Wire the timing module into the dsv4_p800_sglang_profile
experiment's server startup so benchmarks produce per-operator
Prefill/Decode breakdowns alongside the existing aggregate metrics.
Changes to start_sglang_docker.sh:
- Mount p800_timing.py into the container site-packages (read-only)
via PATCH_ROOT so the path resolves correctly on any host.
- Set SGLANG_TIMING_ENABLED=1 in the container env to activate
the monkey-patches loaded by sitecustomize.
- Prepend import p800_timing to the launch_server python -c
entrypoint so the polling thread starts before model loading.
Combined with the previous two commits, a single run of
run_profile.sh now emits /tmp/p800_timing_results_{pid}.json
per TP worker with layer/attention/moe/hc/rmsnorm timing split
by prefill and decode.
Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
- New experiment: dsv4_p800_sglang_profile for PyTorch profiler testing
- Documents XPU cuptiActivityDisable bug (error 17) when saving traces
- Includes benchmark results (ISL=4k, OSL=1k, C=16, TP8/DP1)
- PROFILE_REPORT.md with full analysis of P800 vs H20 performance gap
- Add dsv4_p800_sglang_tp_dp_official experiment config
