Distributed training is bottlenecked by GPU-to-GPU communication, and these collectives are how the data moves. The signal is what each one does and which parallelism strategy depends on it. Here is the answer.
Updated Aug 2026 · Grounded in real Applied AI Engineer interview loops and written to a senior-engineer editorial bar.
Distributed training is bottlenecked by GPU-to-GPU communication, and these collectives are how the data moves. The signal is what each one does and which parallelism strategy depends on it. Here is the answer.
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