<?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 on Noureddine RAMDI</title><link>https://ramdi.fr/tags/gpu-memory/</link><description>Recent content in Gpu-Memory on Noureddine RAMDI</description><generator>Hugo</generator><language>en</language><lastBuildDate>Sat, 23 May 2026 20:41:27 +0000</lastBuildDate><atom:link href="https://ramdi.fr/tags/gpu-memory/index.xml" rel="self" type="application/rss+xml"/><item><title>MegaTrain: RAM-centric training architecture for 100B+ parameter LLMs on a single GPU</title><link>https://ramdi.fr/github-stars/megatrain-ram-centric-training-architecture-for-100b-parameter-llms-on-a-single-gpu/</link><pubDate>Mon, 04 May 2026 10:23:01 +0000</pubDate><guid>https://ramdi.fr/github-stars/megatrain-ram-centric-training-architecture-for-100b-parameter-llms-on-a-single-gpu/</guid><description>MegaTrain enables training 100B+ parameter LLMs on a single GPU by offloading all parameters to CPU RAM and streaming layers to GPU. Supports HuggingFace models and multi-GPU data parallelism without NCCL.</description></item></channel></rss>