SketchUp GPU Rendering

What is GPU rendering? 

GPU rendering means, that there is used the power of GPU (Graphics card) for rendering, instead of CPU (processor).

Conventional CPUs (Intel, AMD) didn’t make such dramatic progress, like GPUs in last 10 years. What is GPU rendering – NVIDIA article.

GPU rendering is definitely the future of rendering. One single customer GPU has the same power as the huge and expensive Features selection in reflections computer clusters with many CPUs.

GPU rendering is incredibly fast and less power hungry. Since you will need fewer computers for the same performance, it is also much CHEAPER.

Which is faster GPU or CPU Rendering?

As GPU render engines become more popular and feature rich, you may be thinking that it’s time to jump in and integrate GPUs into your workflow. The driving force behind a migration to GPU rendering has always been speed. SketchUp users frequently ask, “How much faster is GPU rendering as compared to CPU rendering?” This article by BOXX may provide some insight: GPU Rendering vs. CPU Rendering

GPU Rendering for SketchUp

These Rendering Engines for SketchUp say that they use the GPU for Rendering:

(Source: SketchUp Extension Warehouse)

Allura GPU

Allura GPU – Powered by NVIDIA Iray® – is a new GPU based renderer which utilizes the power of you GPU to create faster renderings.. – is the latest, GPU based rendering engine for SketchUp.

Using your video board GPU lets us achieve amazing rendering speeds, a high quality rendering image  and a satisfying rendering experience.

NVIDIA Iray is a physically based 3D renderer which uses the power of your GPU – Graphics Processor to perform the rendering.


Allura sample scene.png


Raylectron utilize all the CPU cores and threads (user selectable) to render as fast as possible and new GPU version available.

Bloom Unit

Bloom Unit performs all processing in the Cloud using powerful NVIDIA GPU technology.


Thea for SketchUp is a combination of powerful rendering engines of Thea with the simplicity of SketchUp. Having biased, unbiased and interactive render modes (including GPU support)

More on GPU Rendering


GPU-accelerated computing is the use of a graphics processing unit (GPU) together with a CPU to accelerate deep learning, analytics, and engineering applications. Pioneered in 2007 by NVIDIA, GPU accelerators now power energy-efficient data centers in government labs, universities, enterprises, and small-and-medium businesses around the world. They play a huge role in accelerating applications in platforms ranging from artificial intelligence to cars, drones, and robots.


GPU-accelerated computing offloads compute-intensive portions of the application to the GPU, while the remainder of the code still runs on the CPU. From a user’s perspective, applications simply run much faster.

How GPU Acceleration Works

GPU vs CPU Performance

A simple way to understand the difference between a GPU and a CPU is to compare how they process tasks. A CPU consists of a few cores optimized for sequential serial processing while a GPU has a massively parallel architecture consisting of thousands of smaller, more efficient cores designed for handling multiple tasks simultaneously.

GPUs have thousands of cores to process parallel workloads efficiently

GPU Vs GPU: Which is better?


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