Building memchunk: A High-Performance Text Chunking Library for RAG Pipelines Using SIMD and memchr
By
snyy
Fresh out the oven, still warm. Top of the tray.
Summary
The article details the development of memchunk, a high-performance text chunking library for RAG (Retrieval-Augmented Generation) pipelines. The authors started with Chonkie, a chunking library, but found it too slow when benchmarking on Wikipedia-scale datasets. This led them to explore the theoretical limits of text chunking speed by building memchunk, which uses SIMD (Single Instruction, Multiple Data) instructions and memchr for optimized performance. The article explains what chunking is in the context of LLMs and retrieval systems, and documents their journey from identifying performance bottlenecks to creating a significantly faster solution.
Key quotes
· 3 pulledthat's when things started feeling... slow. not unbearably slow, but slow enough that we started wondering: what's the theoretical limit here? how fast can text chunking actually get if we throw out all the abstractions and go straight to the metal?
this post is about that rabbit hole, and how we ended up building memchunk.
what even is chunking? if you're building anything with LLMs and retrieval, you've probably dealt with this: you have a massive pile of
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