#!/usr/bin/env bash set -euo pipefail TP="${TP:?TP must be set to 1, 2, or 4}" case "${TP}" in 1|2|4) ;; *) echo "ERROR: invalid TP=${TP}" >&2; exit 1 ;; esac OUTPUT_ROOT="${OUTPUT_ROOT:?OUTPUT_ROOT must be set}" VENV_ROOT="${VENV_ROOT:-/tmp/wjh/venvs/vllm-0.20.0-cu129-profiler-v1}" VLLM_SOURCE="${VLLM_SOURCE:-/home/admin/cpfs/wjh/agentic-kv/third_party/vllm_v20_build}" MODEL="${MODEL:-/home/admin/cpfs/wjh/models/Qwen/Qwen3-30B-A3B}" CAMPAIGN_ROOT="$(cd "$(dirname "${BASH_SOURCE[0]}")" && pwd)" PROFILE_SCRIPT="${CAMPAIGN_ROOT}/../frontier-qwen30-vllm020-profile-v1/profile_vllm020_flashattn.py" LOG_DIR="${OUTPUT_ROOT}/logs" PROVENANCE_DIR="${OUTPUT_ROOT}/provenance" BATCH_SPECS=(2q512 4q512 8q512 16q512 2q2k 4q2k) mkdir -p "${LOG_DIR}" "${PROVENANCE_DIR}" "${OUTPUT_ROOT}/raw" exec > >(tee -a "${LOG_DIR}/composition.log") 2>&1 if [[ -z "${CUDA_VISIBLE_DEVICES:-}" ]]; then echo "ERROR: CUDA_VISIBLE_DEVICES must contain the fleet-allocated GPU" >&2 exit 1 fi IFS=',' read -r -a GPU_IDS <<< "${CUDA_VISIBLE_DEVICES}" if [[ "${#GPU_IDS[@]}" -ne 1 ]]; then echo "ERROR: expected exactly one GPU, got ${CUDA_VISIBLE_DEVICES}" >&2 exit 1 fi echo "PROFILE_LAUNCH_ECHO host=$(hostname) gpu=${CUDA_VISIBLE_DEVICES} model=${MODEL} runtime=vLLM-0.20.0+cu129 operator=FlashAttention3 tp=${TP} batch_specs=${BATCH_SPECS[*]} profile_script=${PROFILE_SCRIPT} output=${OUTPUT_ROOT} expected_wall=3-8m hard_wall=900s hard_gpu_cap=0.25_H20h" date -u +"START_UTC=%Y-%m-%dT%H:%M:%SZ" nvidia-smi --query-gpu=index,name,driver_version,memory.used,utilization.gpu --format=csv,noheader test -x "${VENV_ROOT}/bin/python" test -f "${VLLM_SOURCE}/benchmarks/attention_benchmarks/runner.py" test -f "${MODEL}/config.json" test -f "${PROFILE_SCRIPT}" git -C "${CAMPAIGN_ROOT}/../.." rev-parse HEAD > "${PROVENANCE_DIR}/aituner.commit" git -C "${VLLM_SOURCE}" rev-parse HEAD > "${PROVENANCE_DIR}/vllm-source.commit" sha256sum "${PROFILE_SCRIPT}" "${BASH_SOURCE[0]}" > "${PROVENANCE_DIR}/source.sha256" uv pip freeze --python "${VENV_ROOT}/bin/python" > "${PROVENANCE_DIR}/pip-freeze.txt" nvidia-smi --query-gpu=index,uuid,name,driver_version,memory.total --format=csv,noheader > "${PROVENANCE_DIR}/gpus.csv" printf '%s\n' "${BATCH_SPECS[@]}" > "${PROVENANCE_DIR}/batch-specs.txt" timeout --signal=TERM --kill-after=30s 780 \ "${VENV_ROOT}/bin/python" "${PROFILE_SCRIPT}" \ --vllm-source "${VLLM_SOURCE}" \ --model "${MODEL}" \ --output "${OUTPUT_ROOT}/raw/flashattn-composition-tp${TP}.json" \ --tp "${TP}" \ --batch-specs "${BATCH_SPECS[@]}" \ --warmup-iters 5 \ --repeats 10 \ --profile-kv-update test -s "${OUTPUT_ROOT}/raw/flashattn-composition-tp${TP}.json" sha256sum "${OUTPUT_ROOT}/raw/flashattn-composition-tp${TP}.json" "${PROVENANCE_DIR}"/* > "${OUTPUT_ROOT}/artifacts.sha256" nvidia-smi --query-gpu=index,name,memory.used,utilization.gpu --format=csv,noheader date -u +"END_UTC=%Y-%m-%dT%H:%M:%SZ" echo "FLASHATTN_COMPOSITION_COMPLETE tp=${TP} cases=${#BATCH_SPECS[@]}"