Engineering / advanced
Schedule a model pipeline
Analyze microbatches, activation lifetimes, weight versions, and communication schedules to quantify pipeline efficiency and correctness.
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Module 01 advanced
Schedule a model pipeline
Analyze microbatches, activation lifetimes, weight versions, and communication schedules to quantify pipeline efficiency and correctness.
- 01
Pipeline stages and partition costs
Partition execution with explicit compute, boundary traffic, memory, and backward dependencies rather than equal layer counts.
28 min - 02
Fill-drain schedules and bubbles
Derive balanced-stage fill/drain time and distinguish elapsed idle fraction from overhead relative to ideal compute.
28 min - 03
One-forward-one-backward schedules
Trace warmup, alternating steady state, cooldown, and the activation lifetimes of a synchronous 1F1B pipeline.
28 min - 04
Interleaved pipeline schedules
Map virtual chunks to physical ranks and trade a smaller ideal bubble against additional boundaries and schedule constraints.
28 min - 05
Activation stashing and rematerialization
Treat saved forward state as identity-bearing data and account for recomputation, randomness, and side effects.
28 min - 06
Microbatch size and gradient semantics
Preserve the intended sample or token objective while changing accumulation, kernel shape, and schedule microbatches.
29 min - 07
Pipeline weight-version consistency
Distinguish matching local forward/backward weights from synchronous global-update semantics and delayed-gradient algorithms.
29 min - 08
Stage imbalance and repartitioning
Locate the dependency critical path and amortize a safe partition change rather than treating average stage cost as throughput.
29 min - 09
Point-to-point pipeline deadlocks
Trace communication matching, wait cycles, collective order, and buffer ownership instead of assuming asynchronous calls guarantee progress.
29 min - 10
Pipeline schedule verification
Validate operation identities, dependencies, versions, memory, numeric results, and bounded progress before trusting a throughput trace.
29 min