Distributed training is bottlenecked by GPU-to-GPU communication, and these collectives are how the data travels. The signal is what each one does and which parallelism strategy relies on it. Here is the answer.
Updated Sep 2026 · Grounded in real GenAI, LLM, and AI/ML engineering 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 travels. The signal is what each one does and which parallelism strategy relies on it. Here is the answer.
No comments yet — be the first to share your approach.
