<feed xmlns="http://www.w3.org/2005/Atom"> <id>https://datta0.github.io/</id><title>Datta's Blog</title><subtitle>A minimal, responsive and feature-rich Jekyll Chirpy theme for technical writing.</subtitle> <updated>2026-04-14T11:24:48+05:30</updated> <author> <name>Datta Nimmaturi</name> <uri>https://datta0.github.io/</uri> </author><link rel="self" type="application/atom+xml" href="https://datta0.github.io/feed.xml"/><link rel="alternate" type="text/html" hreflang="en" href="https://datta0.github.io/"/> <generator uri="https://jekyllrb.com/" version="4.4.1">Jekyll</generator> <rights> © 2026 Datta Nimmaturi </rights> <icon>/assets/img/favicons/favicon.ico</icon> <logo>/assets/img/favicons/favicon-96x96.png</logo> <entry><title>The MathemaTricks behind FlashAttention</title><link href="https://datta0.github.io/posts/flash-attention/" rel="alternate" type="text/html" title="The MathemaTricks behind FlashAttention" /><published>2026-04-12T14:30:00+05:30</published> <updated>2026-04-14T11:24:23+05:30</updated> <id>https://datta0.github.io/posts/flash-attention/</id> <content type="text/html" src="https://datta0.github.io/posts/flash-attention/" /> <author> <name>datta0</name> </author> <category term="Transformer" /> <category term="Attention" /> <category term="GPU" /> <category term="Kernels" /> <category term="Training" /> <category term="Finetuning" /> <category term="Math" /> <summary>Fast and memory efficient exact attention</summary> </entry> <entry><title>The lore behind LoRA</title><link href="https://datta0.github.io/posts/the-lore-behind-lora/" rel="alternate" type="text/html" title="The lore behind LoRA" /><published>2026-03-23T14:30:00+05:30</published> <updated>2026-04-13T12:40:34+05:30</updated> <id>https://datta0.github.io/posts/the-lore-behind-lora/</id> <content type="text/html" src="https://datta0.github.io/posts/the-lore-behind-lora/" /> <author> <name>datta0</name> </author> <category term="LoRA" /> <category term="Transformer" /> <category term="Training" /> <category term="Finetuning" /> <category term="Math" /> <summary>LoRA imagined from the ground up</summary> </entry> <entry><title>Exploring the Mixture of Experts</title><link href="https://datta0.github.io/posts/exploring-the-moe/" rel="alternate" type="text/html" title="Exploring the Mixture of Experts" /><published>2026-02-24T14:30:00+05:30</published> <updated>2026-04-13T12:40:34+05:30</updated> <id>https://datta0.github.io/posts/exploring-the-moe/</id> <content type="text/html" src="https://datta0.github.io/posts/exploring-the-moe/" /> <author> <name>datta0</name> </author> <category term="Mixture of Experts" /> <category term="Transformer" /> <category term="FFNN" /> <category term="Math" /> <summary>An intuitive build up to Mixture of Experts</summary> </entry> <entry><title>Understanding multi GPU Parallelism paradigms</title><link href="https://datta0.github.io/posts/understanding-multi-gpu-parallelism-paradigms/" rel="alternate" type="text/html" title="Understanding multi GPU Parallelism paradigms" /><published>2025-07-06T16:33:31+05:30</published> <updated>2026-02-24T21:37:53+05:30</updated> <id>https://datta0.github.io/posts/understanding-multi-gpu-parallelism-paradigms/</id> <content type="text/html" src="https://datta0.github.io/posts/understanding-multi-gpu-parallelism-paradigms/" /> <author> <name>datta0</name> </author> <category term="Attention" /> <category term="Transformer" /> <category term="FFNN" /> <category term="GPU" /> <category term="Parallelism" /> <category term="vLLM" /> <category term="Inference" /> <summary>We’ve been talking about Transformers all this while. But how do we get the most out of our hardware? There are two different paradigms that we can talk about here. One case where your model happily fits on one GPU but you have many GPUs at your disposal and you want to save time by distributing the workload across multiple GPUs. Another case is where your workload doesn’t even fit entirely on ...</summary> </entry> <entry><title>Attention and Transformer Imagined</title><link href="https://datta0.github.io/posts/transformer-imagined/" rel="alternate" type="text/html" title="Attention and Transformer Imagined" /><published>2025-06-14T14:30:00+05:30</published> <updated>2025-06-15T20:19:27+05:30</updated> <id>https://datta0.github.io/posts/transformer-imagined/</id> <content type="text/html" src="https://datta0.github.io/posts/transformer-imagined/" /> <author> <name>datta0</name> </author> <category term="Attention" /> <category term="Transformer" /> <category term="FFNN" /> <category term="Math" /> <summary>An intuitive build up to Attention and Transformer</summary> </entry> </feed>
