Best Practices for Running LP360 on Virtual Machines – LP360

This guide outlines key recommendations for deploying and operating LP360 in virtualized environments such as Azure, AWS, or on-prem VDI platforms.

✅ Use the Latest LP360 Build

Always ensure the VM is running the most recent version of LP360. Updates often include performance optimizations and bug fixes that address VM-specific issues.

🖥️ Choose the Right VM Configuration

GPU Acceleration: Use VMs with dedicated GPU support (e.g., Nvidia A40 or A10). Avoid relying solely on virtual GPUs.
Image Type: Prefer Virtual Desktop Images over Server Images to ensure compatibility with GPU acceleration and GUI responsiveness.
Disk Performance: Use high-throughput disks (e.g., Azure P50 or better) to avoid I/O bottlenecks during processing.

⚙️ Optimize System Settings

Verify GPU Usage: Use tools like GPU-Z to confirm that LP360 is utilizing the physical GPU and OpenGL is enabled.
Remote Desktop Compatibility: Ensure your remote desktop solution (e.g., Omnissa Horizon) supports GPU passthrough and doesn’t interfere with rendering.
Use Premium SSD v2 for better latency and throughput.
Enable Accelerate Networking.
Consider disk caching settings (e.g., ReadOnly for data disks).
Monitor disk queue length and CPU ready time in Azure Monitor.

🔐 Understand Licensing Constraints

LP360’s licensing system includes checks for virtual environments. Avoid cloning VMs or using snapshots that could trigger license violations.

📚 Follow Official Documentation

🧪 Pilot Before Scaling

Before rolling out LP360 across multiple VMs:

Conduct a pilot deployment to validate performance.
Test workflows such as ground classification, point cloud editing, and contour generation under load.

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