collectives

Two phases, n minus one steps each, one slice per step: the derivation that gives 2(n−1)/n times the buffer per rank, the argument that no algorithm can beat it on bytes, and the latency term that makes NCCL switch to trees at scale.

Before the first byte moves, the library has already discovered the machine's topology, built rings and trees over it, split the work into parallel channels and chosen a wire protocol by message size. What each of those four decisions is for, and the environment variables that let you see and override them.

Four operations cover almost everything a distributed training step sends. What each one does to the data, the bytes each rank moves for a message of size S across N ranks, and which parallelism strategy generates which, worked through for a 70B model so the numbers are concrete rather than symbolic.

A hang is a collective that one rank never entered, and finding it means asking which rank is missing rather than what is broken. The flight recorder that answers that in seconds, what to do when it is not enabled, and the four causes that a missing rank turns out to be.

Each rank keeps a ring buffer of its recent collectives, and on a timeout every rank dumps it. Comparing sequence numbers across a thousand of those buffers finds the missing participant in one pass, and the three patterns those comparisons produce point at three different causes.

Two phases of N-1 steps each, a chunk index that rotates with the step, and a byte count that should come out to exactly the textbook formula. The implementation, the verification against a direct sum, and the measured traffic matching 2(N-1)/N times the message at every rank count tested.

Full GPU utilization during a hang is the clue, because a spinning collective looks identical to real work. The isolation order that finds the mismatched rank in minutes, a runnable reproducer that hangs on demand, and the fix that gates the logging rather than the collective.