Beyond basic gradient checkpointing, how do you choose selective activation recomputation to maximize MFU?
Full activation checkpointing saves memory but costs a flat 30% extra compute. Selective recomputation wins most of that back by recomputing only the cheap, memory-heavy operations. Here is how to pick what to recompute.
Updated Sep 2026 · Grounded in real GenAI, LLM, and AI/ML engineering interview loops and written to a senior-engineer editorial bar.
Full activation checkpointing saves memory but costs a flat 30% extra compute. Selective recomputation wins most of that back by recomputing only the cheap, memory-heavy operations. Here is how to pick what to recompute.
Lead with where the obvious approach breaks, because that is the judgment they are screening for — most candidates jump straight to the happy path and lose the room.
Then walk the failure back through the pipeline in order, naming the one metric the customer's exec sponsor actually cares about before you propose the fix.
