[ROCm][P/D] Support MoRIIO heterogeneous TP fan-in

[tanpinsiang]

Summary

This PR builds on the MoRIIO typed control-message support merged in #46290.

This PR adds MoRIIO READ-mode support for heterogeneous prefill/decode TP sizes, e.g. P4/D8 and P8/D4.

Changes

• Add remote TP rank mapping for local_tp != remote_tp.
• Use the mapped TP rank for MoRIIO handshake and READ release notify ports.
• Send READ release ACKs as typed msgpack release messages with consumer_tp_size.
• Count producer-side ACK fan-in before reporting finished_sending.
• Preserve duplicate release ACKs instead of deduping them.
• Guard unsupported heterogeneous-TP KV head splitting.
• Add focused unit coverage for rank mapping, ACK fan-in, stale ACKs, duplicate ACKs, and head-splitting guard.

Notes

This refactors READ completion ACKs to use the typed msgpack control-message path introduced in #46290. Plain string completions are still accepted for backward compatibility and are treated as a single ACK.

This PR is co-authored by
@vllmellm @hongxiayang @junkang1991 @tanpinsiang @chunfangamd @TianDi101 @functionstackx @tjtanaa.

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[tjtanaa]

Amazing work. I have validated this PR as well on 2 nodes of mi355x.

I will document down the details here because it is extremely complex to setup the environment. Leaving down a log of commands can help to future endeavors in using this feature especially for agents to scrape the command.

Launch docker on two different nodes.

 #!/bin/bash
podman run -it --rm \
   --name moriio-prefill-node1 \
   --network=host \
   --ipc=host \
   --pid=host \
   --privileged \
   --cap-add=SYS_PTRACE \
   --security-opt seccomp=unconfined \
   --ulimit memlock=-1 \
   --ulimit stack=67108864 \
   --group-add=video \
   --group-add=render \
   --device /dev/kfd \
   --device /dev/dri \
   --device /dev/infiniband \
   -v /sys:/sys \
   -v hf-cache-nvme:/app/hf-cache-nvme \
   -e HF_HUB_CACHE="/app/hf-cache-nvme" \
   -e VLLM_HOST_IP=smci355-ccs-aus-g12-30 \
   -e NCCL_MIN_NCHANNELS=112 \
   -e VLLM_ENGINE_READY_TIMEOUT_S=3600 \
   -e VLLM_SERVER_DEV_MODE=1 \
   --entrypoint /bin/bash \
   vllm-openai-rocm:ainic-1.125.0
   # use vllm-openai-rocm:nightly

1P1D Command:

lmeval score

local-completions ({'model': 'MiniMaxAI/MiniMax-M3-MXFP8', 'base_url': 'http://127.0.0.1:30000/v1/completions', 'num_concurrent': 32, 'max_retries': 10, 'max_gen_toks': 2048, 'max_length': 1048576, 'timeout': 60000}), gen_kwargs: ({}), limit: None, num_fewshot: 30, batch_size: auto
|Tasks|Version|     Filter     |n-shot|  Metric   |   |Value |   |Stderr|
|-----|------:|----------------|-----:|-----------|---|-----:|---|-----:|
|gsm8k|      3|flexible-extract|    30|exact_match|↑  |0.9393|±  |0.0066|
|     |       |strict-match    |    30|exact_match|↑  |0.9401|±  |0.0065|

Command

vLLM-Router (I am launching this on the prefill node)

#!/bin/bash
podman run --rm --network host docker.io/vllm/vllm-router:nightly \
  vllm-router \
    --host 0.0.0.0 \
    --port 30000 \
    --vllm-pd-disaggregation \
    --kv-connector moriio \
    --vllm-discovery-address 0.0.0.0:36367 \
    --policy consistent_hash \
    --prefill-policy consistent_hash \
    --decode-policy consistent_hash \
    --log-level info

Prefill node

Since I have launched the docker image as an interactive environment I only need to run the following

export VLLM_ROCM_USE_AITER=1
export VLLM_USE_BREAKABLE_CUDAGRAPH=0
export VLLM_ENGINE_READY_TIMEOUT_S=3600
export HSA_ENABLE_SDMA=1

export P_IP=<P_IP>
export ROUTER_IP=<ROUTER_IP>

export MORI_RDMA_DEVICES=ionic_0,ionic_1,ionic_2,ionic_3,ionic_4,ionic_5,ionic_7,ionic_8
export MORI_SOCKET_IFNAME=enp196s0
unset MORI_IB_GID_INDEX

vllm serve MiniMaxAI/MiniMax-M3-MXFP8 \
  --host 0.0.0.0 \
  --port 8100 \
  --trust-remote-code \
  --tensor-parallel-size 8 \
  --block-size 128 \
  --language-model-only \
  --kv-cache-dtype fp8 \
  --attention-backend TRITON_ATTN \
  --no-enable-prefix-caching \
  --gpu-memory-utilization 0.90 \
  --tool-call-parser minimax_m3 \
  --reasoning-parser minimax_m3 \
  --enable-auto-tool-choice \
  --kv-transfer-config '{
    "kv_connector": "MoRIIOConnector",
    "kv_role": "kv_producer",
    "kv_connector_extra_config": {
      "host_ip": "'"${P_IP}"'",
      "proxy_ip": "'"${ROUTER_IP}"'",
      "proxy_ping_port": 36367,
      "http_port": 8100,
      "handshake_port": 6301,
      "notify_port": 61005,
      "read_mode": true,
      "backend": "rdma",
      "qp_per_transfer": 4,
      "num_workers": 4
    }
  }'

Decode Node

Since I have launched the docker image as an interactive environment I only need to run the following

export VLLM_MORIIO_CONNECTOR_READ_MODE=1
export VLLM_USE_V1=1
export VLLM_ROCM_USE_AITER=1
export VLLM_USE_BREAKABLE_CUDAGRAPH=0
export VLLM_ENGINE_READY_TIMEOUT_S=3600
export HSA_ENABLE_SDMA=1

export D_IP=<D_IP>
export ROUTER_IP=<ROUTER_IP>

export MORI_RDMA_DEVICES=ionic_0,ionic_1,ionic_2,ionic_3,ionic_4,ionic_5,ionic_7,ionic_8
export MORI_SOCKET_IFNAME=enp196s0
unset MORI_IB_GID_INDEX

vllm serve MiniMaxAI/MiniMax-M3-MXFP8 \
  --host 0.0.0.0 \
  --port 8200 \
  --trust-remote-code \
  --tensor-parallel-size 8 \
  --block-size 128 \
  --language-model-only \
  --kv-cache-dtype fp8 \
  --attention-backend TRITON_ATTN \
  --no-enable-prefix-caching \
  --gpu-memory-utilization 0.90 \
  --tool-call-parser minimax_m3 \
  --reasoning-parser minimax_m3 \
  --enable-auto-tool-choice \
  --kv-transfer-config '{
    "kv_connector": "MoRIIOConnector",
    "kv_role": "kv_consumer",
    "kv_connector_extra_config": {
      "host_ip": "'"${D_IP}"'",
      "proxy_ip": "'"${ROUTER_IP}"'",
      "proxy_ping_port": 36367,
      "http_port": 8200,
      "handshake_port": 7301,
      "notify_port": 7501,
      "read_mode": true,
      "backend": "rdma",
      "qp_per_transfer": 4,
      "num_workers": 4
    }
  }'

2P1D (two TP4 + one TP8)

lm-eval score

local-completions ({'model': 'MiniMaxAI/MiniMax-M3-MXFP8', 'base_url': 'http://127.0.0.1:30000/v1/completions', 'num_concurrent': 32, 'max_retries': 10, 'max_gen_toks': 2048, 'max_length': 1048576, 'timeout': 60000}), gen_kwargs: ({}), limit: None, num_fewshot: 30, batch_size: auto
|Tasks|Version|     Filter     |n-shot|  Metric   |   |Value |   |Stderr|
|-----|------:|----------------|-----:|-----------|---|-----:|---|-----:|
|gsm8k|      3|flexible-extract|    30|exact_match|↑  |0.9386|±  |0.0066|
|     |       |strict-match    |    30|exact_match|↑  |0.9386|±  |0.0066|

Command

vLLM-Router (I am launching this on the prefill node)

#!/bin/bash
podman run --rm --network host docker.io/vllm/vllm-router:nightly \
  vllm-router \
    --host 0.0.0.0 \
    --port 30000 \
    --vllm-pd-disaggregation \
    --kv-connector moriio \
    --vllm-discovery-address 0.0.0.0:36367 \
    --policy consistent_hash \
    --prefill-policy consistent_hash \
    --decode-policy consistent_hash \
    --log-level info

Prefill node

Since I have launched the docker image as an interactive environment I only need to run the following

NODE 1

export VLLM_ROCM_USE_AITER=1
export VLLM_USE_BREAKABLE_CUDAGRAPH=0
export VLLM_ENGINE_READY_TIMEOUT_S=3600
export HSA_ENABLE_SDMA=1

export P_IP=<P_IP>
export ROUTER_IP=<ROUTER_IP>

export MORI_RDMA_DEVICES=ionic_0,ionic_1,ionic_2,ionic_3,ionic_4,ionic_5,ionic_7,ionic_8
export MORI_SOCKET_IFNAME=enp196s0
unset MORI_IB_GID_INDEX

vllm serve MiniMaxAI/MiniMax-M3-MXFP8 \
  --host 0.0.0.0 \
  --port 8100 \
  --trust-remote-code \
  --tensor-parallel-size 4 \
  --block-size 128 \
  --language-model-only \
  --kv-cache-dtype fp8 \
  --attention-backend TRITON_ATTN \
  --no-enable-prefix-caching \
  --gpu-memory-utilization 0.90 \
  --tool-call-parser minimax_m3 \
  --reasoning-parser minimax_m3 \
  --enable-auto-tool-choice \
  --kv-transfer-config '{
    "kv_connector": "MoRIIOConnector",
    "kv_role": "kv_producer",
    "kv_connector_extra_config": {
      "host_ip": "'"${P_IP}"'",
      "proxy_ip": "'"${ROUTER_IP}"'",
      "proxy_ping_port": 36367,
      "http_port": 8100,
      "handshake_port": 6301,
      "notify_port": 61005,
      "read_mode": true,
      "backend": "rdma",
      "qp_per_transfer": 4,
      "num_workers": 4
    }
  }'

NODE 2

export VLLM_ROCM_USE_AITER=1
export VLLM_USE_BREAKABLE_CUDAGRAPH=0
export VLLM_ENGINE_READY_TIMEOUT_S=3600
export HSA_ENABLE_SDMA=1

export HIP_VISIBLE_DEVICES=4,5,6,7
export P_IP=<P_IP>
export ROUTER_IP=<ROUTER_IP>

export MORI_RDMA_DEVICES=ionic_0,ionic_1,ionic_2,ionic_3,ionic_4,ionic_5,ionic_7,ionic_8
export MORI_SOCKET_IFNAME=enp196s0
unset MORI_IB_GID_INDEX

vllm serve MiniMaxAI/MiniMax-M3-MXFP8 \
  --host 0.0.0.0 \
  --port 8101 \
  --trust-remote-code \
  --tensor-parallel-size 4 \
  --block-size 128 \
  --language-model-only \
  --kv-cache-dtype fp8 \
  --attention-backend TRITON_ATTN \
  --no-enable-prefix-caching \
  --gpu-memory-utilization 0.90 \
  --tool-call-parser minimax_m3 \
  --reasoning-parser minimax_m3 \
  --enable-auto-tool-choice \
  --kv-transfer-config '{
    "kv_connector": "MoRIIOConnector",
    "kv_role": "kv_producer",
    "kv_connector_extra_config": {
      "host_ip": "'"${P_IP}"'",
      "proxy_ip": "'"${ROUTER_IP}"'",
      "proxy_ping_port": 36367,
      "http_port": 8101,
      "handshake_port": 6305,
      "notify_port": 40006,
      "read_mode": true,
      "backend": "rdma",
      "qp_per_transfer": 4,
      "num_workers": 4
    }
  }'

Decode Node

Since I have launched the docker image as an interactive environment I only need to run the following

export VLLM_MORIIO_CONNECTOR_READ_MODE=1
export VLLM_USE_V1=1
export VLLM_ROCM_USE_AITER=1
export VLLM_USE_BREAKABLE_CUDAGRAPH=0
export VLLM_ENGINE_READY_TIMEOUT_S=3600
export HSA_ENABLE_SDMA=1

export D_IP=<D_IP>
export ROUTER_IP=<ROUTER_IP>

export MORI_RDMA_DEVICES=ionic_0,ionic_1,ionic_2,ionic_3,ionic_4,ionic_5,ionic_7,ionic_8
export MORI_SOCKET_IFNAME=enp196s0
unset MORI_IB_GID_INDEX

vllm serve MiniMaxAI/MiniMax-M3-MXFP8 \
  --host 0.0.0.0 \
  --port 8200 \
  --trust-remote-code \
  --tensor-parallel-size 8 \
  --block-size 128 \
  --language-model-only \
  --kv-cache-dtype fp8 \
  --attention-backend TRITON_ATTN \
  --no-enable-prefix-caching \
  --gpu-memory-utilization 0.90 \
  --tool-call-parser minimax_m3 \
  --reasoning-parser minimax_m3 \
  --enable-auto-tool-choice \
  --kv-transfer-config '{
    "kv_connector": "MoRIIOConnector",
    "kv_role": "kv_consumer",
    "kv_connector_extra_config": {
      "host_ip": "'"${D_IP}"'",
      "proxy_ip": "'"${ROUTER_IP}"'",
      "proxy_ping_port": 36367,
      "http_port": 8200,
      "handshake_port": 7301,
      "notify_port": 7501,
      "read_mode": true,
      "backend": "rdma",
      "qp_per_transfer": 4,
      "num_workers": 4
    }
  }'

1P2D (one TP8 + two TP4)

lm-eval score

local-completions ({'model': 'MiniMaxAI/MiniMax-M3-MXFP8', 'base_url': 'http://127.0.0.1:30000/v1/completions', 'num_concurrent': 32, 'max_retries': 10, 'max_gen_toks': 2048, 'max_length': 1048576, 'timeout': 60000}), gen_kwargs: ({}), limit: None, num_fewshot: 30, batch_size: auto
|Tasks|Version|     Filter     |n-shot|  Metric   |   |Value |   |Stderr|
|-----|------:|----------------|-----:|-----------|---|-----:|---|-----:|
|gsm8k|      3|flexible-extract|    30|exact_match|↑  |0.9401|±  |0.0065|
|     |       |strict-match    |    30|exact_match|↑  |0.9409|±  |0.0065|

I will not repeat the command here as it is similar to the 2P1D command.

[hongxiayang]

Tested in https://github.com/SemiAnalysisAI/InferenceX/actions/runs/27968834654/job/82769697444?pr=1762

[mergify]

This pull request has merge conflicts that must be resolved before it can be
merged. Please rebase the PR, @tanpinsiang.

https://docs.github.com/en/pull-requests/collaborating-with-pull-requests/working-with-forks/syncing-a-fork