From dc801c07cf38b0c495686463e6ca6f871a64440e Mon Sep 17 00:00:00 2001 From: YurenHao0426 Date: Tue, 27 Jan 2026 09:57:37 -0600 Subject: Add collaborativeagents module and update gitignore - Add collaborativeagents subproject with adapters, agents, and evaluation modules - Update .gitignore to exclude large binary files (.whl, .tar), wandb logs, and results Co-Authored-By: Claude Opus 4.5 --- collaborativeagents/slurm/test_vllm_70b_8b.sh | 167 ++++++++++++++++++++++++++ 1 file changed, 167 insertions(+) create mode 100644 collaborativeagents/slurm/test_vllm_70b_8b.sh (limited to 'collaborativeagents/slurm/test_vllm_70b_8b.sh') diff --git a/collaborativeagents/slurm/test_vllm_70b_8b.sh b/collaborativeagents/slurm/test_vllm_70b_8b.sh new file mode 100644 index 0000000..815f267 --- /dev/null +++ b/collaborativeagents/slurm/test_vllm_70b_8b.sh @@ -0,0 +1,167 @@ +#!/bin/bash +#SBATCH --job-name=vllm_bench +#SBATCH --account=bfqt-delta-gpu +#SBATCH --partition=gpuA100x4 +#SBATCH --nodes=1 +#SBATCH --gpus-per-node=2 +#SBATCH --time=02:00:00 +#SBATCH --mem=128G +#SBATCH --output=slurm/logs/vllm_bench_70b_8b_%j.out +#SBATCH --error=slurm/logs/vllm_bench_70b_8b_%j.err + +# Realistic benchmark: 70B AWQ user simulator + 8B agent +# Tests actual conversation throughput with both models +set -e + +cd /projects/bfqt/users/yurenh2/ml-projects/personalization-user-model/collaborativeagents +source /u/yurenh2/miniforge3/etc/profile.d/conda.sh +conda activate eval + +export HF_HOME=/projects/bfqt/users/yurenh2/hf_cache/huggingface + +echo "=== Job Info ===" +echo "Job ID: $SLURM_JOB_ID" +echo "Node: $SLURM_NODELIST" +date + +echo "" +echo "=== GPU Info ===" +nvidia-smi --query-gpu=index,name,memory.total,memory.free --format=csv + +# Download AWQ 70B model if not complete +echo "" +echo "=== Ensuring AWQ 70B Model is Downloaded ===" +python -c " +from huggingface_hub import snapshot_download +import os +os.environ['HF_HOME'] = '/projects/bfqt/users/yurenh2/hf_cache/huggingface' +print('Checking/downloading hugging-quants/Meta-Llama-3.1-70B-Instruct-AWQ-INT4...') +path = snapshot_download('hugging-quants/Meta-Llama-3.1-70B-Instruct-AWQ-INT4') +print(f'Model ready at: {path}') +" + +MODEL_70B_AWQ="hugging-quants/Meta-Llama-3.1-70B-Instruct-AWQ-INT4" +MODEL_8B="/projects/bfqt/users/yurenh2/ml-projects/personalization-user-model/models/llama-3.1-8b-instruct" +PORT_70B=8004 +PORT_8B=8003 + +echo "" +echo "============================================" +echo "Starting 70B AWQ vLLM Server (GPU 0)" +echo "============================================" +CUDA_VISIBLE_DEVICES=0 python -m vllm.entrypoints.openai.api_server \ + --model $MODEL_70B_AWQ \ + --port $PORT_70B \ + --gpu-memory-utilization 0.90 \ + --max-model-len 4096 \ + --disable-log-requests \ + --quantization awq \ + --dtype float16 & +SERVER_70B_PID=$! +echo "70B Server PID: $SERVER_70B_PID" + +echo "" +echo "============================================" +echo "Starting 8B vLLM Server (GPU 1)" +echo "============================================" +CUDA_VISIBLE_DEVICES=1 python -m vllm.entrypoints.openai.api_server \ + --model $MODEL_8B \ + --port $PORT_8B \ + --gpu-memory-utilization 0.90 \ + --max-model-len 4096 \ + --disable-log-requests \ + --dtype bfloat16 & +SERVER_8B_PID=$! +echo "8B Server PID: $SERVER_8B_PID" + +echo "" +echo "Waiting for servers to start..." + +# Wait for 70B (may take 3-5 minutes) +for i in $(seq 1 120); do + if curl -s http://localhost:$PORT_70B/health > /dev/null 2>&1; then + echo "70B Server ready after $((i*3)) seconds" + break + fi + if [ $((i % 20)) -eq 0 ]; then + echo " Waiting for 70B... ($((i*3)) seconds)" + fi + sleep 3 +done + +# Wait for 8B +for i in $(seq 1 60); do + if curl -s http://localhost:$PORT_8B/health > /dev/null 2>&1; then + echo "8B Server ready after $((i*2)) seconds" + break + fi + sleep 2 +done + +# Check both servers +echo "" +if ! curl -s http://localhost:$PORT_70B/health > /dev/null 2>&1; then + echo "ERROR: 70B server failed to start" + kill $SERVER_70B_PID $SERVER_8B_PID 2>/dev/null + exit 1 +fi +echo "✓ 70B server healthy" + +if ! curl -s http://localhost:$PORT_8B/health > /dev/null 2>&1; then + echo "ERROR: 8B server failed to start" + kill $SERVER_70B_PID $SERVER_8B_PID 2>/dev/null + exit 1 +fi +echo "✓ 8B server healthy" + +echo "" +echo "=== vLLM Server Info ===" +echo "70B model:" +curl -s http://localhost:$PORT_70B/v1/models | python -m json.tool 2>/dev/null | head -10 +echo "" +echo "8B model:" +curl -s http://localhost:$PORT_8B/v1/models | python -m json.tool 2>/dev/null | head -10 + +echo "" +echo "============================================" +echo "Test 1: Individual Model Throughput" +echo "============================================" + +echo "" +echo "--- 70B AWQ Sequential (10 requests) ---" +python scripts/benchmark_inference.py --mode vllm --url http://localhost:$PORT_70B/v1 -n 10 + +echo "" +echo "--- 8B Sequential (20 requests) ---" +python scripts/benchmark_inference.py --mode vllm --url http://localhost:$PORT_8B/v1 -n 20 + +echo "" +echo "============================================" +echo "Test 2: Full Conversation Benchmark" +echo "============================================" +echo "Running 10 conversations with 70B user simulator + 8B agent..." +python scripts/benchmark_inference.py \ + --mode conversation \ + --url-70b http://localhost:$PORT_70B/v1 \ + --url-8b http://localhost:$PORT_8B/v1 \ + -n 10 + +# Cleanup +echo "" +echo "Cleaning up..." +kill $SERVER_70B_PID $SERVER_8B_PID 2>/dev/null +wait $SERVER_70B_PID $SERVER_8B_PID 2>/dev/null + +echo "" +echo "============================================" +echo "BENCHMARK COMPLETE!" +echo "============================================" +echo "" +echo "Key metrics to compare with paper:" +echo " - Paper: 2000 conversations/hour on H100x8" +echo " - Expected A100x2 with 70B AWQ + 8B: ~100-300 conv/hr" +echo " - Our old code: ~20 conv/hr" +echo "" +echo "If throughput is good, update experiment code to use vLLM." +echo "" +date -- cgit v1.2.3