34;anchor&#34; href=&#34;#overview&#34;&gt;#&lt;/a&gt;&lt;/h2&gt;&#xA;&lt;p&gt;The AMD Instinct MI60 is a datacenter GPU from 2018 that remains surprisingly capable for local AI workloads. With 32GB of HBM2 memory per card, a dual-MI60 setup provides 64GB of VRAM, enough to run 70B parameter models with quantization.&lt;/p&gt;&#xA;&lt;p&gt;This section documents my setup: hardware modifications for cooling, software configuration for ROCm and vLLM, and the workflows that make it practical for daily use.&lt;/p&gt;</description>
    </item>
  </channel>
</rss>
