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    <title>gpu on David An</title>
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    <description>Recent content in gpu on David An</description>
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      <title>Local-first GPU Cluster with nvkind and Time Splitting</title>
      <link>https://davidan.dev/posts/nvkind/</link>
      <pubDate>Sun, 14 Dec 2025 00:00:00 +0000</pubDate>
      
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      <description>You have a brand new shiny GPU and want to start experimenting with it by running some sample experiments in Kubernetes, but how would you start that. In this short tutorial, we go over how to use nvkind, the gpu-operator to start running some basic experiemtns using your new GPU. We assume that the reader already has things such as Docker, golang, and relevant drivers/systems (nvidia-ctk, nvidia-smi, etc.) installed too.</description>
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      <title>A Dive into GPU Math</title>
      <link>https://davidan.dev/posts/gpumath/</link>
      <pubDate>Wed, 15 Oct 2025 00:00:00 +0000</pubDate>
      
      <guid>https://davidan.dev/posts/gpumath/</guid>
      <description>You ever wonder what goes on when you ask ChatGPT a question and how that is served? Or what people mean when by using a A100 to train a model and the time it takes? Or even considering the levels of abstraction between the model and the hardware? This article will aim to bring light to many of the concepts related to GPUs and the math behind them.
We assume that the reader has a basic understanding of how recent LLM technologies work.</description>
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