Windows GPU Setup Guide

Overview

Kamiwaza supports hardware acceleration on Windows through WSL2 with the following GPU configurations:

• NVIDIA GPUs (RTX series, GTX series, Quadro series)
• Intel Arc GPUs (A3xx, A5xx, A7xx series)
• Intel Integrated GPUs (UHD Graphics, Iris Xe)

Prerequisites

System Requirements

• Windows 11 (Build 22000 or later)
• WSL2 enabled and updated
• Latest GPU drivers installed
• Compatible GPU hardware

WSL2 Requirements

• WSL2 kernel version 5.10.60.1 or later
• Windows 11 with GPU virtualization support
• GPU drivers with WSL2 compatibility

NVIDIA GPU Setup

Supported Hardware

• RTX 40 Series: RTX 4090, RTX 4080, RTX 4070 Ti, RTX 4070, RTX 4060 Ti, RTX 4060
• RTX 30 Series: RTX 3090, RTX 3080, RTX 3070, RTX 3060 Ti, RTX 3060
• RTX 20 Series: RTX 2080 Ti, RTX 2080, RTX 2070, RTX 2060
• GTX 16 Series: GTX 1660 Ti, GTX 1660, GTX 1650
• GTX 10 Series: GTX 1080 Ti, GTX 1080, GTX 1070, GTX 1060

Driver Requirements

• Minimum: NVIDIA Driver 470.82 or later
• Recommended: NVIDIA Driver 535.98 or later
• Latest: Download from NVIDIA Driver Downloads

Installation Steps

1. Install NVIDIA Drivers

1. Download the latest driver for your GPU
2. Run the installer as Administrator
3. Restart your computer
4. Verify installation: nvidia-smi in Command Prompt

2. Install NVIDIA CUDA Toolkit for WSL

# In WSL (Ubuntu 24.04)
wget https://developer.download.nvidia.com/compute/cuda/repos/ubuntu2404/x86_64/cuda-keyring_1.1-1_all.deb
sudo dpkg -i cuda-keyring_1.1-1_all.deb
sudo apt-get update
sudo apt-get -y install cuda-toolkit-12-4

3. Verify GPU Access in WSL

# Check if GPU is visible
nvidia-smi

# Expected output:
# +-----------------------------------------------------------------------------+
# | NVIDIA-SMI 535.98                 Driver Version: 535.98                    |
# |-------------------------------+----------------------+----------------------+
# | GPU  Name        Persistence-M| Bus-Id        Disp.A | Volatile Uncorr. ECC |
# | Fan  Temp  Perf  Pwr:Usage/Cap|         Memory-Usage | GPU-Util  Compute M. |
# |                               |                      |               MIG M. |
# |===============================+======================+======================|
# |   0  NVIDIA GeForce RTX 4090  On   | 00000000:01:00.0  Off |                  N/A |
# |  0%   45C    P8    25W /  450W |      0MiB /  24576MiB |      0%      Default |
# |                               |                      |                  N/A |
# +-------------------------------+----------------------+----------------------+

Configuration Files

.wslconfig (Windows)

[wsl2]
gpuSupport=true
memory=16GB
processors=8

Environment Variables (WSL)

# Add to ~/.bashrc
export CUDA_HOME=/usr/local/cuda
export PATH=$PATH:$CUDA_HOME/bin
export LD_LIBRARY_PATH=$LD_LIBRARY_PATH:$CUDA_HOME/lib64

Intel Arc GPU Setup

Supported Hardware

• Arc A7 Series: A770, A750
• Arc A5 Series: A580, A570, A560, A550
• Arc A3 Series: A380, A370, A350, A310

Driver Requirements

• Minimum: Intel Arc Driver 31.0.101.4502 or later
• Recommended: Latest Intel Arc Driver
• Download: Intel Arc Driver Downloads

Installation Steps

1. Install Intel Arc Drivers

1. Download the latest Intel Arc driver
2. Run the installer as Administrator
3. Restart your computer
4. Verify installation in Device Manager

2. Install Intel OpenCL Runtime and oneAPI (Recommended)

For optimal Intel GPU performance, install Intel's oneAPI toolkit:

# In WSL (Ubuntu 24.04)
# Add Intel's GPG key
wget -O- https://apt.repos.intel.com/intel-gpg-keys/GPG-PUB-KEY-INTEL-SW-PRODUCTS.PUB | \
  gpg --dearmor | sudo tee /usr/share/keyrings/oneapi-keyring.gpg > /dev/null

# Add the oneAPI repository
echo "deb [signed-by=/usr/share/keyrings/oneapi-keyring.gpg] https://apt.repos.intel.com/oneapi all main" | \
  sudo tee /etc/apt/sources.list.d/oneAPI.list

# Update and install Intel OpenCL runtime and oneAPI
sudo apt update
sudo apt install -y intel-opencl-icd intel-basekit

# Configure permissions
sudo usermod -a -G render $USER
newgrp render

3. Alternative: Install OpenCL Runtime Only

If you prefer not to install the full oneAPI toolkit:

# Install OpenCL loader and tools
sudo apt-get update
sudo apt-get install -y ocl-icd-libopencl1 ocl-icd-opencl-dev opencl-headers clinfo

# Add Intel Graphics PPA for latest drivers
sudo apt-get install -y software-properties-common
sudo add-apt-repository -y ppa:kobuk-team/intel-graphics
sudo apt-get update
sudo apt-get install -y libze-intel-gpu1 libze1 intel-opencl-icd

4. Verify GPU Access in WSL

# Check OpenCL availability
clinfo | grep "Platform Name"

# Check GPU devices
clinfo | grep "Device Name"

# Expected output:
# Platform Name                                Intel(R) OpenCL
# Device Name                                  Intel(R) Arc(TM) A770 Graphics

Configuration Files

.wslconfig (Windows)

[wsl2]
gpuSupport=true
memory=16GB
processors=8

Environment Variables (WSL)

# Add to ~/.bashrc
export INTEL_OPENCL_CONFIG=/etc/OpenCL/vendors/intel.icd

# For oneAPI users, source the environment
echo 'source /opt/intel/oneapi/setvars.sh' >> ~/.bashrc

Intel Integrated GPU Setup

Supported Hardware

• 12th Gen Intel: UHD Graphics 730, UHD Graphics 770
• 13th Gen Intel: UHD Graphics 770, UHD Graphics 730
• 14th Gen Intel: UHD Graphics 770, UHD Graphics 730
• Intel Iris Xe: Integrated graphics in 11th-14th gen processors

Driver Requirements

• Minimum: Intel Graphics Driver 30.0.101.1190 or later
• Recommended: Latest Intel Graphics Driver
• Download: Intel Graphics Driver Downloads

Installation Steps

1. Install Intel Graphics Drivers

1. Download the latest Intel Graphics driver
2. Run the installer as Administrator
3. Restart your computer
4. Verify installation in Device Manager

2. Install Intel OpenCL Runtime

# In WSL (Ubuntu 24.04)
sudo apt-get update
sudo apt-get install -y intel-opencl-icd

3. Verify GPU Access in WSL

# Check OpenCL availability
clinfo | grep "Platform Name"

# Check GPU devices
clinfo | grep "Device Name"

# Expected output:
# Platform Name                                Intel(R) OpenCL
# Device Name                                  Intel(R) UHD Graphics 770

GPU Detection Scripts

Automatic Detection (PowerShell)

# detect_gpu.ps1
$gpuInfo = Get-WmiObject -Class Win32_VideoController | Select-Object Name, AdapterRAM, DriverVersion

foreach ($gpu in $gpuInfo) {
    if ($gpu.Name -match "NVIDIA") {
        Write-Host "NVIDIA GPU detected: $($gpu.Name)"
        # Run NVIDIA setup
    }
    elseif ($gpu.Name -match "Intel.*Arc") {
        Write-Host "Intel Arc GPU detected: $($gpu.Name)"
        # Run Intel Arc setup
    }
    elseif ($gpu.Name -match "Intel.*UHD|Intel.*Iris") {
        Write-Host "Intel Integrated GPU detected: $($gpu.Name)"
        # Run Intel Integrated setup
    }
}

GPU Setup Scripts

NVIDIA Setup (setup_nvidia_gpu.sh)

#!/bin/bash
# setup_nvidia_gpu.sh

echo "Setting up NVIDIA GPU acceleration..."

# Install CUDA toolkit
sudo apt-get update
sudo apt-get install -y cuda-toolkit-12-4

# Configure environment
echo 'export CUDA_HOME=/usr/local/cuda' >> ~/.bashrc
echo 'export PATH=$PATH:$CUDA_HOME/bin' >> ~/.bashrc
echo 'export LD_LIBRARY_PATH=$LD_LIBRARY_PATH:$CUDA_HOME/lib64' >> ~/.bashrc

# Test GPU access
nvidia-smi

echo "NVIDIA GPU setup complete!"

Intel Arc Setup (setup_intel_arc_gpu.sh)

#!/bin/bash
# setup_intel_arc_gpu.sh

echo "Setting up Intel Arc GPU acceleration..."

# Install oneAPI for optimal performance
wget -O- https://apt.repos.intel.com/intel-gpg-keys/GPG-PUB-KEY-INTEL-SW-PRODUCTS.PUB | \
  gpg --dearmor | sudo tee /usr/share/keyrings/oneapi-keyring.gpg > /dev/null

echo "deb [signed-by=/usr/share/keyrings/oneapi-keyring.gpg] https://apt.repos.intel.com/oneapi all main" | \
  sudo tee /etc/apt/sources.list.d/oneAPI.list

sudo apt update
sudo apt install -y intel-opencl-icd intel-basekit

# Configure permissions
sudo usermod -a -G render $USER
newgrp render

# Configure environment
echo 'source /opt/intel/oneapi/setvars.sh' >> ~/.bashrc
echo 'export INTEL_OPENCL_CONFIG=/etc/OpenCL/vendors/intel.icd' >> ~/.bashrc

# Test GPU access
clinfo | grep "Device Name"

echo "Intel Arc GPU setup complete!"

Intel Integrated Setup (setup_intel_integrated_gpu.sh)

#!/bin/bash
# setup_intel_integrated_gpu.sh

echo "Setting up Intel Integrated GPU acceleration..."

# Install OpenCL runtime
sudo apt-get update
sudo apt-get install -y intel-opencl-icd

# Configure environment
echo 'export INTEL_OPENCL_CONFIG=/etc/OpenCL/vendors/intel.icd' >> ~/.bashrc

# Test GPU access
clinfo | grep "Device Name"

echo "Intel Integrated GPU setup complete!"

Advanced Intel GPU Setup for AI Workloads

Building llama.cpp with Intel GPU Support

For optimal Intel GPU performance with AI models, build llama.cpp with SYCL support:

# Install build dependencies
sudo apt-get install -y build-essential cmake libcurl4-openssl-dev

# Clone llama.cpp
git clone https://github.com/ggerganov/llama.cpp.git
cd llama.cpp

# Source oneAPI environment (required for SYCL build)
source /opt/intel/oneapi/setvars.sh

# Build with SYCL support
rm -rf build
mkdir -p build && cd build
cmake .. -DGGML_SYCL=ON -DCMAKE_C_COMPILER=icx -DCMAKE_CXX_COMPILER=icpx
make -j$(nproc)

Testing Intel GPU Acceleration

# Download a sample model
mkdir -p ../models
cd ../models
wget https://huggingface.co/Qwen/Qwen2.5-0.5B-Instruct-GGUF/resolve/main/qwen2.5-0.5b-instruct-q8_0.gguf

# Test inference with GPU offloading
cd ../build
source /opt/intel/oneapi/setvars.sh
./bin/llama-cli \
    -m ../models/qwen2.5-0.5b-instruct-q8_0.gguf \
    -p "Hello, how are you?" \
    -n 128 \
    -ngl 999  # Offload all layers to GPU

Troubleshooting

Common GPU Issues

GPU Not Detected in WSL

# Check WSL version
wsl --list --verbose

# Ensure WSL2 is being used
wsl --set-version Ubuntu-24.04 2

# Check GPU support
wsl --status

Driver Compatibility Issues

1. Update Windows: Ensure Windows 11 is fully updated
2. Update WSL: wsl --update
3. Reinstall drivers: Remove and reinstall GPU drivers
4. Check compatibility: Verify GPU supports WSL2 virtualization

Intel GPU Specific Issues

# Check OpenCL installation
clinfo

# Verify oneAPI environment (if installed)
source /opt/intel/oneapi/setvars.sh
sycl-ls

# Check permissions
groups $USER
# Should show 'render' in the list

Performance Issues

1. Memory allocation: Increase WSL memory in .wslconfig
2. Processor allocation: Allocate more CPU cores
3. GPU memory: Ensure sufficient GPU VRAM
4. Background processes: Close unnecessary applications

GPU Status Verification

NVIDIA GPU

# Check GPU status
nvidia-smi

# Check CUDA availability
nvcc --version

# Test CUDA functionality
cuda-install-samples-12.4.sh ~
cd ~/NVIDIA_CUDA-12.4_Samples/1_Utilities/deviceQuery
make
./deviceQuery

Intel GPU

# Check OpenCL availability
clinfo

# Check GPU information
lspci | grep -i vga

# Test OpenCL functionality
sudo apt-get install -y ocl-icd-opencl-dev

Performance Optimization

WSL Configuration (.wslconfig)

[wsl2]
gpuSupport=true
memory=32GB
processors=16
swap=8GB
localhostForwarding=true

Environment Optimization

# Add to ~/.bashrc
export CUDA_CACHE_DISABLE=0
export CUDA_CACHE_MAXSIZE=1073741824
export INTEL_OPENCL_CONFIG=/etc/OpenCL/vendors/intel.icd

# For oneAPI users
echo 'source /opt/intel/oneapi/setvars.sh' >> ~/.bashrc

GPU Memory Management

• NVIDIA: Use nvidia-smi to monitor GPU memory usage
• Intel: Monitor through Windows Task Manager
• Optimization: Close unnecessary GPU applications

Support and Resources

Official Documentation

• NVIDIA CUDA Documentation
• Intel OpenCL Documentation
• Intel oneAPI Documentation
• Microsoft WSL GPU Support

Community Resources

• NVIDIA Developer Forums
• Intel Community Forums
• WSL GitHub Issues

Troubleshooting Tools

• GPU-Z: Detailed GPU information and monitoring
• MSI Afterburner: GPU monitoring and overclocking
• HWiNFO: Comprehensive system information
• Windows Performance Monitor: System performance analysis

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Last Updated: October 3rd, 2025 Version: Compatible with Kamiwaza v0.5.1 Support: Contact our support team