When you spin up a virtual machine on Google Cloud and attach a powerful GPU like an NVIDIA H100, A100, or L4, you’re tapping into incredible processing power. But your journey isn’t quite over. To unlock that power, you need to install the correct driver.
It’s a crucial step, and it’s not a one-size-fits-all situation. NVIDIA offers two primary types of GPU drivers for their GPUs, each tailored for very different tasks: the standard drivers for AI and compute workloads, and the specialized drivers for Virtual Workstations that can handle graphics-heavy applications. Do not confuse the virtual workstations with Cloud Workstations which offer hosted developer environments, though without the full remote desktop experience. You can read more about the difference between Cloud Workstations and Virtual Workstations in a separate post.
Choosing the wrong one can be confusing at best and a non-starter at worst. Let’s break down the differences so you can pick the right one, every time.
The Two Paths: AI/Compute vs. Virtual Workstation
At a high level, the choice is simple: are you doing “headless” number-crunching, or do you need to see and interact with a graphical desktop?
1. Standard GPU Drivers (For AI & Compute)
These are the default, high-performance drivers you’ll use for the majority of GPU-accelerated tasks on the cloud. They are optimized to shuttle massive amounts of data to the GPU for parallel processing, without any overhead for graphical display.
This is the driver you’ll use for headless (non-graphical) workloads. Think of it as the powerhouse for pure computation.
Primary Use Cases:
- AI/ML Training & Inference: Running frameworks like TensorFlow, PyTorch, and JAX.
- High-Performance Computing (HPC): Scientific simulations, financial modeling, and complex data analysis.
- Data Processing: Accelerating data science libraries with NVIDIA RAPIDS.
- Video Transcoding: Batch processing video files.
How to Install: You typically follow the guide for installing standard NVIDIA GPU drivers.
2. NVIDIA RTX Virtual Workstation (vWS) Drivers
These are specialized drivers, previously called “GRID” drivers. They are designed to do something completely different: turn your cloud VM into a high-end, interactive desktop that you can stream to your local machine.
These drivers enable software like HP Anyware, Parsec, RustDesk or IAP Desktop to capture the rendered desktop and send it to you with low latency, allowing you to run graphically-demanding applications remotely as if they were on your local desk.
Primary Use Cases:
- 3D Modeling & CAD: Running applications like AutoCAD, Maya, Blender, or SolidWorks.
- Video Editing & Visual Effects: Using Adobe Premiere Pro, After Effects, or DaVinci Resolve.
- Game Development: Building and testing game assets in engines like Unreal Engine or Unity.
- Scientific Visualization: Interacting with complex 3D medical or geological data.
How to Install: This involves a different process for installing NVIDIA RTX Virtual Workstation drivers.
How to Choose: A Simple Guide
Here’s a simple cheat sheet to help you decide.
Choose the Standard GPU Driver if:
- You are training an AI model.
- You are running batch inference jobs.
- You are doing HPC or scientific simulations.
- You do not need to see or interact with a graphical desktop (you’re primarily using SSH).
Choose the NVIDIA RTX Virtual Workstation (vWS) Driver if:
- You need to run graphical applications (like Maya, AutoCAD, Adobe Creative Suite).
- You need a high-performance, remote desktop experience.
- Your work is visual, interactive, and requires a “screen.”
A Note on Licensing and cost of multi-purpose GPUs
This is where things can get confusing, but it’s an important distinction. Some versatile GPUs, like the NVIDIA L4 or T4, are excellent at both AI inference and graphics. However, the driver you use dictates its function and, critically, its cost.
- If you attach an L4 GPU and install the standard driver, it’s ready for AI workloads. You pay for the VM and the GPU runtime — that’s it.
- If you want to use that same L4 GPU as a virtual workstation, you must enable the NVIDIA RTX Virtual Workstation (vWS) license when you create the virtual machine.
This is a paid service, as it includes the license from NVIDIA to use their vWS technology. The good news is that Google Cloud handles all the complex licensing for you. The cost for the vWS license is simply bundled into your VM’s hourly price. There’s no separate marketplace subscription or license server to manage.
The Future is Flexible
Choosing the right driver is the key to unlocking your GPU’s full potential on Google Cloud, whether you’re crunching petabytes of data for an AI model or designing the next blockbuster film.
And the hardware options are only getting better. Keep an eye out for the new NVIDIA RTX PRO 6000 Blackwell Server professional GPUs, which are coming to Google Cloud (currently in preview for selected customers). These powerful cards are designed from the ground up to excel at both demanding AI workloads and high-fidelity virtual workstation tasks, offering even more flexibility for your most ambitious cloud projects.
Source Credit: https://medium.com/google-cloud/google-cloud-gpu-drivers-explained-b9f7bbeeeaa5?source=rss—-e52cf94d98af—4
