WHAT IS GPU VIRTUALISATION?

In 2025, as edge computing and AI become ever more pervasive, the need to maximise hardware performance across multiple domains is accelerating. GPU virtualisation is now a foundational technology, reshaping industries from automotive to cloud gaming. But what exactly is GPU virtualisation, and why is it so essential today?

WHAT IS GPU VIRTUALISATION?

At its core, GPU virtualisation is the process that allows multiple virtual machines (VMs) or operating systems to share the same underlying physical GPU resources. Each VM is allocated its own isolated environment, behaving as if it has exclusive access to the GPU, while actually operating alongside others on the same hardware. This virtualisation is managed through sophisticated hardware and software controls that ensure stability, performance, and security.

The ability to share GPU resources in this way unlocks powerful benefits, enabling advanced multitasking across a wide range of applications, from Edge AI inference at the device level to complex automotive compute environments and large-scale cloud infrastructure. Critically, these shared workloads can run in parallel without compromising real-time performance, safety requirements, or system responsiveness.

As AI and compute demands intensify, and as device manufacturers seek to consolidate processing functions into fewer chips, GPU virtualisation stands out as a key enabler of efficiency, flexibility, and scalability.

HOW GPU VIRTUALISATION HAS EVOLVED

Initially, virtualisation was handled entirely in software. Techniques like device emulation and para-virtualisation allowed VMs to interact with GPUs, but at the cost of performance and complexity. These methods required powerful CPUs and custom hypervisors to manage the overhead. 

The real breakthrough came with hardware-based GPU virtualisation, where support is embedded directly in the GPU silicon. This allows systems to achieve near-native performance and improved security, crucial in modern semiconductor system designs. Our GPUs feature full hardware virtualisation using our proprietary HyperLane architecture.

Learn more in our in-depth white paper on GPU virtualisation. 

WHY GPU VIRTUALISATION IS CRUCIAL IN 2025 AND BEYOND

As we move into a new era of compute where edge devices, AI workloads, and connected systems demand more power and flexibility, the ability to share GPU resources securely and efficiently has never been more important. GPU virtualisation is no longer a nice-to-have; it’s a foundational technology enabling safer, smarter, and more scalable devices across automotive, cloud, and consumer markets.

With hardware-level support like our HyperLane technology, virtualised GPU performance now meets the real-time demands of tomorrow’s applications.

How GPU Virtualisation Delivers Real-World Impact

• Consolidated compute for automotive: Run ADAS, infotainment, and digital dashboards on a single chip while maintaining safety and isolation.
• Scalable cloud gaming infrastructure: Share GPU power between multiple gamers or sessions without compromising gameplay quality.
• Secure consumer experiences: Isolate workloads on smart TVs and set-top boxes to support AI tasks and multi-tenant security.
• Reduced system costs: Decrease hardware requirements by maximising GPU utilisation across virtualised environments.
• Future-ready AI processing: Support mixed workloads in edge AI systems with real-time guarantees and fault isolation.

Let’s expand on some of these:

AUTOMOTIVE GPU VIRTUALISATION FOR ADAS & INFOTAINMENT

In modern vehicles, computing power is increasingly consolidated into a single, software-defined system-on-chip (SoC) that must seamlessly manage safety-critical workloads like Advanced Driver Assistance Systems (ADAS) alongside infotainment and digital cockpit functions. GPU virtualisation enables this by creating isolated GPU environments for each domain ensuring that a spike in route-planning computations or media playback doesn’t affect the performance or safety of other systems.

Hardware-accelerated GPU virtualisation ensures that each workload operates with near-dedicated efficiency and reliability, while maintaining robust separation and preventing resource contention. This capability is particularly vital as ADAS systems leverage machine learning and high-resolution sensor fusion, requiring both intensive compute and low latency.

Did you know… The global ADAS software market is projected to grow from USD 50.1 billion in 2025, at a compound annual growth rate (CAGR) of 16.5 % through 2029. 

As OEMs race to integrate more sophisticated ADAS features, the ability to virtualise GPU resources becomes a strategic advantage, enabling cost-effective, safe, and scalable deployment across vehicle lines.

^{An example of GPU multitasking in automotive using Imagination’s HyperLane virtualisation technology}

CLOUD GAMING AND DATA CENTRE SCALING WITH VIRTUAL GPUS

Cloud gaming and hyperscale compute are two of the fastest-growing sectors placing pressure on modern GPU infrastructure. Providers are under increasing demand to deliver high-performance, low-latency experiences, often to thousands of concurrent users or AI-driven services, all while maintaining cost and energy efficiency. GPU virtualisation allows a single physical GPU to be shared across multiple cloud gaming sessions or virtual machines, dynamically adjusting resource allocation in real time to meet changing demands.

This makes it possible to serve multiple users or processes from a single piece of silicon, significantly reducing the number of discrete GPUs required. With hardware-accelerated virtualisation, such as Imagination’s HyperLane technology, providers can maintain smooth frame rates, protect user data with strict isolation, and scale performance seamlessly.

Did you know… The global data centre GPU market is expected to grow from roughly US $21.8 billion in 2025 to about US $192.7 billion by 2034, expanding at a CAGR of 27.5 %, driven by AI, cloud gaming, and enterprise workloads.

In this landscape, GPU virtualisation isn’t just an enhancement, it’s a competitive necessity. It empowers gaming companies, cloud providers, and enterprise data centres to scale securely, improve utilisation, and reduce capital and operational expenses.

^{An example of forty four gamers running on the same processor using GPU virtualisation}

VIRTUALISATION FOR SMARTER, SAFER CONSUMER DEVICES

In smart TVs, set-top boxes, and other connected devices, GPU virtualisation plays a critical role in enabling modern multimedia and AI-rich experiences while keeping content secure. By partitioning GPU resources across isolated environments, manufacturers can ensure that content from streaming providers, broadcast channels, or third-party applications remains protected from unauthorised access or interference.

At the same time, virtualisation enables real-time multitasking, allowing AI functions such as voice assistants, on-screen recommendations, or visual enhancements to run alongside high-resolution video rendering. This means smarter, more responsive user experiences without performance trade-offs or security compromises.

Did you know… Global smart TV penetration is expected to surpass 1.1 billion households by 2026, reaching over 51% of households worldwide as consumer demand for integrated, intelligent entertainment platforms continues to grow.

As device intelligence increases, so does the need for flexible, secure compute. GPU virtualisation is the unseen enabler powering safer content delivery and smarter interfaces at the heart of modern living rooms.

IMAGINATION’S HYPERLANE: GPU VIRTUALISATION REINVENTED

At Imagination Technologies, we’ve spent over three decades solving the toughest challenges in graphics processing. From pioneering GPU architectures in embedded systems, to designing the GPU for the world’s first smartphone, and bringing ray tracing to mobile, we have continually pushed the boundaries of what is possible. Today, we are continuing that innovation at the edge, delivering high-performance, programmable AI and graphics solutions that meet the needs of modern compute.

Our HyperLane technology lies at the core of our GPU virtualisation solution. It provides:

• Support for up to 16 virtual machines (VMs) per core
• Full isolation between workloads for safety and security
• Maximum GPU utilisation across applications
• Real-time performance guarantees for critical systems
• Protection against denial-of-service (DoS) attacks

As the demand for secure, efficient and scalable compute accelerates, GPU virtualisation is quickly becoming essential. From enabling safer autonomous vehicles, to powering scalable cloud gaming and delivering AI-enhanced consumer devices, virtualisation is the foundation that tomorrow’s systems will be built on.

Want to explore how GPU virtualisation can unlock performance and efficiency for your next product? Download our in-depth white paper on GPU virtualisation to dive deeper into the technology, use cases and architecture behind HyperLane.