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wangxiaoteng888 ca05f7d632 [Bugfix] TP size larger than KV cache head causes accuracy issues (#3366) 
### What this PR does / why we need it?
Resolve the issue where, in the case of unequal TP (Tensor Parallelism),
the TP size is larger than the number of model attention kvcache heads,
causing the KV cache to generate duplicates, which leads to transmission
errors in the original code.
### Does this PR introduce _any_ user-facing change?
No
### How was this patch tested?
By ci
- vLLM version: v0.11.0rc3
- vLLM main: https://github.com/vllm-project/vllm/commit/v0.11.0

---------

Signed-off-by: nwpu-zxr <zhouxuerong2@huawei.com>
Signed-off-by: wangxiaoteng <wangxiaoteng@huawei.com>
Co-authored-by: nwpu-zxr <zhouxuerong2@huawei.com>
2025-10-11 11:22:23 +08:00

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Prefill-Decode Disaggregation Mooncake Verification (Qwen)

Getting Start

vLLM-Ascend now supports prefill-decode (PD) disaggregation with EP (Expert Parallel) options. This guide take one-by-one steps to verify these features with constrained resources.

Take the Qwen3-235B model as an example, use vllm-ascend v0.11.0rc1 (with vLLM v0.11.0) on 4 Atlas 800T A3 servers to deploy the "2P1D" architecture. Assume the ip of the prefiller server is 192.0.0.1 (prefill 1) and 192.0.0.2 (prefill 2), and the decoder servers are 192.0.0.3 (decoder 1) and 192.0.0.4 (decoder 2). On each server, use 8 NPUs 16 chips to deploy one service instance.

Verify Multi-Node Communication Environment

Physical Layer Requirements

  • The physical machines must be located on the same WLAN, with network connectivity.
  • All NPUs must be interconnected. Intra-node connectivity is via HCCS, and inter-node connectivity is via RDMA.

Verification Process

  1. Single Node Verification:

Execute the following commands on each node in sequence. The results must all be success and the status must be UP:

# Check the remote switch ports
for i in {0..15}; do hccn_tool -i $i -lldp -g | grep Ifname; done 
# Get the link status of the Ethernet ports (UP or DOWN)
for i in {0..15}; do hccn_tool -i $i -link -g ; done
# Check the network health status
for i in {0..15}; do hccn_tool -i $i -net_health -g ; done
# View the network detected IP configuration
for i in {0..15}; do hccn_tool -i $i -netdetect -g ; done
# View gateway configuration
for i in {0..15}; do hccn_tool -i $i -gateway -g ; done
# View NPU network configuration
cat /etc/hccn.conf
  1. Get NPU IP Addresses
for i in {0..15}; do hccn_tool -i $i -ip -g | grep ipaddr; done
  1. Cross-Node PING Test
# Execute on the target node (replace 'x.x.x.x' with actual npu ip address)
for i in {0..15}; do hccn_tool -i $i -ping -g address x.x.x.x;done

Install Mooncake

Mooncake is the serving platform for Kimi, a leading LLM service provided by Moonshot AI. First, we need to obtain the Mooncake project. Refer to the following command:

git clone -b pooling_async_memecpy_v1 https://github.com/AscendTransport/Mooncake

Update and install Python

apt-get install python3

Install the relevant dependencies.

cd Mooncake
bash dependencies.sh

Install mpi

apt purge mpich libmpich-dev
apt purge openmpi-bin
apt purge openmpi-bin libopenmpi-dev
apt install mpich libmpich-dev
export CPATH=/usr/lib/aarch64-linux-gnu/mpich/include/:$CPATH
export CPATH=/usr/lib/aarch64-linux-gnu/openmpi/lib:$CPATH

Compile and install

mkdir build
cd build
cmake ..
make -j
make install
cp mooncake-transfer-engine/src/transport/ascend_transport/hccl_transport/ascend_transport_c/libascend_transport_mem.so /usr/local/Ascend/ascend-toolkit/latest/python/site-packages/
cp mooncake-transfer-engine/src/libtransfer_engine.so /usr/local/Ascend/ascend-toolkit/latest/python/site-packages/
export LD_LIBRARY_PATH=/usr/local/Ascend/ascend-toolkit/latest/python/site-packages:$LD_LIBRARY_PATH

Prefiller / Decoder Deployment

We can run the following scripts to launch a server on the prefiller/decoder node respectively.

layerwise

:::::{tab-set}

::::{tab-item} Prefiller node 1

unset ftp_proxy
unset https_proxy
unset http_proxy
export HCCL_IF_IP=192.0.0.1
export GLOO_SOCKET_IFNAME="eth0"  # network card name
export TP_SOCKET_IFNAME="eth0"
export HCCL_SOCKET_IFNAME="eth0"
export VLLM_USE_V1=1
export HCCL_BUFFSIZE=1024
export OMP_PROC_BIND=false
export OMP_NUM_THREADS=10
export ASCEND_AGGREGATE_ENABLE=1
export ASCEND_TRANSPORT_PRINT=0
export ACL_OP_INIT_MODE=1
export ASCEND_A3_ENABLE=1
vllm serve /model/Qwen3-235B-A22B-W8A8 \
  --host 0.0.0.0 \
  --port 8004 \
  --api-server-count 2 \
  --data-parallel-size 2 \
  --data-parallel-size-local 2 \
  --data-parallel-address 192.0.0.1 \
  --data-parallel-rpc-port 13389 \
  --tensor-parallel-size 8 \
  --enable-expert-parallel \
  --seed 1024 \
  --enforce-eager \
  --distributed-executor-backend mp \
  --served-model-name qwen3-moe \
  --max-model-len 32768 \
  --max-num-batched-tokens 4096 \
  --trust-remote-code \
  --no-enable-prefix-caching \
  --gpu-memory-utilization 0.9 \
  --kv-transfer-config \
  '{"kv_connector": "MooncakeLayerwiseConnector",
  "kv_role": "kv_producer",
  "kv_port": "30000",
  "engine_id": "0",
  "kv_connector_module_path": "vllm_ascend.distributed.mooncake_layerwise_connector",
  "kv_connector_extra_config": {
            "use_ascend_direct": true,
            "prefill": {
                    "dp_size": 2,
                    "tp_size": 8
             },
             "decode": {
                    "dp_size": 32,
                    "tp_size": 1
             }
      }
  }'

::::

::::{tab-item} Prefiller node 2

unset ftp_proxy
unset https_proxy
unset http_proxy
export HCCL_IF_IP=192.0.0.2
export GLOO_SOCKET_IFNAME="eth0"  # network card name
export TP_SOCKET_IFNAME="eth0"
export HCCL_SOCKET_IFNAME="eth0"
export VLLM_USE_V1=1
export HCCL_BUFFSIZE=1024
export OMP_PROC_BIND=false
export OMP_NUM_THREADS=10
export ASCEND_AGGREGATE_ENABLE=1
export ASCEND_TRANSPORT_PRINT=0
export ACL_OP_INIT_MODE=1
export ASCEND_A3_ENABLE=1
vllm serve /model/Qwen3-235B-A22B-W8A8 \
  --host 0.0.0.0 \
  --port 8004 \
  --api-server-count 2 \
  --data-parallel-size 2 \
  --data-parallel-size-local 2 \
  --data-parallel-address 192.0.0.2 \
  --data-parallel-rpc-port 13389 \
  --tensor-parallel-size 8 \
  --enable-expert-parallel \
  --seed 1024 \
  --enforce-eager \
  --distributed-executor-backend mp \
  --served-model-name qwen3-moe \
  --max-model-len 32768 \
  --max-num-batched-tokens 4096 \
  --trust-remote-code \
  --no-enable-prefix-caching \
  --gpu-memory-utilization 0.9 \
  --kv-transfer-config \
  '{"kv_connector": "MooncakeLayerwiseConnector",
  "kv_role": "kv_producer",
  "kv_port": "30100",
  "engine_id": "1",
  "kv_connector_module_path": "vllm_ascend.distributed.mooncake_layerwise_connector",
  "kv_connector_extra_config": {
            "prefill": {
                    "dp_size": 2,
                    "tp_size": 8
             },
             "decode": {
                    "dp_size": 32,
                    "tp_size": 1
             }
      }
  }'

::::

::::{tab-item} Decoder node 1

unset ftp_proxy
unset https_proxy
unset http_proxy
export HCCL_IF_IP=192.0.0.3
export GLOO_SOCKET_IFNAME="eth0"  # network card name
export TP_SOCKET_IFNAME="eth0"
export HCCL_SOCKET_IFNAME="eth0"
export VLLM_USE_V1=1
export HCCL_BUFFSIZE=2048
export OMP_PROC_BIND=false
export OMP_NUM_THREADS=10
export ASCEND_AGGREGATE_ENABLE=1
export ASCEND_TRANSPORT_PRINT=0
export ACL_OP_INIT_MODE=1
export ASCEND_A3_ENABLE=1
vllm serve /model/Qwen3-235B-A22B-W8A8 \
  --host 0.0.0.0 \
  --port 8004 \
  --api-server-count 4 \
  --data-parallel-size 32 \
  --data-parallel-size-local 16 \
  --data-parallel-address 192.0.0.3 \
  --data-parallel-rpc-port 5964  \
  --tensor-parallel-size 1 \
  --enable-expert-parallel \
  --seed 1024 \
  --distributed-executor-backend mp \
  --served-model-name qwen3-moe \
  --max-model-len 32768 \
  --max-num-batched-tokens 512 \
  --max-num_seqs 16 \
  --trust-remote-code \
  --no-enable-prefix-caching \
  --gpu-memory-utilization 0.9 \
  --compilation-config '{"cudagraph_capture_sizes":[16]}' \
  --kv-transfer-config \
  '{"kv_connector": "MooncakeLayerwiseConnector",
  "kv_role": "kv_consumer",
  "kv_port": "30200",
  "engine_id": "2",
  "kv_connector_module_path": "vllm_ascend.distributed.mooncake_layerwise_connector",
  "kv_connector_extra_config": {
            "prefill": {
                    "dp_size": 2,
                    "tp_size": 8
             },
             "decode": {
                    "dp_size": 32,
                    "tp_size": 1
             }
      }
  }'

::::

::::{tab-item} Decoder node 2

unset ftp_proxy
unset https_proxy
unset http_proxy
export HCCL_IF_IP=192.0.0.4
export GLOO_SOCKET_IFNAME="eth0"  # network card name
export TP_SOCKET_IFNAME="eth0"
export HCCL_SOCKET_IFNAME="eth0"
export VLLM_USE_V1=1
export HCCL_BUFFSIZE=2048
export OMP_PROC_BIND=false
export OMP_NUM_THREADS=10
export ASCEND_AGGREGATE_ENABLE=1
export ASCEND_TRANSPORT_PRINT=0
export ACL_OP_INIT_MODE=1
export ASCEND_A3_ENABLE=1
vllm serve /model/Qwen3-235B-A22B-W8A8 \
  --host 0.0.0.0 \
  --port 8004 \
  --headless \
  --data-parallel-size 32 \
  --data-parallel-size-local 16 \
  --data-parallel-start-rank 16 \
  --data-parallel-address 192.0.0.3 \
  --data-parallel-rpc-port 5964  \
  --tensor-parallel-size 1 \
  --enable-expert-parallel \
  --seed 1024 \
  --distributed-executor-backend mp \
  --served-model-name qwen3-moe \
  --max-model-len 32768 \
  --max-num-batched-tokens 512 \
  --max-num_seqs 16 \
  --trust-remote-code \
  --no-enable-prefix-caching \
  --gpu-memory-utilization 0.9 \
  --compilation-config '{"cudagraph_capture_sizes":[16]}' \
  --kv-transfer-config \
  '{"kv_connector": "MooncakeLayerwiseConnector",
  "kv_role": "kv_consumer",
  "kv_port": "30300",
  "engine_id": "3",
  "kv_connector_module_path": "vllm_ascend.distributed.mooncake_layerwise_connector",
  "kv_connector_extra_config": {
            "prefill": {
                    "dp_size": 2,
                    "tp_size": 8
             },
             "decode": {
                    "dp_size": 32,
                    "tp_size": 1
             }
      }
  }'

::::

:::::

mooncake

:::::{tab-set}

::::{tab-item} Prefiller node 1

unset ftp_proxy
unset https_proxy
unset http_proxy
export HCCL_IF_IP=192.0.0.1
export GLOO_SOCKET_IFNAME="eth0"  # network card name
export TP_SOCKET_IFNAME="eth0"
export HCCL_SOCKET_IFNAME="eth0"
export VLLM_USE_V1=1
export HCCL_BUFFSIZE=1024
export OMP_PROC_BIND=false
export OMP_NUM_THREADS=10
vllm serve /model/Qwen3-235B-A22B-W8A8 \
  --host 0.0.0.0 \
  --port 8004 \
  --api-server-count 2 \
  --data-parallel-size 2 \
  --data-parallel-size-local 2 \
  --data-parallel-address 192.0.0.1 \
  --data-parallel-rpc-port 13389 \
  --tensor-parallel-size 8 \
  --enable-expert-parallel \
  --seed 1024 \
  --enforce-eager \
  --distributed-executor-backend mp \
  --served-model-name qwen3-moe \
  --max-model-len 32768 \
  --max-num-batched-tokens 4096 \
  --trust-remote-code \
  --no-enable-prefix-caching \
  --gpu-memory-utilization 0.9 \
  --kv-transfer-config \
  '{"kv_connector": "MooncakeConnector",
  "kv_role": "kv_producer",
  "kv_port": "30000",
  "engine_id": "0",
  "kv_connector_module_path": "vllm_ascend.distributed.mooncake_connector",
  "kv_connector_extra_config": {
            "use_ascend_direct": true,
            "prefill": {
                    "dp_size": 2,
                    "tp_size": 8
             },
             "decode": {
                    "dp_size": 32,
                    "tp_size": 1
             }
      }
  }'

::::

::::{tab-item} Prefiller node 2

unset ftp_proxy
unset https_proxy
unset http_proxy
export HCCL_IF_IP=192.0.0.2
export GLOO_SOCKET_IFNAME="eth0"  # network card name
export TP_SOCKET_IFNAME="eth0"
export HCCL_SOCKET_IFNAME="eth0"
export VLLM_USE_V1=1
export HCCL_BUFFSIZE=1024
export OMP_PROC_BIND=false
export OMP_NUM_THREADS=10
vllm serve /mnt/weight/Qwen3-235B-A22B-W8A8 \
  --host 0.0.0.0 \
  --port 8004 \
  --api-server-count 2 \
  --data-parallel-size 2 \
  --data-parallel-size-local 2 \
  --data-parallel-address 192.0.0.2 \
  --data-parallel-rpc-port 13389 \
  --tensor-parallel-size 8 \
  --enable-expert-parallel \
  --seed 1024 \
  --enforce-eager \
  --distributed-executor-backend mp \
  --served-model-name qwen3-moe \
  --max-model-len 32768 \
  --max-num-batched-tokens 4096 \
  --trust-remote-code \
  --no-enable-prefix-caching \
  --gpu-memory-utilization 0.9 \
  --kv-transfer-config \
  '{"kv_connector": "MooncakeConnector",
  "kv_role": "kv_producer",
  "kv_port": "30100",
  "engine_id": "1",
  "kv_connector_module_path": "vllm_ascend.distributed.mooncake_connector",
  "kv_connector_extra_config": {
            "prefill": {
                    "dp_size": 2,
                    "tp_size": 8
             },
             "decode": {
                    "dp_size": 32,
                    "tp_size": 1
             }
      }
  }'

::::

::::{tab-item} Decoder node 1

unset ftp_proxy
unset https_proxy
unset http_proxy
export HCCL_IF_IP=192.0.0.3
export GLOO_SOCKET_IFNAME="eth0"  # network card name
export TP_SOCKET_IFNAME="eth0"
export HCCL_SOCKET_IFNAME="eth0"
export VLLM_USE_V1=1
export HCCL_BUFFSIZE=2048
export OMP_PROC_BIND=false
export OMP_NUM_THREADS=10

vllm serve /model/Qwen3-235B-A22B-W8A8 \
  --host 0.0.0.0 \
  --port 8004 \
  --api-server-count 4 \
  --data-parallel-size 32 \
  --data-parallel-size-local 16 \
  --data-parallel-address 192.0.0.3 \
  --data-parallel-rpc-port 5964  \
  --tensor-parallel-size 1 \
  --enable-expert-parallel \
  --seed 1024 \
  --distributed-executor-backend mp \
  --served-model-name qwen3-moe \
  --max-model-len 32768 \
  --max-num-batched-tokens 512 \
  --max-num_seqs 16 \
  --trust-remote-code \
  --no-enable-prefix-caching \
  --gpu-memory-utilization 0.9 \
  --compilation-config '{"cudagraph_capture_sizes":[16]}' \
  --kv-transfer-config \
  '{"kv_connector": "MooncakeConnector",
  "kv_role": "kv_consumer",
  "kv_port": "30200",
  "engine_id": "2",
  "kv_connector_module_path": "vllm_ascend.distributed.mooncake_connector",
  "kv_connector_extra_config": {
            "prefill": {
                    "dp_size": 2,
                    "tp_size": 8
             },
             "decode": {
                    "dp_size": 32,
                    "tp_size": 1
             }
      }
  }'

::::

::::{tab-item} Decoder node 2

unset ftp_proxy
unset https_proxy
unset http_proxy
export HCCL_IF_IP=192.0.0.4
export GLOO_SOCKET_IFNAME="eth0"  # network card name
export TP_SOCKET_IFNAME="eth0"
export HCCL_SOCKET_IFNAME="eth0"
export VLLM_USE_V1=1
export HCCL_BUFFSIZE=2048
export OMP_PROC_BIND=false
export OMP_NUM_THREADS=10

vllm serve /model/Qwen3-235B-A22B-W8A8 \
  --host 0.0.0.0 \
  --port 8004 \
  --headless \
  --data-parallel-size 32 \
  --data-parallel-size-local 16 \
  --data-parallel-start-rank 16 \
  --data-parallel-address 192.0.0.3 \
  --data-parallel-rpc-port 5964  \
  --tensor-parallel-size 1 \
  --enable-expert-parallel \
  --seed 1024 \
  --distributed-executor-backend mp \
  --served-model-name qwen3-moe \
  --max-model-len 32768 \
  --max-num-batched-tokens 512 \
  --max-num_seqs 16 \
  --trust-remote-code \
  --no-enable-prefix-caching \
  --gpu-memory-utilization 0.9 \
  --compilation-config '{"cudagraph_capture_sizes":[16]}' \
  --kv-transfer-config \
  '{"kv_connector": "MooncakeConnector",
  "kv_role": "kv_consumer",
  "kv_port": "30300",
  "engine_id": "3",
  "kv_connector_module_path": "vllm_ascend.distributed.mooncake_connector",
  "kv_connector_extra_config": {
            "prefill": {
                    "dp_size": 2,
                    "tp_size": 8
             },
             "decode": {
                    "dp_size": 32,
                    "tp_size": 1
             }
      }
  }'

::::

:::::

Example proxy for Deployment

Run a proxy server on the same node with prefiller service instance. You can get the proxy program in the repository's examples: load_balance_proxy_layerwise_server_example.py

python load_balance_proxy_layerwise_server_example.py \
    --host 192.0.0.1 \
    --port 8080 \
    --prefiller-hosts 192.0.0.1 192.0.0.2\
    --prefiller-port 8004 8004\
    --decoder-hosts 192.0.0.3 192.0.0.4\
    --decoder-ports 8004 8004

Verification

Check service health using the proxy server endpoint.

curl http://192.0.0.1:8080/v1/completions \
    -H "Content-Type: application/json" \
    -d '{
        "model": "qwen3-moe",
        "prompt": "Who are you?",
        "max_tokens": 100,
        "temperature": 0
    }'