dynamo/examples/backends/trtllm/launch/disagg_same_gpu.sh

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#!/bin/bash
# SPDX-FileCopyrightText: Copyright (c) 2025 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
# SPDX-License-Identifier: Apache-2.0
# Disaggregated mode on single GPU - for testing only
# Both prefill and decode workers share the same GPU with reduced memory
# Check GPU memory availability
FREE_GPU_GB=$(python3 -c "import torch; print(torch.cuda.mem_get_info()[0]/1024**3)" 2>/dev/null)
if [ $? -ne 0 ]; then
echo "Error: Failed to check GPU memory. Is PyTorch with CUDA available?"
exit 1
fi
REQUIRED_GB=16
# Use bash arithmetic instead of bc to avoid external dependency
FREE_GPU_INT=$(python3 -c "print(int(float('$FREE_GPU_GB')))" 2>/dev/null)
if [ $? -ne 0 ]; then
echo "Error: Failed to parse GPU memory value."
exit 1
fi
if (( FREE_GPU_INT < REQUIRED_GB )); then
echo "Error: Insufficient GPU memory. Required: ${REQUIRED_GB}GB, Available: ${FREE_GPU_GB}GB"
echo "Please free up GPU memory before running disaggregated mode on single GPU."
exit 1
fi
echo "GPU memory check passed: ${FREE_GPU_GB}GB available (required: ${REQUIRED_GB}GB)"
# Environment variables with defaults
export DYNAMO_HOME=${DYNAMO_HOME:-"/workspace"}
export MODEL_PATH=${MODEL_PATH:-"Qwen/Qwen3-0.6B"}
export SERVED_MODEL_NAME=${SERVED_MODEL_NAME:-"Qwen/Qwen3-0.6B"}
export PREFILL_ENGINE_ARGS=${PREFILL_ENGINE_ARGS:-"$DYNAMO_HOME/tests/serve/configs/trtllm/prefill.yaml"}
export DECODE_ENGINE_ARGS=${DECODE_ENGINE_ARGS:-"$DYNAMO_HOME/tests/serve/configs/trtllm/decode.yaml"}
export CUDA_VISIBLE_DEVICES=${CUDA_VISIBLE_DEVICES:-"0"}
export MODALITY=${MODALITY:-"text"}
# Setup cleanup trap
cleanup() {
echo "Cleaning up background processes..."
kill $DYNAMO_PID $PREFILL_PID 2>/dev/null || true
wait $DYNAMO_PID $PREFILL_PID 2>/dev/null || true
echo "Cleanup complete."
}
trap cleanup EXIT INT TERM
# run frontend
python3 -m dynamo.frontend --http-port 8000 &
DYNAMO_PID=$!
# run prefill worker (shares GPU with decode)
CUDA_VISIBLE_DEVICES=$CUDA_VISIBLE_DEVICES \
DYN_SYSTEM_ENABLED=true DYN_SYSTEM_PORT=8081 \
python3 -m dynamo.trtllm \
--model-path "$MODEL_PATH" \
--served-model-name "$SERVED_MODEL_NAME" \
--extra-engine-args "$PREFILL_ENGINE_ARGS" \
--modality "$MODALITY" \
--publish-events-and-metrics \
--disaggregation-mode prefill &
PREFILL_PID=$!
# run decode worker (shares GPU with prefill)
CUDA_VISIBLE_DEVICES=$CUDA_VISIBLE_DEVICES \
DYN_SYSTEM_ENABLED=true DYN_SYSTEM_PORT=8082 \
python3 -m dynamo.trtllm \
--model-path "$MODEL_PATH" \
--served-model-name "$SERVED_MODEL_NAME" \
--extra-engine-args "$DECODE_ENGINE_ARGS" \
--modality "$MODALITY" \
--publish-events-and-metrics \
--disaggregation-mode decode