Validate archived MI355X MiniMax M3 vLLM disaggregation with srt-slurm

.github/workflows/run-sweep.yml

@@ -109,7 +109,7 @@ jobs:
                   ALL_EVALS: ${{ contains(github.event.pull_request.labels.*.name, 'all-evals') }}
                   EVALS_ONLY: ${{ contains(github.event.pull_request.labels.*.name, 'evals-only') }}
               run: |
-                  pip install pydantic pyyaml
+                  pip install "pydantic>=2" pyyaml
                   CMD=(
                       python3 utils/validate_perf_changelog.py
                       --changelog-file perf-changelog.yaml

.github/workflows/test-changelog-gate.yml

@@ -68,7 +68,7 @@ jobs:
       - name: Install dependencies
         run: |
           python -m pip install --upgrade pip
-          python -m pip install pytest pydantic pyyaml tabulate
+          python -m pip install pytest "pydantic>=2" pyyaml tabulate
 
       - name: Run validator, reuse, and gating tests
         run: |

benchmarks/multi_node/srt-slurm-recipes/vllm/minimax-m3/mi355x-fp4/8k1k/disagg-1p1d-tp4.yaml

@@ -0,0 +1,147 @@
+# Compatibility validation of the archived MI355X MiniMax-M3 FP4 recipe.
+# Preserve the original TP4/TP4 serving and benchmark settings. srt-slurm
+# owns allocation, native vLLM Router discovery, health, logs, and teardown.
+name: mi355x-vllm-minimaxm3-disagg-1p1d-tp4-8k1k
+
+model:
+  # Same provisioned checkpoint selected by the retired AMD launcher.
+  path: /it-share/data/MiniMax-M3-MXFP4
+  container: vllm/vllm-openai-rocm:v0.28.0
+  precision: fp4
+
+identity:
+  model:
+    repo: amd/MiniMax-M3-MXFP4
+  container:
+    image: vllm/vllm-openai-rocm:v0.28.0
+  frameworks:
+    vllm-router: 1d10e71fb7bb4c0adc9f2c16ec77bf5dd4aa1586
+
+slurm:
+  time_limit: "08:00:00"
+
+resources:
+  gpu_type: mi355x
+  gpus_per_node: 8
+  prefill_nodes: 1
+  decode_nodes: 1
+  prefill_workers: 1
+  decode_workers: 1
+  gpus_per_prefill: 4
+  gpus_per_decode: 4
+
+frontend:
+  type: vllm-router
+  container_image: vllm/vllm-router:nightly-20260903-1d10e71
+  enable_multiple_frontends: false
+  args:
+    policy: consistent_hash
+    prefill-policy: consistent_hash
+    decode-policy: consistent_hash
+    log-level: info
+
+environment: &runtime_environment
+  HF_HOME: /hf_hub_cache
+  HF_HUB_CACHE: /hf_hub_cache
+  HUGGINGFACE_HUB_CACHE: /hf_hub_cache
+  PYTHONDONTWRITEBYTECODE: "1"
+  PYTHONUNBUFFERED: "1"
+  GLOO_SOCKET_IFNAME: eno0
+  NCCL_SOCKET_IFNAME: eno0
+  NCCL_IB_HCA: rdma0,rdma1,rdma2,rdma3,rdma4,rdma5,rdma6,rdma7
+  MORI_RDMA_TC: "104"
+  MORI_IO_SQ_BACKOFF_TIMEOUT_US: "50000"
+  MORI_IO_QP_MAX_SEND_WR: "16384"
+  MORI_IO_QP_MAX_CQE: "32768"
+  MORI_IO_QP_MAX_SGE: "2"
+  MORI_IO_TC_DISABLE: "0"
+  VLLM_USE_V1: "1"
+  VLLM_SERVER_DEV_MODE: "0"
+  VLLM_DISABLE_REQUEST_ID_RANDOMIZATION: "1"
+  VLLM_ROCM_USE_AITER: "1"
+  VLLM_ROCM_USE_AITER_MOE: "1"
+  VLLM_ROCM_USE_AITER_FUSION_SHARED_EXPERTS: "1"
+  VLLM_USE_BREAKABLE_CUDAGRAPH: "0"
+  VLLM_ENGINE_READY_TIMEOUT_S: "3600"
+
+backend:
+  type: vllm
+  connector: moriio
+  prefill_environment:
+    VLLM_ROCM_QUICK_REDUCE_QUANTIZATION: INT4
+    VLLM_ROCM_QUICK_REDUCE_MAX_SIZE_BYTES_MB: "2048"
+  vllm_config:
+    prefill: &server_options
+      tensor-parallel-size: 4
+      served-model-name: MiniMax-M3-MXFP4
+      max-num-batched-tokens: 32768
+      max-num-seqs: 512
+      block-size: 128
+      language-model-only: true
+      attention-backend: TRITON_ATTN
+      moe-backend: aiter
+      no-enable-prefix-caching: true
+      gpu-memory-utilization: 0.90
+      tool-call-parser: minimax_m3
+      reasoning-parser: minimax_m3
+      enable-auto-tool-choice: true
+      trust-remote-code: true
+    decode: *server_options
+
+# Preserve the original exclusive two-node allocation, although each worker
+# uses only four GPUs. Do not pack the roles onto one node.
+sbatch_directives:
+  cpus-per-task: "128"
+  mem: "0"
+  exclusive: ""
+
+srun_options:
+  container-writable: ""
+  container-remap-root: ""
+  mem: "0"
+
+health_check:
+  max_attempts: 720
+  interval_seconds: 5
+
+benchmark:
+  type: custom
+  command: |
+    set -euo pipefail
+    result_root="/results/${SLURM_JOB_ID}"
+    mkdir -p "${result_root}/fixed-seq"
+    archive_runtime_logs() {
+      tar -C /logs -czf "${result_root}/runtime-logs.tar.gz" . 2>/dev/null || true
+    }
+    trap archive_runtime_logs EXIT
+    for concurrency in ${CONC_LIST}; do
+      num_prompts=$((concurrency * 10))
+      if (( num_prompts < 16 )); then num_prompts=16; fi
+      python3 /infmax-workspace/utils/bench_serving/benchmark_serving.py \
+        --backend openai \
+        --base-url "http://${SRT_FRONTEND_HOST}:${SRT_FRONTEND_PORT}" \
+        --endpoint /v1/completions \
+        --model MiniMax-M3-MXFP4 \
+        --tokenizer /model \
+        --dataset-name random \
+        --random-input-len 8192 \
+        --random-output-len 1024 \
+        --random-range-ratio "${RANDOM_RANGE_RATIO:-0.8}" \
+        --num-warmups "$((concurrency * 2))" \
+        --num-prompts "${num_prompts}" \
+        --max-concurrency "${concurrency}" \
+        --request-rate inf \
+        --ignore-eos \
+        --trust-remote-code \
+        --percentile-metrics ttft,tpot,itl,e2el \
+        --save-result \
+        --result-dir "${result_root}/fixed-seq" \
+        --result-filename "minimaxm3-vllm-mi355x-disagg-1p1d-tp4-isl8192-osl1024-c${concurrency}.json"
+      # The original vLLM benchmark allowed the idle KV reaper ten seconds.
+      sleep 10
+    done
+  env:
+    <<: *runtime_environment
+    MODEL_NAME: MiniMax-M3-MXFP4
+    TRANSFORMERS_VERBOSITY: error
+    TOKENIZERS_PARALLELISM: "false"

benchmarks/single_node/agentic/kimik3_fp4_mi355x_mtp.sh

@@ -35,10 +35,10 @@ set -x
 #   GPU_MEM_UTIL             0.95   (reference)
 #   MAX_NUM_BATCHED_TOKENS   8192   (default)
 #   AITER_A8W4               1      (reference; 0 = aiter a16w4 MoE path)
-#   LANGUAGE_MODEL_ONLY      true   
+#   LANGUAGE_MODEL_ONLY      true
 #   KV_CACHE_DTYPE           fp8    (default for every arm; =auto for a bf16 A/B)
 #   KV_BLOCK_SIZE            unset  (unset -> vLLM sizes the page; 128 under fp8)
-#   MAX_MODEL_LEN            1M     
+#   MAX_MODEL_LEN            1M
 #   SPEC_DECODE              true   (this is the _mtp DSpark recipe; =false for a no-spec A/B)
 #   SPEC_NUM_TOKENS          2      (DSpark draft length; validated by the _mtp config)
 
@@ -149,10 +149,9 @@ case "${KV_OFFLOAD_BACKEND:-}" in
       lmcache)
     require_agentic_kv_offload_backend "$KV_OFFLOAD_BACKEND"
 
-    # Keep the image's tested torch/ROCm stack and install only LMCache's
-    # missing runtime dependencies, same as the MiniMax-M3 lmcache arm.
-    LMCACHE_VERSION="0.5.5.dev60+rocm7.2"
+    LMCACHE_VERSION=0.5.5.dev89+rocm7.2
     LMCACHE_ROCM_INDEX="https://github.com/LMCache/LMCache/releases/expanded_assets/nightly-rocm"
+
     agentic_pip_install --quiet --no-cache-dir --no-deps \
         "sortedcontainers==2.4.0" \
         "opentelemetry-exporter-prometheus==0.61b0" \
@@ -197,6 +196,18 @@ case "${KV_OFFLOAD_BACKEND:-}" in
 
     LMCACHE_L1_SIZE_GB="$TOTAL_CPU_DRAM_GB"
 
+    # DCP shards decode KV across the TP ranks, so the LMCache GPU transfer
+    # pool needs one worker per rank; a non-DCP arm only needs a single worker.
+    # The DCP KV interleave also needs the larger 12288 chunk; a non-DCP arm
+    # uses the 3072 minimum (one KDA state group).
+    if [ "${DCP_SIZE:-1}" -gt 1 ]; then
+        LMCACHE_MAX_GPU_WORKERS=8
+        LMCACHE_CHUNK_SIZE=12288
+    else
+        LMCACHE_MAX_GPU_WORKERS=1
+        LMCACHE_CHUNK_SIZE=3072
+    fi
+
     LMCACHE_CMD=(
         lmcache server
         --host 127.0.0.1
@@ -205,12 +216,12 @@ case "${KV_OFFLOAD_BACKEND:-}" in
         --http-port "$LMCACHE_HTTP_PORT"
         --l1-size-gb "$LMCACHE_L1_SIZE_GB"
         --l1-init-size-gb 10
-        --chunk-size 3072
+        --chunk-size "$LMCACHE_CHUNK_SIZE"
         --separate-object-groups
         --enable-extra-logging
         --extra-logging-interval 30
         --max-cpu-workers 8
-        --max-gpu-workers 1
+        --max-gpu-workers "$LMCACHE_MAX_GPU_WORKERS"
         --eviction-policy LRU
         --supported-transfer-mode lmcache_driven
         --shm-name ""
@@ -256,16 +267,21 @@ case "$CONC" in
         GPU_MEM_UTIL=0.9
         MAX_NUM_BATCHED_TOKENS=16384
         ;;
-    2|4|8|10|12|14)
+    4|8|10|12|14)
         SYNTHETIC_ACCEPT_LEN=3.00
         SPEC_NUM_TOKENS=3
         GPU_MEM_UTIL=0.9
         MAX_NUM_BATCHED_TOKENS=8192
         ;;
+    44|48|52)
+        SPEC_NUM_TOKENS=0
+        GPU_MEM_UTIL=0.9
+        MAX_NUM_BATCHED_TOKENS=8192
+        ;;
     *)
         SPEC_NUM_TOKENS=0
-        GPU_MEM_UTIL=0.85
-        MAX_NUM_BATCHED_TOKENS=4096
+        GPU_MEM_UTIL=0.9
+        MAX_NUM_BATCHED_TOKENS=8192
         ;;
 esac
 
@@ -306,7 +322,7 @@ CP_ARGS=()
 ATTN_BE_ARGS=()
 if [ "$DCP_SIZE" -gt 1 ]; then
     CP_ARGS+=(--decode-context-parallel-size "$DCP_SIZE" --dcp-comm-backend a2a)
-    ATTN_BE_ARGS+=(--attention-backend TRITON_MLA)
+    ATTN_BE_ARGS+=(--attention-backend ROCM_AITER_MLA)
 fi
 export VLLM_USE_DIRECT_DCP_A2A=0
 export VLLM_USE_DIRECT_DCP_Q_GATHER=0

configs/amd-master.yaml

@@ -395,7 +395,7 @@ dsr1-fp8-mi355x-atom-mtp:
       search-space:
       - { tp: 8, conc-start: 4, conc-end: 256, spec-decoding: mtp  }
 kimik3-fp4-mi355x-vllm-agentic-mtp:
-  image: vllm/vllm-openai-rocm:nightly-1dc464d42681d22f38caf1fdc1eb632dc4421c45
+  image: vllm/vllm-openai-rocm:nightly-7c5dc571cbd1064ecc8a9b1045637ff647aa22cb
   model: moonshotai/Kimi-K3
   model-prefix: kimik3
   runner: cluster:mi355x-amds
@@ -406,8 +406,9 @@ kimik3-fp4-mi355x-vllm-agentic-mtp:
     agentic-coding:
     - dram-utilization: 0.60
       search-space:
-      - { tp: 8, kv-offloading: none, conc-list: [1] , spec-decoding: mtp}
-      - { tp: 8, ep: 1, kv-offloading: dram, kv-offload-backend: { name: lmcache, version: "0.5.5.dev60+rocm7.2" }, conc-list: [4, 8, 10, 12, 14], spec-decoding: mtp }
+      - { tp: 8, ep: 1, dcp-size: 1, kv-offloading: none, conc-list: [1] , spec-decoding: mtp}
+      - { tp: 8, ep: 1, dcp-size: 1, kv-offloading: dram, kv-offload-backend: { name: lmcache, version: "0.5.5.dev89+rocm7.2" }, conc-list: [4, 8, 10, 12, 14], spec-decoding: mtp }
+      - { tp: 8, ep: 1, dcp-size: 8, kv-offloading: dram, kv-offload-backend: { name: lmcache, version: "0.5.5.dev89+rocm7.2" }, conc-list: [44, 48, 52], spec-decoding: mtp }
 
 # Kimi-K3 MXFP4 agentic-coding benchmark on MI355X via ATOM with DSpark
 # speculative decoding (2 draft tokens -> golden AL 2.51,

configs/deprecated/amd-minimaxm3-8k1k-master.yaml

@@ -42,6 +42,43 @@ minimaxm3-fp8-mi355x-vllm-mtp:
       osl: 1024
       search-space:
       - { tp: 4, conc-start: 1, conc-end: 512, spec-decoding: mtp }
+# Archived compatibility lane; opt in through e2e-tests.yml, not active sweeps.
+# The old AMD launch infrastructure is removed by the shared base PR.
+minimaxm3-fp4-mi355x-vllm-disagg:
+  image: vllm/vllm-openai-rocm:v0.28.0
+  model: amd/MiniMax-M3-MXFP4
+  model-prefix: minimaxm3
+  runner: cluster:mi355x-amds
+  precision: fp4
+  framework: vllm-disagg
+  router: { name: vllm-router, version: "1d10e71fb7bb4c0adc9f2c16ec77bf5dd4aa1586" }
+  kv-p2p-transfer: moriio
+  multinode: true
+  disagg: true
+  scenarios:
+    fixed-seq-len:
+    - isl: 8192
+      osl: 1024
+      search-space:
+      - spec-decoding: "none"
+        conc-list: [ 1, 2, 4, 8, 16, 32, 64, 128, 256 ]
+        prefill:
+          num-worker: 1
+          tp: 4
+          ep: 1
+          dp-attn: false
+          additional-settings:
+          - "CONFIG_FILE=recipes/vllm/minimax-m3/mi355x-fp4/8k1k/disagg-1p1d-tp4.yaml"
+          - "SRT_SLURM_COMMIT=33a3d811b7956973e4ef78b1d0cf4a5d56dad6a1"
+        decode:
+          num-worker: 1
+          tp: 4
+          ep: 1
+          dp-attn: false
+          additional-settings:
+          - "CONFIG_FILE=recipes/vllm/minimax-m3/mi355x-fp4/8k1k/disagg-1p1d-tp4.yaml"
+          - "SRT_SLURM_COMMIT=33a3d811b7956973e4ef78b1d0cf4a5d56dad6a1"
+
 minimaxm3-fp4-mi355x-vllm:
   image: vllm/vllm-openai-rocm:nightly-69715823df89b11ee684b84066390cbb9092d5c1
   model: amd/MiniMax-M3-MXFP4

perf-changelog.yaml

@@ -6832,6 +6832,16 @@
     - "Isolate SGLang runtime caches per Slurm allocation to prevent concurrent sweep cells from sharing per-rank cache files."
   pr-link: https://github.com/SemiAnalysisAI/InferenceX/pull/2808
 
+- config-keys:
+    - kimik3-fp4-mi355x-vllm-agentic-mtp
+  scenario-type:
+    - agentic-coding
+  description:
+    - "Bump the MI355X K3 vLLM recipe to vLLM ROCm nightly 7c5dc571 and LMCache 0.5.5rc3."
+    - "Add a TP8/DCP8 spec-mtp DRAM-offload arm at concurrency 44/48/52."
+    - "Retune the LMCache tier (12288-token chunk, 8 GPU workers) and the no-spec decode profile (gpu-memory-utilization 0.9, 8192 batched tokens); switch the DCP attention backend to ROCM_AITER_MLA."
+  pr-link: https://github.com/SemiAnalysisAI/InferenceX/pull/2810
+
 - config-keys:
     - glm5.2-fp4-gb300-dynamo-trt-agentic-disagg-mtp
   scenario-type:
@@ -6885,3 +6895,22 @@
     - "Remove the mandatory host-repair hook, RDMA/GPU-drain helper scripts, and separate image/model staging allocation; use provisioned caches and native Pyxis container lifecycle."
     - "Keep InferenceX-specific benchmark/eval metadata and artifact collection in a portable adapter while preserving the existing serving and workload settings."
   pr-link: https://github.com/SemiAnalysisAI/InferenceX/pull/2542
+
+- config-keys:
+    - minimaxm3-fp4-mi355x-vllm-disagg
+  scenario-type:
+    - fixed-seq-len
+  description:
+    - "Port the archived MiniMax-M3 FP4 MI355X 1P1D TP4/TP4 MoRI-IO configuration to native srt-slurm and vLLM Router, retaining all nine 8k/1k concurrency points and explicit engine options."
+    - "Use official vLLM ROCm v0.28.0 and vLLM Router nightly-20260903-1d10e71 because both original image tags are no longer published. No engine patches or setup hooks."
+    - "Keep this deprecated configuration opt-in; validate through the upstream end-to-end workflow without restoring it to active production sweeps."
+  pr-link: https://github.com/SemiAnalysisAI/InferenceX/pull/2824
+
+- config-keys:
+    - minimaxm3-fp4-mi355x-vllm-disagg
+  scenario-type:
+    - fixed-seq-len
+  description:
+    - "Pin srt-slurm 33a3d811b795 for this archived compatibility lane: preserve upstream ephemeral-port allocation for MoRI TP child processes instead of injecting one shared VLLM_PORT scan base."
+    - "Keep the official engine/router images, model options, workload, and all previously validated recipes and runtime pins unchanged."
+  pr-link: https://github.com/SemiAnalysisAI/InferenceX/pull/2824