chunked prefill

The gain is not a constant. It is a statistic of your output-length distribution, and the right token budget is a point on the roofline. The answer derives both, then says where the paper number and the real knee disagree.

One 32K-token prompt in front of ten short ones costs each of them more than a second of TTFT. The answer separates the half of the job length you know from the half you do not, and schedules each differently.

Chunked prefill keeps the decoders running, so the damage looks bounded. The walkthrough shows the inter-token gap climbing from 10 ms to a full second, new arrivals locked out for 8.6 seconds, and a slowdown that outlives the prefill.

Eight tiles too many turns a one-wave GEMM into two. The answer prices the waste in microseconds for a real prefill shape, then compares the three fixes, including the one that lives in the scheduler, not the kernel.

Users see the first token quickly and then the stream stutters. The answer builds the decode step from bytes, shows which cause produces a bimodal latency histogram, and names the one metric that tells the top two apart.

A regular period is a clue most candidates throw away. The answer turns it into a ranked list of periodic sources, shows why a few slow steps out of hundreds own the p99, and names the one correlation that separates the top two.

A scheduler is a loop over three queues and a budget. The answer gets the order of those loops right, shows what the budget costs in milliseconds of TPOT, and tests the invariants a grader will check.