Does Nanite Use the GPU in Unreal Engine 5?

With the release of Unreal Engine 5 (UE5), Epic Games introduced several groundbreaking technologies, one of which is Nanite, a virtualized geometry system that allows developers to create and use highly detailed models without worrying about traditional polygon budgets or performance limitations. A common question among developers and enthusiasts is: Does Nanite use the GPU? The answer is a resounding yes! In fact, Nanite heavily leverages the GPU to achieve its impressive performance and visual fidelity. This blog post will dive into how Nanite uses the GPU and why this is so crucial for its functionality.

What is Nanite?

Before we delve into the details of GPU usage, let’s quickly recap what Nanite is. Nanite is a virtualized geometry system that allows developers to import film-quality assets with millions or even billions of polygons directly into Unreal Engine 5. Unlike traditional rendering methods that require developers to create multiple levels of detail (LODs) to optimize performance, Nanite automatically adjusts the detail level in real-time based on the camera’s distance and angle to the object. This dynamic adjustment enables highly detailed scenes to be rendered efficiently, eliminating the need for manual LOD creation and significantly reducing the development workload.

How Does Nanite Leverage the GPU?

Nanite is specifically designed to harness the power of modern GPUs. Here’s a closer look at how Nanite utilizes the GPU to achieve its impressive real-time rendering capabilities:

1. Dynamic LOD Generation on the GPU

One of the core features of Nanite is its ability to dynamically generate levels of detail (LOD) on the fly. Unlike traditional methods that use pre-generated LOD models, Nanite creates LODs in real-time based on the screen size and distance from the camera. This process is computationally intensive and relies heavily on the GPU.

Triangle Binning and Culling: Nanite uses a method known as triangle binning, where it divides complex geometry into clusters of triangles (called clusters). These clusters are then processed and culled based on the camera’s position and viewing angle. The GPU performs these operations extremely quickly, allowing Nanite to render only the visible triangles, thus reducing the amount of geometry that needs to be processed.
Micropolygon Rendering: Nanite’s rendering technique involves generating micropolygons, which are small triangles that represent the surface details of an object at varying levels of detail. The GPU dynamically adjusts the density of these micropolygons based on the screen size, rendering just enough detail to maintain visual fidelity without wasting resources.

2. Hardware-Accelerated Occlusion Culling

Nanite uses hardware-accelerated occlusion culling to determine which parts of the scene are visible to the camera and which are hidden behind other objects. Occlusion culling is a technique that prevents the rendering of objects that are not visible to the player, saving GPU resources.

Hierarchical Z-Buffer: Nanite employs a hierarchical Z-buffer technique, which is a GPU-accelerated method for determining depth. This technique quickly identifies which objects are occluded (blocked by other objects) and should not be rendered. By offloading this computation to the GPU, Nanite can efficiently cull large portions of the scene that do not contribute to the final image, significantly improving performance.

3. Parallel Processing and Compute Shaders

Nanite is designed to take full advantage of the parallel processing power of modern GPUs.

Compute Shaders: Nanite utilizes compute shaders, which are programs that run on the GPU to perform general-purpose computations. These shaders allow Nanite to process large amounts of geometric data in parallel, dramatically speeding up tasks like LOD generation, triangle binning, and occlusion culling.
Asynchronous Compute: Nanite leverages asynchronous compute capabilities of GPUs, meaning it can perform multiple tasks simultaneously without waiting for other processes to complete. This parallelism is essential for maintaining high frame rates in complex scenes with thousands of objects and millions of polygons.

4. Cluster-Based Rendering

Nanite’s architecture is built around a cluster-based rendering system. When an object is imported into Unreal Engine 5, Nanite breaks it down into clusters of triangles that are grouped together based on their spatial location and screen importance.

Cluster Rendering on the GPU: The GPU handles these clusters individually, determining which clusters are visible and at what level of detail they need to be rendered. This clustering approach allows Nanite to optimize GPU workloads by only rendering what is necessary, reducing the number of draw calls and ensuring efficient use of GPU resources.

5. Data Streaming and Memory Management

Efficient data management is crucial for Nanite’s performance, especially when dealing with high-polygon assets.

Virtualized Data Streaming: Nanite streams data from disk to GPU memory dynamically, loading only the necessary parts of the model that are visible to the player. This process is managed by the GPU, which ensures that memory usage is optimized and that only the required data is stored in the GPU’s VRAM (Video RAM). By dynamically loading and unloading data, Nanite prevents the GPU from being overwhelmed by the sheer amount of geometry data in complex scenes.

Why Is GPU Usage Important for Nanite?

Nanite’s reliance on the GPU is crucial for several reasons:

High Throughput and Parallelism: GPUs are designed for high throughput and parallelism, making them ideal for processing the vast amount of geometric data Nanite requires. This capability allows Nanite to render extremely detailed models in real time without causing performance bottlenecks.
Efficiency in Real-Time Applications: In real-time applications like video games or virtual reality, maintaining high frame rates is essential for a smooth and immersive experience. By offloading most of the heavy computations to the GPU, Nanite ensures that even the most detailed scenes can be rendered efficiently, providing consistent performance.
Maximizing Visual Fidelity: The GPU’s ability to handle massive amounts of parallel data processing allows Nanite to maintain high visual fidelity, even with extremely complex assets. This capability is particularly beneficial in next-generation games and simulations where realism and detail are paramount.

Conclusion

Yes, Nanite does use the GPU—and heavily so! By leveraging the power of modern GPUs, Nanite can dynamically manage and render billions of polygons in real time, achieving levels of detail previously only possible in offline rendering. Through techniques like dynamic LOD generation, hardware-accelerated occlusion culling, parallel processing, and efficient data streaming, Nanite harnesses the full capabilities of the GPU to deliver stunning visuals while maintaining optimal performance.

Nanite represents a significant leap forward in real-time rendering technology, allowing developers to push the boundaries of what’s possible in games and interactive experiences. As GPU technology continues to advance, the capabilities of Nanite—and the games and applications built with Unreal Engine 5—will only continue to grow.