Communication is hidden only when readiness and shared resources allow it

During data-parallel backward execution, different gradient groups become ready at different times. A reduction cannot safely consume a group before its required contributions exist. Framework bucketing trades earlier readiness against per-collective launch and transfer costs: a large bucket may wait longer, while many small buckets can create substantial overhead. Collective ordering across ranks is another correctness constraint. A configured asynchronous path does not permit arbitrary reordering or early use of an unfinished reduced gradient by the optimizer.

Start with a timeline that marks the first valid launch of each communication operation, the compute that is independent of it, and the consumer that requires its completion. The final communication tail can dominate even if earlier buckets overlap well. An apparent empty region on one rank might reflect another rank's late readiness rather than a slow link. Correlate the same collective and relevant ranks before calling the entire interval network transfer. Readiness, transport progress, and completion waits are different components of the observed schedule.

If independent compute and communication begin together, run at fixed durations, and can progress concurrently without interference, their joint duration is the larger of the two. This is the ideal fully overlapped case. It is not valid when communication begins near the end of compute, when a stream wait serializes the operations, or when either duration grows under contention. An isolated collective benchmark and an isolated matrix kernel do not establish their durations when both run simultaneously on the training device.

Measure concurrent durations and compare completed steps with and without the proposed overlap path. A shorter exposed tail can be offset by slower compute if communication consumes execution or memory resources. Likewise, a collective can report a longer duration while the whole step becomes faster because more of that duration is hidden. Avoid optimizing a percentage of overlapped trace area independently of end-to-end time. Preserve the same collective semantics and valid gradient updates so the comparison measures scheduling rather than a changed training algorithm.

Change one bucket or overlap setting at a time and record readiness, launch, compute completion, collective completion, and final update. Compare multiple warm completed windows rather than one trace. Keep topology, rank placement, message sizes, accumulation, and input work fixed. If a setting improves only an isolated collective, test whether its launch schedule still fits the actual backward path. A valid explanation should identify which exposed interval disappeared, what new contention appeared, and why the end-to-end result follows under the observed dependencies.

The roofline lab makes one resource ceiling explicit but contains no collective. Reset, set both I=8 FLOP/byte and B=100 decimal GB/s, predict 800 GFLOP/s, then Play. Reset and set both I=16 and B=100 to predict the fixed 1000 GFLOP/s compute roof. Its memory bandwidth is a synthetic device-memory parameter, not network bandwidth; playback changes neither control. The activity reminds us that a shared resource can limit progress, but it cannot simulate overlapping kernels, rank readiness, transport, or the slowdown caused by running communication beside compute.