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Are you confused about sticking with your old CPU-based rendering engine or acquiring the latest GPU rendering unit?
Well, it’s a difficult choice for many creators in the graphic computing industry.
However, through our in-depth research, we’ve found that one is best for commercial rendering where speed is a factor, whereas the other suits quality-oriented creators with enough time in their hands.
Let’s take a deep dive into their operational features and how they impact rendering.
Value-focused projects where deadlines are not strict, i.e., film industries
High-end commercial processing where speed is a concern
Graphics Processing Units (GPUs) is a new rendering technology taking over from the traditional CPU rendering. These GPUs are specialized models of microprocessors that can run alongside the CPU.
GPU processors will handle intensive applications such as:
- 3D animation
- Deep learning
- Image processing
- Visual effects (VFX)
- Big data
In case your focus is on quality-clear images with less noise, then CPU rendering is what you need. CPU Rendering may be slow, running for several hours or days but with final quality image creations.
For real-time visualization at accelerated speeds, GPU rendering will work well in driving viewpoint performance in the software to allow for real-time viewing, manipulation of lighting, and 3D framing.
Although the benefits of GPU rendering out-weigh CPUs by far, technologists did not make GPUs to replace the traditional CPU renderers. These two processing units live and work in symbiotic harmony for enhanced graphical productions.
Why Do GPUs Exist?
GPUs came in to accelerate existing rendering practices, maximize production, and relieve CPUs from heavy processor tasks that may slow down the system.
Otherwise, using these processing units together in your imagery creations will give seamless image rendering in your projects compared to deploying just one.
How GPU Rendering Works
To understand how GPU rendering works, you can relate it to how a swiss army knife works.
A swiss army knife is a multipurpose tool that will open your bottle of wine, cut food, has a pair of scissors to cut strings, and many more.
But, suppose you’re out on your daily chores, meet an accident, end up in the hospital, and an operation is needed. You’ll not expect the surgeon to flip up your swiss army knife and use it for an operation process on you, right?
The surgeon will use a surgical knife specialized for that particular task. So, although your swiss army knife is a multi-tasker, it may not help as much as the surgeon’s blade.
Similarly, just like the swiss army knife, computer CPUs are designed to perform several tasks simultaneously. These multipurpose machines will enable you to listen to music, open spreadsheets, and browse multiple web pages simultaneously.
Your CPU can handle all these activities with less hassle.
However, GPUs are there for one critical focus - to render graphics, which includes a parallel tabulation of millions of similar calculations at the same time.
Unlike CPUs that execute tasks by assigning each process to a single core, GPUs will take one instruction and spread it across several cores for faster processing.
These cores can focus on a task or perform several tasks three times faster than the CPU. Generally, CPUs work similarly to GPUs. But the latter put more emphasis on parallel processing (handling more data simultaneously for faster visual creations).
Remember, modern GPUs, which are already becoming popular, can do more than just graphics processing. Technology has seen the introduction of General Purpose Graphic Processing Units (GPGPUs). These GPGPUs can perform computations that were initially a reserve for CPUs.
How CPU Rendering Works
We’ve seen that CPU and GPU renderers can perform the same graphics processing tasks at varying efficiency levels. However, CPU renderers, also known as render engines or software rendering, are the industry’s standard rendering units and remain the first to be used in image rendering.
CPU rendering works by converting data input from the CPU directly to the GIU. CPU-based rendering is an independent process that does not involve the support of a graphics card.
Data processing is by one core at a time and may take longer. Unlike in GPUs with many cores where each thread will work on up to 30 blocks of data, CPU-limited cores will assign one thread to one block of data at a time.
Although limited in terms of core count, a single core in a GPU is slower than one core in a CPU. Additionally, CPU renderer has high levels of cache, gives quality images, which to date makes them a favorite for most industry professionals.
Relevant Characteristics Between CPU and GPU Rendering
Up to 768 GB RAM
Up to 80 GB RAM
Stable-integrated in the system
Less stable-Independent unit
Clearer and less noisy
Less clear images
Integrated into the system-Expensive
Similarities and Differences
CPU and GPU renderers work at different efficiency levels both in terms of speed and image quality.
This section will identify the major distinguishing features between the two processing units and other features that they have in common.
CPU and GPU Rendering Differences
Take a look below at some of the differences between cpu and gpu:
Most professionals and artists are concerned about rendering speed, which varies sharply between CPUs and GPUs. CPUs have a limited number of cores (average 24) which makes them slower at image rendering.
On the other hand, GPUs come with numerous small cores of between 2000-3000. These cores focus on parallel computation during execution, making them up to three times faster than the CPUs.
CPUs have broader memory support of up to 768GB RAM. Since CPUs are multitaskers, the more expansive memory allows smooth operations when running other programs alongside image rendering.
On the contrary, the highest memory in a modern GPU can only go up to 80GB RAM. The GPU memory will not stack up even if you add more GPU renderers, unlike the CPUs.
So, be careful when adding more GPU renderers lest you risk compromising your present render engine’s performance.
CPU renderers are in-built (integrated into the computer system). The integration makes these processing units very stable and reliable, giving the user a smooth experience.
On the other hand, GPU renderers are external components prone to heating up and may crash your system if there is poor integration. These renderers will also require frequent driver updates, which may slow down operations.
Image quality is essential in any rendering process. A CPU renderer is an integrated unit that will produce highly improved images compared to GPU renderers.
Setting up a GPU rendering firm with studio-quality production is much affordable compared to a CPU rendering firm. Apart from the high speed, a GPU is at least five times more potent than a CPU.
The high speeds here mean a single GPU workstation will perform several CPU workstation tasks, which saves on space further, making it even more cost-effective.
The above comparison shows a win-win scenario with CPUs carrying the day in terms of stability and image quality. At the same time, GPUs are more cost-effective and fast at rendering.
CPU and GPU Rendering Similarities
Check the things that cpu and gpu have in common:
The GPU-based units are famous for their fast rendering that takes a few minutes to several hours depending on the task. Thanks to the numerous cores and the parallel computation focus.
However, that does not mean that CPU-based rendering cannot compete with GPUs in speed. Keep in mind that GPUs have thousands of cores which are less powerful compared to CPU cores.
Therefore, interconnecting a few CPU-based units will complete a rendering process in equal duration or even faster than a GPU unit.
A CPU and GPU-based renders can work mutually to improve both the images and lighting quality at an accelerated speed. The CPU hosts the program, while GPU with higher core numbers complements the rendering process by speeding it up.
Advantages of CPU Rendering
Here are some benefits of CPU rendering:
Can Handle Complicated Projects
High processing speed in GPUs results from directing big chunks of data in the same direction for repeated processing.
Leveraging these high speeds that GPUs are known for requires the user to process larger volumes of data with similar execution requirements.
On the other hand, CPUs come with a broader memory that will handle several computation tasks simultaneously without feeling overload or fatigue. An ideal CPU rendering example is an architectural project which may require separate rooms to design differently.
Initial Graphics Fidelity
If patience is your portion and you have no pressure of meeting any deadlines, then CPU-based renders are for you.
The integration of CPUs into the computer atmosphere, coupled with powerful cores, will render exquisite final images compared to GPU-based rendering solutions.
Most film producers use CPU rendering to produce high-quality images and frames. They’ll interconnect several CPUs where both speed and quality are required.
Poor integration of a GPU into a computer system can easily lead to system crashes. However, CPUs are part of the system that makes them stable and reliable without fear of overheating, leading to crashing.
The vast CPU memory of up to 768 GB RAM in a single pc offers enough room for rendering while the machine still focuses on other computations without straining.
The primary reason professionals and other creators have continued to use CPU-based rendering engines is the hyper-clear image output.
However, CPU-based rendering engines have remained unreliable in speed for a long time due to the multi-tasking nature.
You’ll need to interconnect several CPUs to match GPU-based rendering speeds. That process can be expensive. Therefore, their GPU-based counterparts are quickly becoming a favorite to many creators and will likely take over the graphic processing industry in a few years.
However, you should note that GPU units can never replace CPUs fully. The main program runs in the CPU, and the GPU is there to complement the CPU architecture.
Advantages of GPU Rendering
If you decide to go with GPU rendering, you'll enjoy:
Quick rendering is among the top reasons why professionals and other artists use GPU-based graphics solutions. These GPUs have many cores and also use parallel computation to finish tasks faster.
Modern GPUs will execute tasks 100 times faster where the process requires the same type of execution.
The GPU-accelerated machines will enable you to view and manipulate lights and frame dimensions in real-time. Some GPUs will even allow you to work in an entirely rendered viewpoint.
In such a case, you’ll minimize potential errors common when rendering in a different program. Using these GPUS will also maximize your general output. Thanks to their exclusive rendering software.
You’ll need just one GPU rendering workstation to perform a task that would require up to five CPU renderers to do. Besides, these are external components that offer an opportunity for upgrading in the future.
With just a fraction of a CPU render firm cost, creators can get reliable GPU workstations with studio-quality performance.
As the graphic industry continues to grow, the need to process big chunks of data and other complex computing tasks has also increased. Rendering engines create task-intensive 3D visuals, games, and other GPU-based cloud computations.
Such processes require dedicated resources and heavy processing power that only GPU-based renderers can provide. Combined with the GPU high speeds, the production will be fast and with realistic image creations.
GPU renderers are becoming more popular due to the constant evolution they’ve continued to experience. Manufacturers are finding new ways to improve previous limitations while also looking for ways to strengthen these rendering engines.
Introduction of General Purpose Graphic Processing Units (GPGPUs) is one proof of evolution. GPGPU engines can render images at high speeds while also carrying out other computation tasks.
GPU-based render engines are thus poised for further and quicker growth, judging by what they have achieved so far. The introduction of GPGPU was a significant milestone in addressing some of its limitations.
Users should expect further developments that may focus on image clarity or system stability and increased memories, which remain the most significant setbacks until today.
CPU vs GPU Rendering Comparisons
The following section will discuss how GPU and CPU rendering compare when paired with some popular computer graphic software.
Finally, the latest beta version of blender 2.80 is out. Blender 2.79 is an improvement from the early alpha Blender 2.80. Both CPU and GPU hybrid rendering work well with consistent results, both in lighting and image clarity.
The results remain the same, whether on CPU-rendering only or GPU. The inclusion of the new GPU in the upgraded version has had a tremendous impact in optimizing the entire rendering engine.
The hybrid model does not use all the CPU threads, and render time can vary depending on the number of tiles assigned to the CPU or GPU. Users should look forward to improved performance on blender 2.92.
Graphic designers, professional creators, hardware reviewers, and other manufacturing firms have used the V-Ray Benchmark application to test their innovations.
Although V-Ray hybrid will render on GPUs and CPUs simultaneously, the GPU cores and CPU cores are not equal. For instance, a GPU with 2560 cores cannot be 320 times faster than a CPU with eight cores. Real-world benchmarking tests are required to determine the actual speed.
In 3Ds Max
The primary difference when comparing CPU and GPU rendering is speed and accuracy. While CPU-based renderers are more accurate, their GPU counterparts are faster.
The 3D max comes with some in-built render engines, which use both the CPU and GPU rendering for a more enhanced output in terms of speed and clarity.
Picking the proper renderer narrows down to the nature of your rendering needs. While CPU renderers are still preferred and trusted for quality image creation, GPUs have many benefits and are poised to take over the professional rendering industry in the future.
Maintaining a GPU is affordable for those who are into high-level animation compared to CPU-based rendering. If speed is your primary focus, as is the case for some creators, you may consider a GPU with software specifications that align with your CPU.
Proper software alignment with the GPU will give you high-quality image creations at higher speeds.
People Also Ask
Some professional designers and private creators still have difficulty on what features make an excellent renderer in a CPU or a GPU.
Below are some common questions from graphics processing artists.
Does CPU Matter for Rendering?
A CPU renderer will take more hours or days to complete a task a GPU can do in a few minutes or hours. However, interconnecting a few CPUs will give faster and more explicit images than a GPU. Also, aligning the right CPU with the right GPU gives better visual creations.
So, a CPU choice for your rendering project will impact your images and other graphical creations. More cores and hyperthreading in the CPU equals higher performance.
What Will Happen If I Force GPU Rendering?
GPU renderer is an external component introduced to the computer system to work in harmony with other graphical processes. Proper installation that includes software compatibility is among the crucial factors to consider.
Forcing a GPU rendering may cause the system to overheat and crash. In some cases, where the apps are not compatible, the rendering process may be slower than the CPU-based engines.
How Many Cores Do I Need for Rendering?
The number of cores needed for rendering may depend on a few factors that include the magnitude of the rendering workload, how long you intend to use the render engine, and the type of rendering (CPU/GPU-based).
Generally, a laptop with 32GB of RAM and four cores is enough for entry-level rendering. Whether for GPU or CPU-based rendering. For-high end commercial rendering, you may need as high as over 200GB of RAM.
Is 8GB RAM Enough for 3D Rendering?
Considering that rendering can work with as little as one core, 8GB RAM will give a 3D rendering but at an extremely low speed. To improve the process, you may need to get a CPU with many cores or with hyperthreading. But, 8GB RAM will still be limited to light rendering tasks.
Does Rendering Use CPU Or GPU?
Initially, CPUs were the only rendering engines in the image creations. The graphics processing industry’s rapid growth needed quick solutions, focusing on image creations, hence GPUs’ introduction.
Today, rendering is done only with two processing units- CPUs and GPUs, which you can choose from depending on individual needs.