#!/bin/bash # SPDX-FileCopyrightText: Copyright (c) 2025-2026 NVIDIA CORPORATION & AFFILIATES. All rights reserved. # SPDX-License-Identifier: Apache-2.0 # # Disaggregated prefill/decode on a SINGLE GPU. # Per-worker VRAM is estimated from model parameters below. Override individual # knobs (CONTEXT_LENGTH, MAX_RUNNING_REQUESTS) via env vars, or set # DYN_GPU_MEMORY_FRACTION_OVERRIDE to bypass the calculation entirely. # # Measured reference (Qwen/Qwen3-0.6B, --context-length 4096, RTX 6000 Ada 48 GiB): # estimate (from gpu_utils.sh) : ~5.7 GiB per worker (w=1.1 + kv=0.9 + oh=3.7) # actual (nvidia-smi) : ~5.3 GiB per worker (~10.9 GiB total) # fraction per worker (48 GiB) : 0.12 # KV cache : 25,536-29,712 tokens per worker # Handles full 4096-token context with --max-running-requests 2. set -e trap 'echo Cleaning up...; kill 0' EXIT SCRIPT_DIR="$(dirname "$(readlink -f "$0")")" source "$SCRIPT_DIR/../../../common/gpu_utils.sh" MODEL="Qwen/Qwen3-0.6B" # ---- Tunable (override via env vars) ---- CONTEXT_LENGTH="${CONTEXT_LENGTH:-4096}" MAX_RUNNING_REQUESTS="${MAX_RUNNING_REQUESTS:-2}" # ---- Estimate per-worker VRAM (see examples/common/gpu_utils.md) ---- # Sets _EW_WEIGHTS_GIB, _EW_KV_GIB, _EW_OVERHEAD_GIB, _EW_TOTAL_GIB estimate_worker_vram "$MODEL" "$CONTEXT_LENGTH" "$MAX_RUNNING_REQUESTS" sglang # DYN_GPU_MEMORY_FRACTION_OVERRIDE takes precedence (profiler binary search). # In single-GPU mode, split the override evenly between the two workers. if [[ -n "${DYN_GPU_MEMORY_FRACTION_OVERRIDE:-}" ]]; then GPU_MEM_FRACTION=$(awk -v f="$DYN_GPU_MEMORY_FRACTION_OVERRIDE" 'BEGIN { printf "%.2f", f / 2 }') else GPU_MEM_FRACTION=$(gpu_worker_fraction sglang) fi source "$SCRIPT_DIR/../../../common/launch_utils.sh" HTTP_PORT="${DYN_HTTP_PORT:-8000}" print_launch_banner "Launching Disaggregated (same GPU)" "$MODEL" "$HTTP_PORT" \ "Context len: $CONTEXT_LENGTH" \ "GPU Mem: ${GPU_MEM_FRACTION} per worker (~${_EW_TOTAL_GIB} GiB each)" \ " estimate: weights=${_EW_WEIGHTS_GIB} + kv=${_EW_KV_GIB} + overhead=${_EW_OVERHEAD_GIB} GiB" # run ingress with KV router mode for disaggregated setup # dynamo.frontend accepts either --http-port flag or DYN_HTTP_PORT env var (defaults to 8000) python3 -m dynamo.frontend --router-mode kv & # run prefill worker with metrics on port 8081 DYN_SYSTEM_PORT=${DYN_SYSTEM_PORT1:-8081} \ python3 -m dynamo.sglang \ --model-path "$MODEL" \ --served-model-name "$MODEL" \ --page-size 16 \ --tp 1 \ --trust-remote-code \ --disaggregation-mode prefill \ --disaggregation-bootstrap-port 12345 \ --host 0.0.0.0 \ --disaggregation-transfer-backend nixl \ --mem-fraction-static "${GPU_MEM_FRACTION}" \ --context-length "$CONTEXT_LENGTH" \ --chunked-prefill-size "$CONTEXT_LENGTH" \ --max-prefill-tokens "$CONTEXT_LENGTH" \ --enable-memory-saver \ --delete-ckpt-after-loading \ --max-running-requests "$MAX_RUNNING_REQUESTS" \ --enable-metrics & # Wait for prefill worker to initialize before starting decode worker # This prevents both workers from competing for GPU memory simultaneously, which can cause OOM. # The prefill worker needs time to: # 1. Load model weights and allocate its memory fraction # 2. Initialize KV cache with --delete-ckpt-after-loading to free checkpoint memory # 3. Register with NATS service discovery so decode worker can find it echo "Waiting for prefill worker to initialize..." sleep 5 # run decode worker with metrics on port 8082 DYN_SYSTEM_PORT=${DYN_SYSTEM_PORT2:-8082} \ python3 -m dynamo.sglang \ --model-path "$MODEL" \ --served-model-name "$MODEL" \ --page-size 16 \ --tp 1 \ --trust-remote-code \ --disaggregation-mode decode \ --disaggregation-bootstrap-port 12345 \ --host 0.0.0.0 \ --disaggregation-transfer-backend nixl \ --mem-fraction-static "${GPU_MEM_FRACTION}" \ --context-length "$CONTEXT_LENGTH" \ --chunked-prefill-size "$CONTEXT_LENGTH" \ --max-prefill-tokens "$CONTEXT_LENGTH" \ --enable-memory-saver \ --delete-ckpt-after-loading \ --max-running-requests "$MAX_RUNNING_REQUESTS" \ --enable-metrics & # Exit on first worker failure; kill 0 in the EXIT trap tears down the rest wait_any_exit