When a model is too large for one GPU you split the model itself, not just the data. The signal is telling tensor parallelism (split within a layer) apart from pipeline parallelism (split across layers) and matching each to the interconnect. 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.
When a model is too large for one GPU you split the model itself, not just the data. The signal is telling tensor parallelism (split within a layer) apart from pipeline parallelism (split across layers) and matching each to the interconnect. Here is the answer.
No comments yet — be the first to share your approach.
