- Add RESUME_RUN_ID env var for breakpoint resume in adaptive benchmarks.
When set, the script reuses an existing result directory and skips
already-tested (TP, DP, ISL, OSL) shapes based on adaptive_shapes.jsonl.
- Fix RUN_ID unbound variable in resume mode.
- Fix jq query to use -s (slurp) for jsonl files.
- Add resume skip logic to DRY_RUN mode as well.
- Rename DSL -> OSL across all adaptive benchmark files for consistency:
- scripts/common/adaptive_bench_lib.sh
- scripts/common/adaptive_concurrency.py
- experiments/dsv4_h200_vllm_tp_dp_matrix/adaptive_config.env
- experiments/dsv4_h200_vllm_tp_dp_matrix/run_adaptive_concurrency.sh
- experiments/dsv4_h200_sglang_tp_dp_matrix/adaptive_config.env
- experiments/dsv4_h200_sglang_tp_dp_matrix/run_adaptive_concurrency.sh
- experiments/ADAPTIVE_CONCURRENCY_USAGE.md
- Run vLLM server inside vllm/vllm-openai:latest container on H200.
- Run benchmark client inside lmsysorg/sglang:latest using
sglang.bench_serving --backend vllm, matching the sglang reference.
- Use RUNTIME_BASE for self-contained logs/pids/tmp instead of hardcoded
/data/user1/yy paths.
- Update model path to /data3/hf_models/DeepSeek-V4-Flash.
- Sample only low/high concurrency endpoints to match sglang matrix.
- Fix docker 'invalid reference format' caused by DOCKER_CLIENT_IMAGE not
being exported to bash -c subshells used by run_bench_serving.
- Add offline dummy ShareGPT dataset for random benchmark mode.
Source code was already committed; this adds only the structured final
artifacts from run 20260709-152419_matrix. Raw jsonl/logs/gpu_logs remain
ignored per .gitignore.
