<?xml version="1.0" encoding="utf-8" standalone="yes" ?>
<rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom">
  <channel>
    <title>GPU Memory Requirement on DASYA</title>
    <link>https://dasya.itu.dk/tags/gpu-memory-requirement/</link>
    <description>Recent content in GPU Memory Requirement on DASYA</description>
    <generator>Hugo -- gohugo.io</generator>
    <language>en-us</language>
    <copyright>© DASYA, IT University of Copenhagen</copyright>
    <lastBuildDate>Thu, 05 Jun 2025 00:00:00 +0000</lastBuildDate>
    
	<atom:link href="https://dasya.itu.dk/tags/gpu-memory-requirement/index.xml" rel="self" type="application/rss+xml" />
    
    
    <item>
      <title>GPU Memory Dataset with a focus on Transformer-Based Models</title>
      <link>https://dasya.itu.dk/for-students/proposals/archive/pito-ml-dataset/</link>
      <pubDate>Thu, 05 Jun 2025 00:00:00 +0000</pubDate>
      
      <guid>https://dasya.itu.dk/for-students/proposals/archive/pito-ml-dataset/</guid>
      <description>This project focuses on extending an existing dataset for predicting GPU memory requirements during deep learning training by incorporating transformer-based models such as BERT, GPT, and their variants. The student will study the architecture of these models and develop training scripts to run them under controlled conditions.
During training, key GPU metrics—including memory usage, utilization, and runtime characteristics—will be recorded. These observations will be used to build a richer dataset that links model specifications with their GPU resource needs.</description>
    </item>
    
  </channel>
</rss>