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Your activations for one long sequence no longer fit on a GPU. Explain context parallelism and ring attention.

Data, tensor, and pipeline parallelism all leave one sequence's activations on one device, so 200k+ token training hits a wall none of them can fix. The fourth axis shards the sequence itself, and the interview lives in the communication math.

Updated Aug 2026 · Grounded in real Applied AI Engineer interview loops and written to a senior-engineer editorial bar.

Data, tensor, and pipeline parallelism all leave one sequence's activations on one device, so 200k+ token training hits a wall none of them can fix. The fourth axis shards the sequence itself, and the interview lives in the communication math.

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