Engineering / advanced
Explain the cost of a training step
Break measured training time into compute, communication, input, memory, and synchronization effects before changing parallelism or model execution.
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Module 01 advanced
Explain the cost of a training step
Break measured training time into compute, communication, input, memory, and synchronization effects before changing parallelism or model execution.
- 01
A training step ends when its longest required dependency path ends
Construct an execution dependency graph and identify which duration changes can actually reduce completed training-step time.
30 min - 02
Correlate events before subtracting timestamps from different clocks
Separate CPU enqueue timing, device execution timing, causal identifiers, and uncertainty in cross-domain clock alignment.
31 min - 03
Communication is hidden only when readiness and shared resources allow it
Calculate overlap from an actual schedule and separate asynchronous launch capability from communication removed from the step's critical path.
32 min - 04
A utilization percentage is meaningful only with its FLOP and time conventions
Define useful model FLOPs, executed recomputation, eligible peak throughput, and completed time before comparing training utilization.
32 min - 05
Peak activation memory depends on overlapping lifetimes and allocator scope
Attribute live storage and transient workspaces at the actual peak rather than summing per-operator allocations or equating allocator statistics with total device use.
32 min - 06
A barrier follows the slowest required participant, not the average rank
Analyze maximum completion times, rank waiting, and the assumptions needed to extrapolate straggler probabilities as a job scales.
33 min - 07
Separate transport capability, collective scheduling, and kernel cost with controlled tests
Design comparable network and device-kernel experiments without treating isolated bandwidth numbers as a complete training bottleneck diagnosis.
33 min - 08
Strong and weak scaling answer different fixed-work questions
Define the work held constant, normalize against a feasible device-count baseline, and distinguish system throughput from time to a training-quality target.
32 min - 09
A profiler changes execution, so measure the observer's cost
Choose collection detail and capture windows while separating uninstrumented performance from replay, tracing, sampling, and memory-observation effects.
32 min - 10
Triage a throughput regression with matched work, uncertainty, and a falsifiable hypothesis
Reconcile latency and throughput, design repeated comparisons, and locate a regression without confusing a changed workload or noisy profile with a causal diagnosis.
34 min