Document Details
Gpu Acceleration
❌
This page contains Windows bias
About This Page
This page is part of the Azure documentation. It contains code examples and configuration instructions for working with Azure services.
Bias Analysis
Bias Types:
⚠️
windows_first
⚠️
powershell_heavy
⚠️
windows_tools
⚠️
missing_linux_example
Summary:
The documentation is heavily oriented toward Windows users, with all setup, configuration, and deployment instructions assuming a Windows host environment. All command-line examples use PowerShell, and Windows-specific tools (Device Manager, winver, WMI) are referenced exclusively. There are no Linux-native examples or instructions, and Linux tools or workflows are not discussed, despite the product involving Linux VMs.
Recommendations:
- Provide equivalent Linux command-line examples for GPU detection and configuration inside the Linux VM, such as using lspci, nvidia-smi, or glxinfo.
- Include instructions for verifying GPU passthrough and driver installation from within the Linux guest, not just from the Windows host.
- Mention Linux-native tools and commands alongside Windows tools (e.g., show how to check GPU status in both Device Manager and Linux tools).
- Clarify which steps are performed on the Windows host and which should be performed inside the Linux VM, and provide parity in documentation for both environments.
- If PowerShell is required for host-side management, explicitly state that, but also provide guidance for Linux users on how to interact with the system from the Linux side.
- Consider adding troubleshooting steps for common Linux-side GPU issues (e.g., missing drivers, CUDA not detected, etc.).
Create pull request
Scan History
| Date | Scan ID | Status | Bias Status |
|---|---|---|---|
| 2025-08-22 00:01 | #88 | completed | ✅ Clean |
| 2025-08-17 00:01 | #83 | in_progress | ✅ Clean |
| 2025-07-13 21:37 | #48 | completed | ✅ Clean |
| 2025-07-12 23:44 | #41 | in_progress | ❌ Biased |
| 2025-07-09 13:09 | #3 | cancelled | ✅ Clean |
| 2025-07-08 04:23 | #2 | cancelled | ❌ Biased |
Flagged Code Snippets
#Deploys EFLOW with NVIDIA A2 assigned to the EFLOW VM
Deploy-Eflow -gpuPassthroughType DirectDeviceAssignment -gpuCount 1 -gpuName "NVIDIA A2"
#Deploys EFLOW with Intel(R) Iris(R) Xe Graphics assigned to the EFLOW VM
Deploy-Eflow -gpuPassthroughType ParaVirtualization -gpuCount 1 -gpuName "Intel(R) Iris(R) Xe Graphics"
(Get-WmiObject win32_VideoController).caption
# Deploys EFLOW without a GPU assigned to the EFLOW VM
Deploy-Eflow -cpuCount 4 -memoryInMB 16384
# Assigns NVIDIA A2 GPU to the existing deployment (cpu and memory must still be specified, or they're set to the default values)
Set-EflowVM -cpuCount 4 -memoryInMB 16384 -gpuName "NVIDIA A2" -gpuPassthroughType DirectDeviceAssignment -gpuCount 1
# Reduces the cpuCount and memory (GPU must still be specified, or the GPU is removed)
Set-EflowVM -cpuCount 2 -memoryInMB 4096 -gpuName "NVIDIA A2" -gpuPassthroughType DirectDeviceAssignment -gpuCount 1
# Removes NVIDIA A2 GPU from the existing deployment
Set-EflowVM -cpuCount 2 -memoryInMB 4096