feat: update gpt-oss 120b model recipe

recipes/gpt-oss-120b/README.md

@@ -0,0 +1,21 @@
+Note:
+
+- This recipe is for gpt-oss-120b in aggregated mode.
+
+# Running the recipe
+```bash
+./run.sh --model gpt-oss-120b --framework trtllm agg
+```
+
+# Images
+
+This recipe uses the following container images using custom commits. You might need to build the images to reproduce the benchmark.
+
+* aiperf
+ Based on commit [70af59489df24a601dba57604a7341966150b366](https://github.com/ai-dynamo/aiperf/commit/70af59489df24a601dba57604a7341966150b366)
+
+* dynamo trtllm runtime for arm64
+based on commit [7fdf50fec2cae9112224f5cea26cef3dde78506f](https://github.com/ai-dynamo/dynamo/commit/7fdf50fec2cae9112224f5cea26cef3dde78506f)
+```
+nvcr.io/nvidia/ai-dynamo/tensorrtllm-runtime:7fdf50fec2cae9112224f5cea26cef3dde78506f-35606896-trtllm-arm64
+```

recipes/gpt-oss-120b/model-cache/model-cache.yaml

@@ -0,0 +1,13 @@
+# SPDX-FileCopyrightText: Copyright (c) 2025 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
+# SPDX-License-Identifier: Apache-2.0
+apiVersion: v1
+kind: PersistentVolumeClaim
+metadata:
+  name: model-cache
+spec:
+  accessModes:
+    - ReadWriteMany
+  resources:
+    requests:
+      storage: 100Gi
+  storageClassName: "your-storage-class-name"

recipes/gpt-oss-120b/model-cache/model-download.yaml

@@ -0,0 +1,42 @@
+# SPDX-FileCopyrightText: Copyright (c) 2025 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
+# SPDX-License-Identifier: Apache-2.0
+apiVersion: batch/v1
+kind: Job
+metadata:
+  name: model-download
+spec:
+  backoffLimit: 3
+  completions: 1
+  parallelism: 1
+  template:
+    metadata:
+      labels:
+        app: model-download
+    spec:
+      restartPolicy: Never
+      containers:
+        - name: model-download
+          image: python:3.10-slim
+          command: ["sh", "-c"]
+          envFrom:
+            - secretRef:
+                name: hf-token-secret
+          env:
+            - name: MODEL_NAME
+              value: openai/gpt-oss-120b
+            - name: HF_HOME
+              value: /model-store
+            - name: HF_HUB_ENABLE_HF_TRANSFER
+              value: "1"
+          args:
+            - |
+              set -eux
+              pip install --no-cache-dir huggingface_hub hf_transfer
+              hf download $MODEL_NAME --exclude "original/*" --exclude "metal/*"
+          volumeMounts:
+            - name: model-cache
+              mountPath: /model-store
+      volumes:
+      - name: model-cache
+        persistentVolumeClaim:
+          claimName: model-cache

recipes/gpt-oss-120b/trtllm/agg/bench.yaml

@@ -11,47 +11,35 @@ spec:
   template:
     metadata:
       labels:
-        app: oss-gpt120b
+        app: oss-gpt120b-bench
     spec:
-      restartPolicy: Never
+      affinity:
+        podAntiAffinity:
+          requiredDuringSchedulingIgnoredDuringExecution:
+            - labelSelector:
+                matchExpressions:
+                  - key: nvidia.com/dynamo-graph-deployment-name
+                    operator: In
+                    values:
+                      - gpt-oss-agg
+              topologyKey: kubernetes.io/hostname
       containers:
-      - name: perf
-        image: my-registry/vllm-runtime:my-tag
-        workingDir: /workspace/components/backends/vllm
-        env:
-          - name: TARGET_MODEL
-            value: openai/gpt-oss-120b
-          - name: ENDPOINT
-            value: gpt-oss-agg-trtllmworker:8000
-          - name: CONCURRENCIES
-            value: "13000 13500 1400"
-          - name: ISL
-            value: "16"
-          - name: OSL
-            value: "1000"
-          - name: DEPLOYMENT_MODE
-            value: "agg"
-          - name: DEPLOYMENT_GPU_COUNT
-            value: "32"
-          - name: JOB_NAME
-            valueFrom:
-              fieldRef:
-                fieldPath: metadata.labels['job-name']
-          - name: ROOT_ARTIFACT_DIR
-            value: /root/.cache/huggingface/hub/perf
-        command:
+      - command:
         - /bin/sh
         - -c
         - |
-          #TODO: this can be baked into the aiperf image
-          apt-get update && apt-get install -y curl jq
+          apt-get update && apt-get install -y curl jq procps git && apt-get clean
+          pip install git+https://github.com/ai-dynamo/aiperf.git@70af59489df24a601dba57604a7341966150b366;
+          echo "aiperf installation completed";
+          sysctl -w net.ipv4.ip_local_port_range="1024 65000"
+          cat /proc/sys/net/ipv4/ip_local_port_range
           export COLUMNS=200
           EPOCH=$(date +%s)
           ## utility functions -- can be moved to a bash script / configmap
           wait_for_model_ready() {
             echo "Waiting for model '$TARGET_MODEL' at $ENDPOINT/v1/models (checking every 5s)..."
             while ! curl -s "http://$ENDPOINT/v1/models" | jq -e --arg model "$TARGET_MODEL" '.data[]? | select(.id == $model)' >/dev/null 2>&1; do
-                echo "[$(date '+%H:%M:%S')] Model not ready yet, waiting 5s..."
+                echo "[$(date '+%H:%M:%S')] Model not ready yet, sleeping 5s before checking again http://$ENDPOINT/v1/models"
                 sleep 5
             done
             echo "✅ Model '$TARGET_MODEL' is now available!"
@@ -65,11 +53,11 @@ spec:
             key=concurrency_${concurrency}
             export ARTIFACT_DIR="${ROOT_ARTIFACT_DIR}/${EPOCH}_${JOB_NAME}/${key}"
             mkdir -p "$ARTIFACT_DIR"
+            echo "ARTIFACT_DIR: $ARTIFACT_DIR"
             aiperf profile --artifact-dir $ARTIFACT_DIR \
                 --model $TARGET_MODEL \
-                --tokenizer ~/.cache/huggingface/hub/models--openai--gpt-oss-120b/snapshots/b5c939de8f754692c1647ca79fbf85e8c1e70f8a  \
-                --endpoint-type chat \
-                --endpoint /v1/chat/completions \
+                --tokenizer /model-cache/hub/models--openai--gpt-oss-120b/snapshots/b5c939de8f754692c1647ca79fbf85e8c1e70f8a  \
+                --endpoint-type chat  --endpoint /v1/chat/completions \
                 --streaming \
                 --url http://$ENDPOINT \
                 --synthetic-input-tokens-mean $isl \
@@ -80,13 +68,14 @@ spec:
                 --extra-inputs "{\"min_tokens\":$osl}" \
                 --extra-inputs "{\"ignore_eos\":true}" \
                 --extra-inputs "{\"nvext\":{\"ignore_eos\":true}}" \
+                --extra-inputs "{\"repetition_penalty\":1.0}" \
+                --extra-inputs "{\"temperature\": 0.0}" \
                 --concurrency $concurrency \
-                --request-count $((3*concurrency)) \
+                --request-count $((10*concurrency)) \
                 --warmup-request-count $concurrency \
-                --conversation-num 1 \
+                --conversation-num 12800 \
                 --random-seed 100 \
-                --request-rate 100000 \
-                --workers-max 128 \
+                --workers-max 252 \
                 -H 'Authorization: Bearer NOT USED' \
                 -H 'Accept: text/event-stream'\
                 --record-processors 32 \
@@ -97,27 +86,66 @@ spec:
           #### Actual execution ####
           wait_for_model_ready
           mkdir -p "${ROOT_ARTIFACT_DIR}/${EPOCH}_${JOB_NAME}"
+          # Calculate total concurrency based on per-GPU concurrency and GPU count
+          TOTAL_CONCURRENCY=$((CONCURRENCY_PER_GPU * DEPLOYMENT_GPU_COUNT))
+          echo "Calculated total concurrency: $TOTAL_CONCURRENCY (${CONCURRENCY_PER_GPU} per GPU × ${DEPLOYMENT_GPU_COUNT} GPUs)"
           # Write input_config.json
           cat > "${ROOT_ARTIFACT_DIR}/${EPOCH}_${JOB_NAME}/input_config.json" <<EOF
           {
             "gpu_count": $DEPLOYMENT_GPU_COUNT,
+            "concurrency_per_gpu": $CONCURRENCY_PER_GPU,
+            "total_concurrency": $TOTAL_CONCURRENCY,
             "mode": "$DEPLOYMENT_MODE",
             "isl": $ISL,
             "osl": $OSL,
             "endpoint": "$ENDPOINT",
             "model endpoint": "$TARGET_MODEL"
           }
           EOF
-          # Run perf for each concurrency
-          for concurrency in $CONCURRENCIES; do
-            run_perf $concurrency $ISL $OSL
-            sleep 10
-          done
+
+          # Run perf with calculated total concurrency
+          run_perf $TOTAL_CONCURRENCY $ISL $OSL
+          echo "done with concurrency $TOTAL_CONCURRENCY"
+        env:
+        - name: TARGET_MODEL
+          value: openai/gpt-oss-120b
+        - name: ENDPOINT
+          value: gpt-oss-agg-frontend:8000
+        - name: CONCURRENCY_PER_GPU
+          value: "900"
+        - name: DEPLOYMENT_GPU_COUNT
+          value: "72"
+        - name: ISL
+          value: "128"
+        - name: OSL
+          value: "1000"
+        - name: DEPLOYMENT_MODE
+          value: agg
+        - name: AIPERF_HTTP_CONNECTION_LIMIT
+          value: "252"
+        - name: JOB_NAME
+          valueFrom:
+            fieldRef:
+              apiVersion: v1
+              fieldPath: metadata.labels['job-name']
+        - name: ROOT_ARTIFACT_DIR
+          value: /model-cache/perf
+        - name: HF_HOME
+          value: /model-cache
+        - name: PYTHONUNBUFFERED
+          value: "1"
+        image: python:3.12-slim
+        imagePullPolicy: IfNotPresent
+        name: perf
+        securityContext:
+          privileged: true
         volumeMounts:
         - name: model-cache
-          mountPath: /root/.cache/huggingface
+          mountPath: /model-cache
+        workingDir: /workspace
       imagePullSecrets:
-        - name: nvcrimagepullsecret
+      - name: nvcrimagepullsecret
+      restartPolicy: Never
       volumes:
       - name: model-cache
         persistentVolumeClaim:

recipes/gpt-oss-120b/trtllm/agg/config.yaml

@@ -6,20 +6,12 @@ metadata:
   name: llm-config
 data:
   config.yaml: |
-    tensor_parallel_size: 4
-    moe_expert_parallel_size: 4
     enable_attention_dp: true
-    build_config:
-      max_batch_size: 640
-      max_num_tokens: 20000
-    moe_config:
-        backend: CUTLASS
     cuda_graph_config:
-        max_batch_size: 640
+        max_batch_size: 800
         enable_padding: true
     kv_cache_config:
-      free_gpu_memory_fraction: 0.9
       enable_block_reuse: false
-    print_iter_log: false
-    stream_interval: 50
-    use_torch_sampler: true
+    stream_interval: 20
+    moe_config:
+        backend: CUTLASS