How to Install NVIDIA Drivers on a GaaS Instance

In the era of high-performance computing and AI-driven workloads, GPU-accelerated servers have become the backbone of modern cloud infrastructure. According to recent industry reports, enterprises using GPU-enabled cloud instances are seeing up to 40% faster training times for AI and machine learning models compared to CPU-only servers. With the growing demand for graphics-intensive applications, AI workloads, and high-performance computing (HPC), GPU as a Service (GaaS) has emerged as a popular solution.

GaaS instances offer the flexibility of cloud hosting while providing dedicated GPU resources on-demand. However, to fully leverage these GPUs, installing the NVIDIA drivers correctly is critical. Improper installation can lead to performance degradation, hardware underutilization, or compatibility issues with AI frameworks like TensorFlow, PyTorch, and CUDA-based applications.

In this blog, we will guide you through how to install NVIDIA drivers on a GaaS instance, highlight the key considerations, and ensure your cloud GPU server is optimized for high-performance workloads.

Understanding the Importance of NVIDIA Drivers on GaaS

A GaaS instance typically provides access to powerful NVIDIA GPUs such as Tesla, A100, or Quadro series in a virtualized or dedicated cloud environment. While the instance itself is ready-to-use, the operating system does not automatically configure the GPU for compute workloads. NVIDIA drivers act as a bridge between the GPU hardware and the software stack, enabling:

Full utilization of GPU cores for parallel processing

Support for CUDA, cuDNN, and other AI frameworks

Hardware acceleration for rendering, deep learning, or simulation tasks

Compatibility with Windows or Linux-based cloud hosting instances

Without proper driver installation, your GaaS server may fail to detect the GPU, or workloads may revert to slower CPU-based computations, significantly affecting performance.

Prerequisites for Installing NVIDIA Drivers

Before installing NVIDIA drivers on a GaaS instance, ensure the following:

Instance Compatibility

Check that your cloud GPU instance supports NVIDIA GPUs and matches the driver version requirements.

Popular cloud hosting providers list compatible NVIDIA driver versions in their documentation.

Operating System Requirements

GaaS instances typically run Linux distributions (Ubuntu, CentOS, RHEL) or Windows Server.

Confirm the OS version aligns with the driver package.

Sufficient Permissions

You need root/admin access on the server to install drivers.

Updated System Packages

On Linux, ensure your OS packages are up to date using sudo apt update && sudo apt upgrade (Ubuntu) or yum update (CentOS).

CUDA Toolkit (Optional)

If your workloads include AI or HPC tasks, installing the CUDA toolkit after the driver ensures GPU-accelerated computation works seamlessly.

Step-by-Step Guide to Installing NVIDIA Drivers on GaaS

The installation process differs slightly based on the operating system of your GaaS instance. Below, we cover Linux and Windows environments for cloud GPU servers.

1. Installing NVIDIA Drivers on Linux GaaS Instances

Step 1: Identify Your GPU

Before installing drivers, verify the GPU model:

lspci | grep -i nvidia

This command lists all NVIDIA GPUs attached to the instance. Knowing the GPU model helps select the correct driver version.

Step 2: Remove Previous Drivers

If a previous NVIDIA driver exists, remove it to prevent conflicts:

sudo apt-get purge nvidia*   # For Ubuntu/Debian

sudo yum remove nvidia*       # For CentOS/RHEL

Step 3: Add NVIDIA Package Repository

Most cloud providers or Linux distributions recommend using NVIDIA’s official repository:

sudo add-apt-repository ppa:graphics-drivers/ppa   # Ubuntu

sudo apt update

For CentOS/RHEL, download and enable the NVIDIA repository RPM.

Step 4: Install the Driver

Check for recommended driver versions:

ubuntu-drivers devices

Install the driver:

sudo apt install nvidia-driver-525   # Replace 525 with recommended version

On CentOS/RHEL:

sudo yum install nvidia-driver-latest-dkms

Step 5: Verify Installation

After installation, reboot the server:

sudo reboot

Post-reboot, verify the driver and GPU status:

nvidia-smi

This command should display GPU model, driver version, memory usage, and active processes.

2. Installing NVIDIA Drivers on Windows GaaS Instances

Step 1: Download NVIDIA Drivers

Visit the official NVIDIA website or your cloud provider’s recommended driver page.

Select the correct GPU model, Windows version, and architecture (x64).

Step 2: Disable Windows Secure Boot (If Required)

Some Windows instances with UEFI may require secure boot to be temporarily disabled to install GPU drivers.

Step 3: Run the Installer

Execute the downloaded .exe file.

Choose Custom Installation → enable Clean Installation to prevent conflicts with older drivers.

Follow on-screen instructions and reboot the instance.

Step 4: Verify Driver Installation

Open Device Manager → expand Display Adapters → confirm NVIDIA GPU is listed.

Run NVIDIA Control Panel or nvidia-smi (via Command Prompt with CUDA toolkit) to verify functionality.

Best Practices for NVIDIA Drivers on GaaS Instances

Keep Drivers Updated

Regularly update NVIDIA drivers to fix bugs, enhance security, and improve GPU performance.

Cloud providers often release tested versions optimized for GaaS instances.

Use Compatible CUDA Versions

For AI workloads, ensure the driver version aligns with CUDA toolkit requirements.

Mismatched versions can cause runtime errors in ML/DL frameworks.

Monitor GPU Health

Use nvidia-smi on Linux or NVIDIA System Management Interface on Windows to monitor GPU usage, temperature, and performance.

Document Installation Steps

Enterprises running multiple cloud instances should maintain documentation to standardize GPU driver installation across all servers.

Backup Configurations

Before updating drivers, backup critical server configurations to avoid disruptions in mission-critical applications.

Conclusion

Installing NVIDIA drivers on a GaaS instance is a fundamental step for enterprises looking to leverage GPU acceleration for AI, machine learning, and graphics-intensive applications. Proper installation ensures full utilization of GPU resources, seamless integration with cloud-hosted Windows or Linux servers, and improved performance for high-demand workloads.

Whether you are running Windows Dedicated Servers, Linux-based cloud servers, or hybrid cloud GPU instances, following a structured approach to install NVIDIA drivers minimizes errors, ensures compatibility with CUDA and other frameworks, and unlocks the full potential of GPU acceleration.

By combining robust driver installation, monitoring, and best practices, enterprises can maintain a high-performance, secure, and reliable GPU-enabled cloud hosting environment—empowering their applications and workflows to run at maximum efficiency.