How to configure virtual memory for 8+ GPUs? (Windows fix)

Understanding Virtual Memory Constraints in Multi-GPU Setups

1. Windows allocates virtual memory per process, not globally, and each GPU-bound application—especially cryptocurrency miners or AI training frameworks—may request large contiguous virtual address space.

2. With 8 or more GPUs, driver-level memory mapping, PCIe BAR allocation, and CUDA context initialization collectively demand significantly higher virtual address space than the default 4GB user-mode limit on 64-bit Windows.

3. Insufficient virtual memory manifests as “CUDA_ERROR_MEMORY_ALLOCATION”, “Failed to initialize device context”, or silent crashes during kernel launch without clear error codes.

4. The Windows page file size alone does not resolve this—virtual address space exhaustion is distinct from physical RAM or paging file capacity.

Modifying Boot Configuration for Extended Address Space

1. Launch Command Prompt as Administrator and execute bcdedit /set increaseuserva 3072 to raise the user-mode virtual address space from 2GB (default on legacy boot) or 4GB (standard UEFI) to 3GB.

2. For systems with >8 GPUs running memory-intensive kernels, use bcdedit /set increaseuserva 4096 to allocate up to 4GB of user-mode VA space—this requires enabling the “/LARGEADDRESSAWARE” flag in compatible binaries.

3. Reboot after applying the change; verify with bcdedit /enum and confirm “increaseuserva” appears under the active boot entry.

4. Avoid values exceeding 4096 unless using Windows Server editions with full 64-bit VA support—consumer Windows versions cap usable user VA at ~4GB even on x64.

GPU Driver and PCIe Configuration Tuning

1. Disable unnecessary GPU features via NVIDIA Control Panel: turn off PhysX, 3D Vision, and GPU-accelerated Windows animations to reduce driver-side virtual address consumption.

2. In Device Manager, open each GPU’s Properties → Resources → Change Setting → uncheck “Enable bus mastering” for non-primary GPUs if they’re used solely for compute—not rendering.

3. Use mmcfg registry tweak: navigate to HKEY_LOCAL_MACHINE\SYSTEM\CurrentControlSet\Control\PCI and set “MmConfig” DWORD to 1 to force memory-mapped configuration space, improving BAR allocation efficiency across multiple PCIe root complexes.

4. Ensure all GPUs are installed in slots connected to the same CPU socket—cross-socket PCIe routing increases VA fragmentation due to NUMA-aware driver mappings.

Page File Optimization for Compute Workloads

1. Set a fixed-size page file on an NVMe SSD: minimum = 16GB, maximum = 32GB—avoid system-managed sizing as it introduces latency spikes during memory pressure.

2. Distribute page files across multiple fast storage devices if multiple NVMe drives exist, assigning one per 4-GPU group to balance I/O contention during concurrent memory dumps.

3. Disable page file compression: run fsutil behavior set disablelastaccess 1 and fsutil behavior set disablelastaccess 0 to reset NTFS metadata overhead that interferes with low-latency swap operations.

4. Confirm page file visibility in Task Manager → Performance → Memory → Commit charge; “Total” should exceed “Limit” by at least 8GB when all 8 GPUs are active and loading models.

Frequently Asked Questions

Q: Does increasing userva affect system stability?A: No—this only adjusts the kernel/user VA split. Kernel space shrinks proportionally but remains sufficient for standard drivers and services on Windows 10/11 build 1904x and later.

Q: Can I apply increaseuserva on Windows 11 Home edition?A: Yes—bcdedit works identically across all Windows 11 editions including Home; no Group Policy or Pro license requirement applies.

Q: Why does nvidia-smi show “N/A” for memory usage on some GPUs after tuning?A: This occurs when the driver fails to map VRAM into host VA space early in initialization—reboot with increaseuserva applied usually restores visibility.

Q: Is WSL2 suitable for 8-GPU mining setups?A: Not recommended—WSL2 runs inside a lightweight VM with fixed VA constraints and lacks direct PCIe passthrough for multi-GPU compute contexts required by most mining binaries.