feat: profiling PVC updates for better UX

benchmarks/profiler/deploy/pvc-access-pod.yaml

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+# SPDX-FileCopyrightText: Copyright (c) 2025 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
+# SPDX-License-Identifier: Apache-2.0
+
+apiVersion: v1
+kind: Pod
+metadata:
+  name: pvc-access-pod
+  labels:
+    app: pvc-access
+spec:
+  activeDeadlineSeconds: 300  # Auto-delete after 5 minutes
+  securityContext:
+    runAsNonRoot: true
+    runAsUser: 1000
+    fsGroup: 1000
+  containers:
+  - name: ubuntu
+    image: ubuntu:22.04
+    command: ["/bin/bash"]
+    args: ["-c", "sleep 290"]  # Sleep for slightly less than deadline - tools can be installed via kubectl exec if needed
+    securityContext:
+      allowPrivilegeEscalation: false
+      readOnlyRootFilesystem: false
+      capabilities:
+        drop:
+        - ALL
+    volumeMounts:
+    - name: profiling-storage
+      mountPath: /profiling_results
+    resources:
+      requests:
+        memory: "128Mi"
+        cpu: "100m"
+      limits:
+        memory: "256Mi"
+        cpu: "200m"
+  volumes:
+  - name: profiling-storage
+    persistentVolumeClaim:
+      claimName: profiling-pvc
+  restartPolicy: Never

benchmarks/profiler/download_pvc_results.py

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+#!/usr/bin/env python3
+
+# SPDX-FileCopyrightText: Copyright (c) 2025 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
+# SPDX-License-Identifier: Apache-2.0
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+# http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+"""
+PVC Results Download Script
+
+This script downloads all relevant profiling results from the profiling PVC to a local directory.
+It creates the necessary access pod, downloads the files, and cleans up automatically.
+
+Usage:
+    python3 download_pvc_results.py --namespace <namespace> --output-dir <local_directory> [--no-config]
+
+Examples:
+    # Download to ./results directory
+    python3 download_pvc_results.py --namespace <namespace> --output-dir ./results
+
+    # Download to specific directory
+    python3 download_pvc_results.py --namespace <namespace> --output-dir /home/user/profiling_data
+
+    # Download without configuration files
+    python3 download_pvc_results.py --namespace <namespace> --output-dir ./results --no-config
+"""
+
+import argparse
+import subprocess
+import sys
+import time
+from pathlib import Path
+from typing import List
+
+from utils.kubernetes import check_kubectl_access, deploy_access_pod, run_command
+
+
+def list_pvc_contents(
+    namespace: str, pod_name: str, skip_config: bool = False
+) -> List[str]:
+    """List contents of the PVC to identify relevant files."""
+    print("Scanning PVC contents...")
+
+    # Build find command with optional config file exclusion
+    find_cmd = [
+        "kubectl",
+        "exec",
+        pod_name,
+        "-n",
+        namespace,
+        "--",
+        "find",
+        "/profiling_results",
+        "-type",
+        "f",
+        "-name",
+        "*.png",
+        "-o",
+        "-name",
+        "*.npz",
+    ]
+
+    # Add config file patterns if not skipping them
+    if not skip_config:
+        find_cmd.extend(
+            [
+                "-o",
+                "-name",
+                "*.yaml",
+                "-o",
+                "-name",
+                "*.yml",
+            ]
+        )
+
+    try:
+        result = run_command(find_cmd, capture_output=True)
+
+        files = [f.strip() for f in result.stdout.split("\n") if f.strip()]
+        config_note = " (excluding config files)" if skip_config else ""
+        print(f"Found {len(files)} relevant files to download{config_note}")
+        return files
+
+    except subprocess.CalledProcessError:
+        print("ERROR: Failed to list PVC contents")
+        sys.exit(1)
+
+
+def download_files(
+    namespace: str, pod_name: str, files: List[str], output_dir: Path
+) -> None:
+    """Download relevant files from PVC to local directory."""
+    if not files:
+        print("No files to download")
+        return
+
+    # Create output directory
+    output_dir.mkdir(parents=True, exist_ok=True)
+    print(f"Downloading {len(files)} files to {output_dir}")
+
+    downloaded = 0
+    failed = 0
+
+    for file_path in files:
+        try:
+            # Determine relative path and create local structure
+            rel_path = file_path.replace("/profiling_results/", "")
+
+            # Validate relative path
+            if ".." in rel_path or rel_path.startswith("/"):
+                print(f"  WARNING: Skipping potentially unsafe path: {file_path}")
+                failed += 1
+                continue
+
+            local_file = output_dir / rel_path
+
+            # Ensure the file is within output_dir
+            if not local_file.resolve().is_relative_to(output_dir.resolve()):
+                print(f"  WARNING: Skipping file outside output directory: {file_path}")
+                failed += 1
+                continue
+
+            local_file.parent.mkdir(parents=True, exist_ok=True)
+
+            # Download file
+            run_command(
+                [
+                    "kubectl",
+                    "cp",
+                    f"{namespace}/{pod_name}:{file_path}",
+                    str(local_file),
+                ],
+                capture_output=True,
+            )
+
+            downloaded += 1
+            if downloaded % 5 == 0:  # Progress update every 5 files
+                print(f"  Downloaded {downloaded}/{len(files)} files...")
+
+        except subprocess.CalledProcessError as e:
+            print(f"  WARNING: Failed to download {file_path}: {e}")
+            failed += 1
+
+    print(f"✓ Download completed: {downloaded} successful, {failed} failed")
+
+
+def download_summary_files(
+    namespace: str, pod_name: str, output_dir: Path, skip_config: bool = False
+) -> None:
+    """Download key summary files that might not match the pattern."""
+    summary_files = [
+        "/profiling_results/prefill_performance.png",
+        "/profiling_results/decode_performance.png",
+    ]
+
+    # Add config files if not skipping them
+    if not skip_config:
+        summary_files.append(
+            "/profiling_results/disagg.yaml"
+        )  # In case it was injected
+
+    print("Downloading summary files...")
+
+    for file_path in summary_files:
+        try:
+            # Check if file exists first using subprocess.run directly
+            result = subprocess.run(
+                [
+                    "kubectl",
+                    "exec",
+                    pod_name,
+                    "-n",
+                    namespace,
+                    "--",
+                    "test",
+                    "-f",
+                    file_path,
+                ],
+                capture_output=True,
+                text=True,
+                check=False,
+            )
+
+            if result.returncode != 0:
+                # File doesn't exist, skip silently
+                continue
+
+            # File exists, download it
+            rel_path = file_path.replace("/profiling_results/", "")
+
+            # Validate relative path
+            if ".." in rel_path or rel_path.startswith("/"):
+                print(
+                    f"  ⚠️  Skipped {file_path.split('/')[-1]}: potentially unsafe path"
+                )
+                continue
+
+            local_file = output_dir / rel_path
+
+            # Ensure the file is within output_dir
+            if not local_file.resolve().is_relative_to(output_dir.resolve()):
+                print(
+                    f"  ⚠️  Skipped {file_path.split('/')[-1]}: outside output directory"
+                )
+                continue
+
+            local_file.parent.mkdir(parents=True, exist_ok=True)
+
+            run_command(
+                [
+                    "kubectl",
+                    "cp",
+                    f"{namespace}/{pod_name}:{file_path}",
+                    str(local_file),
+                ],
+                capture_output=True,
+            )
+
+            print(f"  ✓ {rel_path}")
+
+        except Exception as e:
+            # File doesn't exist or failed to download, skip silently
+            print(f"  ⚠️  Skipped {file_path.split('/')[-1]}: {e}")
+            pass
+
+
+def cleanup_access_pod(namespace: str, pod_name: str) -> None:
+    """Clean up the access pod (let it auto-delete via activeDeadlineSeconds)."""
+    print(f"ℹ️  Access pod '{pod_name}' will auto-delete in 5 minutes")
+    print(f"   To delete immediately: kubectl delete pod {pod_name} -n {namespace}")
+
+
+def generate_readme(output_dir: Path, file_count: int) -> None:
+    """Generate a README file explaining the downloaded contents."""
+    readme_content = f"""# Profiling Results
+
+Downloaded {file_count} files from profiling PVC.
+
+## File Structure
+
+### Performance Plots
+- `prefill_performance.png` - Main prefill performance across TP sizes
+- `decode_performance.png` - Main decode performance across TP sizes
+
+### Interpolation Data
+- `selected_prefill_interpolation/raw_data.npz` - Prefill performance data
+- `selected_prefill_interpolation/*.png` - Prefill interpolation plots
+- `selected_decode_interpolation/raw_data.npz` - Decode performance data
+- `selected_decode_interpolation/*.png` - Decode interpolation plots
+
+### Configuration Files
+- `disagg.yaml` - DynamoGraphDeployment configuration used for profiling
+
+### Individual TP Results
+- `prefill_tp*/` - Individual tensor parallelism profiling results
+- `decode_tp*/` - Individual tensor parallelism profiling results
+
+## Loading Data
+
+To load the .npz data files in Python:
+
+```python
+import numpy as np
+
+# Load prefill data
+prefill_data = np.load('selected_prefill_interpolation/raw_data.npz')
+print("Prefill data keys:", list(prefill_data.keys()))
+
+# Load decode data
+decode_data = np.load('selected_decode_interpolation/raw_data.npz')
+print("Decode data keys:", list(decode_data.keys()))
+```
+
+Generated on: {time.strftime('%Y-%m-%d %H:%M:%S')}
+"""
+
+    readme_path = output_dir / "README.md"
+    with open(readme_path, "w") as f:
+        f.write(readme_content)
+
+    print("📝 Generated README.md with download summary")
+
+
+def main():
+    parser = argparse.ArgumentParser(
+        description="Download profiling results from PVC to local directory",
+        formatter_class=argparse.RawDescriptionHelpFormatter,
+        epilog=__doc__,
+    )
+
+    parser.add_argument(
+        "--namespace",
+        "-n",
+        required=True,
+        help="Kubernetes namespace containing the profiling PVC",
+    )
+
+    parser.add_argument(
+        "--output-dir",
+        "-o",
+        type=Path,
+        required=True,
+        help="Local directory to download results to",
+    )
+
+    parser.add_argument(
+        "--no-config",
+        action="store_true",
+        help="Skip downloading configuration files (*.yaml, *.yml)",
+    )
+
+    args = parser.parse_args()
+
+    print("📥 PVC Results Download")
+    print("=" * 40)
+
+    # Validate inputs
+    check_kubectl_access(args.namespace)
+
+    # Deploy access pod
+    pod_name = deploy_access_pod(args.namespace)
+
+    # List and download files
+    files = list_pvc_contents(args.namespace, pod_name, args.no_config)
+    download_files(args.namespace, pod_name, files, args.output_dir)
+
+    # Download additional summary files
+    download_summary_files(args.namespace, pod_name, args.output_dir, args.no_config)
+
+    # Generate README
+    generate_readme(args.output_dir, len(files))
+
+    # Cleanup info
+    cleanup_access_pod(args.namespace, pod_name)
+
+    print("\n✅ Download completed!")
+    print(f"📁 Results available at: {args.output_dir.absolute()}")
+    print("📄 See README.md for file descriptions")
+
+
+if __name__ == "__main__":
+    main()