#!/bin/bash # run_frames_pixels.sh — task 11 (resolution x frame-rate sweep) on a multi-GPU machine without Slurm. # bash code/run_frames_pixels.sh --dry-run # count the work per benchmark x condition (no GPU) # PILOT=1 bash code/run_frames_pixels.sh # MVBench, LVBench, TimeScope only (report timing first) # bash code/run_frames_pixels.sh # all 84 benchmarks # BENCH="MVBench,LVBench" bash code/run_frames_pixels.sh # explicit benchmark list # One vLLM server per GPU (Qwen3-VL-8B, --max-model-len 65536, --limit-mm-per-prompt images 1024), one # runner process that round-robins over the servers. Resumable: rows already in results/conditions_results.csv # are skipped, so the conditions that exist on the origin cluster are never re-run. # Env: NGPU (default all), WORKERS (default 6 per GPU), GPU_UTIL (0.85), MAX_SEQS (default 32; use 8 on 32 GB GPUs), PORT0 (8011), # PY (python3), VLLM (vllm), CONDS (default: the task-11 list below), TOKEN_BUDGET (58000), MAX_IMAGES (1024) set -u CODE=$(cd "$(dirname "$0")" && pwd); ROOT=$(cd "$CODE/.." && pwd) export BENCH_BASE=${BENCH_BASE:-$ROOT/data} # /data/store/normalized//..., /data/logs export P1_SAMPLES_DIR=${P1_SAMPLES_DIR:-$ROOT/items/samples} export P1_RESULTS_ROOT=${P1_RESULTS_ROOT:-$ROOT/results} export P1_MANIFEST=${P1_MANIFEST:-$ROOT/manifest/manifest_subset.jsonl} mkdir -p "$BENCH_BASE/logs" "$P1_RESULTS_ROOT" "$ROOT/logs" [ -d "$BENCH_BASE/store/normalized" ] || { echo "unpack the video shards into $BENCH_BASE/store/normalized first"; exit 2; } PY=${PY:-python3}; VLLM=${VLLM:-vllm}; PORT0=${PORT0:-8011}; GPU_UTIL=${GPU_UTIL:-0.85}; MAX_SEQS=${MAX_SEQS:-32} TOKEN_BUDGET=${TOKEN_BUDGET:-58000}; MAX_IMAGES=${MAX_IMAGES:-1024} MODEL="Qwen/Qwen3-VL-8B-Instruct"; REV=0c351dd01ed87e9c1b53cbc748cba10e6187ff3b CONDS=${CONDS:-v_blind,v_1,v_32,v_32_s448,v_32_s224,v_32_s168,v_32_s336,v_8_s224,v_128_s224,v_fps0.25_s224,v_fps0.5_s224,v_fps1_s224,v_fps2_s224} RUNNER="$CODE/exp/pipeline/stage_p1_runner.py" if [ "${PILOT:-0}" = "1" ]; then BENCH=${BENCH:-MVBench,LVBench,TimeScope}; fi BENCH_ARG=(); [ -n "${BENCH:-}" ] && BENCH_ARG=(--bench "$BENCH") if [ "${1:-}" = "--dry-run" ]; then "$PY" "$RUNNER" --conditions "$CONDS" --endpoints http://127.0.0.1:1/v1 --token-budget "$TOKEN_BUDGET" --max-images "$MAX_IMAGES" "${BENCH_ARG[@]}" --dry-run; exit $? fi NGPU=${NGPU:-$(nvidia-smi -L 2>/dev/null | wc -l)}; [ "$NGPU" -ge 1 ] || { echo "no GPU found"; exit 2; } WORKERS=${WORKERS:-$((6 * NGPU))} export VLLM_USE_FLASHINFER_SAMPLER=0 PYTORCH_CUDA_ALLOC_CONF=expandable_segments:True TOKENIZERS_PARALLELISM=false PIDS=(); EPS="" for i in $(seq 0 $((NGPU - 1))); do PORT=$((PORT0 + i)); EPS="${EPS:+$EPS,}http://127.0.0.1:$PORT/v1" CUDA_VISIBLE_DEVICES=$i "$VLLM" serve "$MODEL" --revision "$REV" --served-model-name "$MODEL" --host 127.0.0.1 --port "$PORT" \ --max-model-len 65536 --gpu-memory-utilization "$GPU_UTIL" --max-num-seqs "$MAX_SEQS" \ --limit-mm-per-prompt "{\"image\": $MAX_IMAGES}" --mm-processor-cache-gb 0 \ > "$ROOT/logs/vllm_gpu${i}.log" 2>&1 & PIDS+=($!) done trap 'for p in "${PIDS[@]}"; do kill "$p" 2>/dev/null; done' EXIT for i in $(seq 0 $((NGPU - 1))); do PORT=$((PORT0 + i)) for t in $(seq 1 180); do curl -sf "http://127.0.0.1:$PORT/v1/models" >/dev/null 2>&1 && break; kill -0 "${PIDS[$i]}" 2>/dev/null || { echo "vLLM on GPU $i died, see logs/vllm_gpu${i}.log"; exit 1; }; sleep 10; done echo "[frames_pixels] vLLM ready on GPU $i (:$PORT)" done echo "[frames_pixels] launch: --max-model-len 65536 --limit-mm-per-prompt images=$MAX_IMAGES --max-num-seqs $MAX_SEQS --gpu-memory-utilization $GPU_UTIL; runner --token-budget $TOKEN_BUDGET --max-images $MAX_IMAGES --workers $WORKERS" | tee -a "$ROOT/logs/launch_params.txt" "$PY" "$RUNNER" --conditions "$CONDS" --endpoints "$EPS" --workers "$WORKERS" --token-budget "$TOKEN_BUDGET" --max-images "$MAX_IMAGES" "${BENCH_ARG[@]}" 2>&1 | tee -a "$ROOT/logs/runner.log" rc=${PIPESTATUS[0]} echo "[frames_pixels] runner finished rc=$rc"; exit $rc