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Ring Attention From Scratch

Pass the keys around the circle until every GPU has seen the whole sequence.

Key Insight​

This project implements ring attention across 4 GPUs and measures how efficiently it scales at a 64k-token context. Each GPU holds one slice of the sequence (context parallelism). Because a single GPU doesn't have enough memory (VRAM) to hold all the keys and values at once for such a massive text, it passes its keys and values to its neighbor around a ring, round after round, until every slice has attended to every other slice — building the full KV cache no single GPU could hold alone.

Why This Matters​

Very long contexts (100k–1M tokens) create a KV cache far too large for one device, so the sequence must be split across many. Ring attention is the standard way to compute attention over that split sequence with overlapping communication, and building it by hand shows exactly where the scaling efficiency is won or lost.