Files
FastDeploy/examples/splitwise/start_v1_tp1.sh
Juncai 08ca0f6aea [Feature] [PD] add simple router and refine splitwise deployment (#4709)
* add simple router and refine splitwise deployment

* fix
2025-11-06 14:56:02 +08:00

97 lines
2.7 KiB
Bash

#!/bin/bash
set -e
# Test splitwise deployment
# v0 requires prefill and decode in one node and it uses local scheduler
# v1 supports prefill and decode in multi node and it uses splitwise scheduler
# v2 supports prefill and decode in multi node and it uses router and local scheduler
wait_for_health() {
local server_port=$1
while true; do
status_code=$(curl -s -o /dev/null -w "%{http_code}" "http://0.0.0.0:${server_port}/health" || echo "000")
if [ "$status_code" -eq 200 ]; then
break
else
echo "Service not ready. Retrying in 2s..."
sleep 2
fi
done
}
# prepare environment
MODEL_NAME="PaddlePaddle/ERNIE-4.5-0.3B-Paddle"
# MODEL_NAME="baidu/ERNIE-4.5-21B-A3B-Paddle"
export FD_DEBUG=1
export ENABLE_V1_KVCACHE_SCHEDULER=0
export KVCACHE_GDRCOPY_FLUSH_ENABLE=1
SCRIPT_PATH=$(readlink -f "$0")
SCRIPT_DIR=$(dirname "$SCRIPT_PATH")
export $(bash ${SCRIPT_DIR}/../../scripts/get_rdma_nics.sh gpu)
echo "KVCACHE_RDMA_NICS:${KVCACHE_RDMA_NICS}"
if [ -z "${KVCACHE_RDMA_NICS}" ]; then
echo "KVCACHE_RDMA_NICS is empty, please check the output of get_rdma_nics.sh"
exit 1
fi
unset http_proxy && unset https_proxy
rm -rf log_*
# start redis
if ! redis-cli ping &>/dev/null; then
echo "Redis is not running. Starting redis-server..."
redis-server --daemonize yes
sleep 1
else
echo "Redis is already running."
fi
sleep 1
# start prefill
export CUDA_VISIBLE_DEVICES=0
export FD_LOG_DIR="log_prefill"
mkdir -p ${FD_LOG_DIR}
nohup python -m fastdeploy.entrypoints.openai.api_server \
--model ${MODEL_NAME} \
--port 8100 \
--metrics-port 8101 \
--engine-worker-queue-port 8102 \
--cache-queue-port 8103 \
--max-model-len 32768 \
--splitwise-role "prefill" \
--cache-transfer-protocol "rdma,ipc" \
--rdma-comm-ports 8104 \
--pd-comm-port 8105 \
--scheduler-name "splitwise" \
--scheduler-host "127.0.0.1" \
--scheduler-port 6379 \
--scheduler-ttl 9000 \
2>&1 >${FD_LOG_DIR}/nohup &
wait_for_health 8100
# start decode
export CUDA_VISIBLE_DEVICES=1
export FD_LOG_DIR="log_decode"
mkdir -p ${FD_LOG_DIR}
nohup python -m fastdeploy.entrypoints.openai.api_server \
--model ${MODEL_NAME} \
--port 9000 \
--metrics-port 9001 \
--engine-worker-queue-port 9002 \
--cache-queue-port 9003 \
--max-model-len 32768 \
--splitwise-role "decode" \
--cache-transfer-protocol "rdma,ipc" \
--rdma-comm-ports 9004 \
--pd-comm-port 9005 \
--scheduler-name "splitwise" \
--scheduler-host "127.0.0.1" \
--scheduler-port 6379 \
--scheduler-ttl 9000 \
2>&1 >${FD_LOG_DIR}/nohup &
wait_for_health 9000