How LLMs Reach 1 Million Token Context Windows — Context Parallelism and Ring Attention

Large language models have grown from 4,000-token context windows to 10 million tokens, but hardware memory can't keep up. Context parallelism solves this by splitting sequences across multiple GPUs, while Ring Attention organizes processors in a circle where each GPU passes data to the next while computing simultaneously. Zig-Zag Ring Attention improves this by distributing tokens in an interleaved pattern rather than sequential chunks, ensuring balanced workloads and enabling million-token processing across data centers.