For a bandwidth-sensitive benchmark, concurrent jobs would share the network to the
Hub/bucket and corrupt throughput numbers. Chain the matrix jobs with
--dependency=afterany (captured via `sbatch --parsable`) so SLURM runs exactly one at a
time while keeping each config an isolated job (own log + per-job OOM reporting).
afterany keeps the chain going if one job fails/OOMs. SERIAL=0 restores parallel
submission for OOM-isolation-only testing.
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
slurm/run_streaming_matrix.sh fans the benchmark matrix (sources {hub,bucket,
warmed_bucket} x modes {single,sarm} x decode {cpu,cuda}) out as isolated single-GPU
SLURM jobs, so an OOM in one config is contained and reported per-job by SLURM. Worker
count and shuffle buffer are bounded (lower for cuda, which holds a CUDA context + NVDEC
session per worker) to avoid host/VRAM OOM. Source/mode/decode/workers/buffer/account/
partition are env-overridable; SOURCES/MODES/DECODES select subsets.
benchmarks/streaming/summarize_results.py collapses the per-run JSONs into one comparison
table + summary.csv (frames/s/node, first-batch + p50/p95/p99 latency, cache hit-rate).
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
- examples/scaling/train_streaming_multinode.py: Accelerate-based distributed/
resumable streaming training (no DistributedSampler; rank/world_size auto-resolved),
checkpoints the dataset stream state, and supports a --dummy pure-dataloading path
with throughput logging. SLURM launcher in slurm/train_streaming_robocasa.sh.
- benchmarks/streaming/benchmark_streaming.py: dummy-consumer dataloading benchmark
(single / sarm frame modes) emitting frames/s/node, p50/p95/p99 sample latency,
first-batch latency, and VideoDecoderCache reuse stats as JSON + CSV. SLURM launcher
+ README documenting the source/node/mode matrix and manual bucket prewarming.
- VideoDecoderCache: add hit/miss/eviction counters and a stats() method so the
benchmark can surface decoder thrash (no new cache, no eviction-policy change).
- tests/datasets/test_streaming_distributed.py: accelerate-launch smoke test asserting
per-rank disjointness; skips (does not false-pass) when <2 processes spawn.
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>