Elastic Expert Parallel Initial Support

examples/online_serving/elastic_ep/bench.sh

@@ -0,0 +1,11 @@
+#!/bin/bash
+
+MODEL_NAME="deepseek-ai/DeepSeek-V2-Lite-Chat"
+HOST="localhost"
+PORT=8006
+
+vllm bench serve \
+    --model $MODEL_NAME \
+    --host $HOST \
+    --port $PORT \
+    --num-prompts 5

examples/online_serving/elastic_ep/scale.py

@@ -0,0 +1,53 @@
+#!/usr/bin/env python3
+# SPDX-License-Identifier: Apache-2.0
+# SPDX-FileCopyrightText: Copyright contributors to the vLLM project
+
+import argparse
+import json
+import sys
+
+import requests
+
+
+def scale(host, port, new_dp_size):
+    url = f"http://{host}:{port}/scale"
+    payload = {"new_data_parallel_size": new_dp_size}
+    headers = {"Content-Type": "application/json"}
+
+    print(f"Sending scale request to {url}")
+    print(f"Payload: {json.dumps(payload, indent=2)}")
+
+    try:
+        response = requests.post(url, json=payload, headers=headers, timeout=300)
+
+        print(f"Status Code: {response.status_code}")
+        print(f"Response: {response.text}")
+
+        if response.status_code == 200:
+            print("Scale up/down request successful!")
+            return True
+        else:
+            print("Scale up/down request failed!")
+            return False
+
+    except requests.exceptions.RequestException as e:
+        print(f"Request failed: {e}")
+        return False
+
+
+def main():
+    parser = argparse.ArgumentParser(description="Test scale up/down functionality")
+    parser.add_argument("--host", default="localhost", help="API server host")
+    parser.add_argument("--port", type=int, default=8006, help="API server port")
+    parser.add_argument(
+        "--new-dp-size", type=int, default=2, help="New data parallel size"
+    )
+
+    args = parser.parse_args()
+
+    success = scale(args.host, args.port, args.new_dp_size)
+    sys.exit(0 if success else 1)
+
+
+if __name__ == "__main__":
+    main()

examples/online_serving/elastic_ep/serve_deepseek_v2.sh

@@ -0,0 +1,31 @@
+#!/bin/bash
+
+# Serve DeepSeek V2 model with vLLM
+# This script demonstrates how to serve the DeepSeek V2 model using vLLM's V1 engine
+
+# MODEL_NAME="gaunernst/DeepSeek-V2-Lite-Chat-FP8"
+MODEL_NAME="deepseek-ai/DeepSeek-V2-Lite-Chat"
+HOST="0.0.0.0"
+PORT=8006
+
+DATA_PARALLEL_SIZE=3
+DATA_PARALLEL_SIZE_LOCAL=$DATA_PARALLEL_SIZE
+
+export VLLM_USE_V1=1
+export VLLM_ALL2ALL_BACKEND="pplx"
+export VLLM_USE_DEEP_GEMM=1
+
+# Launch the vLLM server
+vllm serve $MODEL_NAME --trust-remote-code \
+    --disable-log-requests \
+    --host $HOST \
+    --port $PORT \
+    --tensor-parallel-size 1 \
+    --enable-expert-parallel \
+    --enable-eplb \
+    --num-redundant-experts 32 \
+    --enforce-eager \
+    --data-parallel-backend ray \
+    --data-parallel-size $DATA_PARALLEL_SIZE \
+    --data-parallel-size-local $DATA_PARALLEL_SIZE_LOCAL \
+    --data-parallel-start-rank 0

tools/ep_kernels/elastic_ep/nvshmem.patch

@@ -0,0 +1,92 @@
+From 18c0599c2f07ec965132efa25961dc8179c2dda3 Mon Sep 17 00:00:00 2001
+From: Yongji Wu <wuyongji317@gmail.com>
+Date: Tue, 20 May 2025 13:41:12 -0700
+Subject: [PATCH] fix reinit issues due to states not cleaned up
+
+fix double free
+---
+ src/host/init/init.cu                             | 10 ++++++++++
+ .../internal/host/nvshmemi_mem_transport.hpp      | 15 +++++++++++++++
+ src/modules/bootstrap/uid/bootstrap_uid.cpp       |  5 +++++
+ 3 files changed, 30 insertions(+)
+
+diff --git a/src/host/init/init.cu b/src/host/init/init.cu
+index b1c5dbf..1fecb4b 100644
+--- a/src/host/init/init.cu
++++ b/src/host/init/init.cu
+@@ -43,6 +43,8 @@
+ #include "internal/host/nvshmemi_types.h"
+ #include "internal/host/shared_memory.h"
+ #include "internal/host/nvshmemi_symmetric_heap.hpp"
++// eep-dev
++#include "internal/host/nvshmemi_mem_transport.hpp"
+
+ extern __constant__ nvshmemi_device_host_state_t nvshmemi_device_state_d;
+ static std::map<void *, int> registered_device_states;
+@@ -1293,6 +1295,14 @@ void nvshmemid_hostlib_finalize(void *device_ctx, void *transport_device_ctx) {
+         /* Multi-init Multi-fini*/
+         nvshmemi_state = NULL;
+         nvshmemi_device_state.nvshmemi_is_nvshmem_initialized = 0;
++        
++        // eep-dev
++        nvshmemi_mem_p2p_transport::destroy_instance();
++        nvshmemi_mem_remote_transport::destroy_instance();
++        free(nvshmemi_default_session);
++        nvshmemi_default_session = nullptr;
++        nvshmemi_device_state.nvshmemi_is_nvshmem_bootstrapped = false;
++        
+         nvshmemi_is_device_state_ready = false;
+     } else
+         nvshmemi_boot_handle.barrier(&nvshmemi_boot_handle);
+diff --git a/src/include/internal/host/nvshmemi_mem_transport.hpp b/src/include/internal/host/nvshmemi_mem_transport.hpp
+index 2495844..e4f408a 100644
+--- a/src/include/internal/host/nvshmemi_mem_transport.hpp
++++ b/src/include/internal/host/nvshmemi_mem_transport.hpp
+@@ -36,6 +36,13 @@ class nvshmemi_mem_p2p_transport final {
+             return p2p_objref_;
+         }
+     }
++    // eep-dev
++    static void destroy_instance(void) {
++        if (p2p_objref_ != nullptr) {
++            delete p2p_objref_;
++            p2p_objref_ = nullptr;
++        }
++    }
+
+     void print_mem_handle(int pe_id, int transport_idx, nvshmemi_symmetric_heap &obj);
+
+@@ -87,6 +94,14 @@ class nvshmemi_mem_remote_transport final {
+         }
+     }
+
++    // eep-dev
++    static void destroy_instance(void) {
++        if (remote_objref_ != nullptr) {
++            delete remote_objref_;
++            remote_objref_ = nullptr;
++        }
++    }
++
+     int gather_mem_handles(nvshmemi_symmetric_heap &obj, uint64_t heap_offset, size_t size);
+     /* On-demand registration and release of memory */
+     int register_mem_handle(nvshmem_mem_handle_t *local_handles, int transport_idx,
+diff --git a/src/modules/bootstrap/uid/bootstrap_uid.cpp b/src/modules/bootstrap/uid/bootstrap_uid.cpp
+index a1fa748..788fa96 100644
+--- a/src/modules/bootstrap/uid/bootstrap_uid.cpp
++++ b/src/modules/bootstrap/uid/bootstrap_uid.cpp
+@@ -630,6 +630,11 @@ int nvshmemi_bootstrap_plugin_pre_init(bootstrap_handle_t* handle, const int abi
+     // Discover the network for bootstrap, if not done previously.
+     // This code needs to be stateful to be able to be called multiple times by the caller
+     BOOTSTRAP_CHECK(bootstrap_net_init());
++    // eep-dev
++    if (handle->pre_init_ops != nullptr) {
++        BOOTSTRAP_PTR_FREE(handle->pre_init_ops);
++        handle->pre_init_ops = nullptr;
++    }
+     if (handle->pre_init_ops == nullptr) {
+         BOOTSTRAP_CALLOC(&handle->pre_init_ops, 1);
+         handle->pre_init_ops->get_unique_id = bootstrap_get_unique_id;
+-- 
+2.43.0
+

vllm/config.py

@@ -2025,6 +2025,19 @@ def has_unfinished_dp(dp_group: "ProcessGroup",
         aggregated_has_unfinished = bool(tensor.item())
         return aggregated_has_unfinished
 
+    @staticmethod
+    def sync_kv_cache_memory_size(dp_group: "ProcessGroup",
+                                  kv_cache_memory: int) -> int:
+        if kv_cache_memory == -1:
+            kv_cache_memory = torch.iinfo(torch.int64).max
+        tensor = torch.tensor([kv_cache_memory],
+                              dtype=torch.int64,
+                              device="cpu")
+        # we cannot use broadcast for stateless dp group since it depends
+        # on global rank
+        torch.distributed.all_reduce(tensor, op=ReduceOp.MIN, group=dp_group)
+        return tensor.item()
+
     def compute_hash(self):
         """
         Provide a hash that uniquely identifies all the configs