What is Graphics Rendering?
Graphics rendering refers to the process of creating a photorealistic or non-photorealistic 2D/ 3D image by a computer program using the information contained in a source file. This information describes the scene lightning, shading, textures, viewpoint, 2D/ 3D geometry, etc. Highly realistic rendering even considers the interplay of light and shadows bouncing off various objects in the scene! As is evident, the final image/ video output is governed by strict mathematical calculations, generally performed by specially designed graphics cards.
Graphics Processing Units (GPUs) are standalone components and constitute a major upgrade over the discrete graphics cards. The entirety of the information stored in the source file is routed from the Central Processing Unit (CPU) to the graphics card or the GPU. But the CPU itself can also undertake graphics rendering when required.
Apart from movies and visual effects, graphics rendering has applications in engineering design simulation, architecture, game development, meteorological and astronomical research and visualization, etc.
Realistic rendering using GPUs (Source: Nvidia)
What are Ray Tracing and Ray Casting?
A very large number of mathematical computations and calculations are set in motion behind the scenes to display a high-definition, realistic image. Every frame in a video or an animation is effectively an image rendering, whose individual elements must be computed and displayed in fractions of a second.
This is indeed a complex process especially if you consider the light bounce effect required for 3D rendering. This is called ray tracing and ray casting and, in many ways, is very similar to the natural light in real life. Both these methodologies seek to visualize 3D objects as they would appear to an actual individual, considering all factors such as illumination, diffused lights, reflection and refraction, etc.
The quality of ray tracing directly depends upon the rendering program you use or whether the CPU or the GPU will handle this task. There are also many hybrid render engines that leverage both the CPU and the GPU for ray tracing, like V-ray.
Spot the Difference: Ray Tracing in Cyberpunk 2077 (Source: Nvidia)
Covering the Basics: What are the Roles of CPU and GPU?
CPU and GPU, both have their niche.
One can confidently assert that the CPU is both the brain and the lifeblood of any computer, given its inevitable role in executing the entire spectrum of system processes, from managing every application (including the OS!) to running firewalls and undertaking image/ video rendering
The GPU, as the name itself is self-explanatory, was designed to efficiently handle high-res graphics rendering but has now also branched off into complimenting the CPU by offloading some of the processor-intensive tasks which can be segmented into smaller, parallelizable operations.
Mostly, it is the GPU’s hundreds/ thousands of parallel processing cores that deliver superlative performance when dealing with complicated calculations involved in high-res graphics rendering as well as AI/ ML model development. Thus, a GPU effortlessly outshines a CPU with its massive parallel-processing capabilities.
Is GPU faster than CPU for Graphics Rendering?
Chances are that if you have reached here, either you are a high-definition VFX fan or have an interest in graphic design or are into industrial designing. In which case, it is imperative to understand the critical decision you are about to make – the choice between CPU or GPU for your rendering needs. It is this decision that will orchestrate the make and capabilities of the workstation that you will use for your rendering workloads.
Speed performance CPU vs GPU for graphics rendering is not a complicated question at all!
GPU rendering can be 50-100 times faster than CPU rendering across benchmarks. What the CPU can deliver in hours, the GPU can deliver in minutes – a train journey vs taking a flight! Both are good, but the quality and the time taken are the most significant metrics that you as an animator must consider.
WYSIWYG: GPU vs CPU, along with time taken for generating the graphics (Source)
Which Other Metrics to Consider?
Wait! The discussion is not over yet. Rendering speed is not the only metric you must consider. Quality matters too! So does the cost!
Let me take you for a deep dive into the world of processors – CPU & GPU – and let us examine the differentiating parameters, outcomes and technicalities before making an informed decision:
*The grid is to be converted into an image.
| CPU | GPU |
| Complex tasks are a cakewalk! ⦁ When the data sets are complex, sequential or interspersed with dependencies, computation requires separate instructions. Syncing them all up becomes paramount, which is what the CPU excels at. Furthermore, the availability of more system RAM than VRAM allows the CPU to handle more extensive rendering effectively. ⦁ However, with fewer processing cores, the rendering takes longer. | Fast Rendering ⦁ More efficient VRAM availability lets larger instruction sets and data to be loaded on to the GPU. Furthermore, the parallel processing cores can simultaneously perform the same operations across multiple data sets, accelerating rendering manifolds since each pixel can be independently handled and then collated, thus optimizing time as well as consistency. Infact, a single GPU can outperform several CPUs! However, when there are sequential instructions or non-parallelizable operations, or VRAM limitations, the numerous cores are helpless. |
| Large Memory ⦁ The CPU has access to the entirety of system memory. In case of excessively heavy workloads like render engines and photorealistic animations, the system speed can take a hit. ⦁ The GPU has access to considerably less memory and is also straitjacketed by the memory bandwidth, but nonetheless is capable of handling far more sophisticated rendering/ animation workloads vis-a-vis the CPU. Handling workloads that exceed the VRAM availability can complicate matters, but this can be easily remediated by shifting to an enterprise-class GPU via a Cloud service provider. | Professional-level Rendering ⦁ If you want to render 3D like a pro in your animation studio, at speed, without compromising on any intricate detail (like glossy finish, shadows, reflections, and field depth to name a few), GPU is your go-to processor. Its ray tracing capabilities help you deliver studio quality output – at reasonable cost! ⦁ A small studio set-up or independent/ freelancer content creators are better off accessing Cloud GPU resources rather than investing in capital intensive CPU render farms |
| Cost and license limitations ⦁ GPUs are exorbitantly priced. Moreover, for individual creators and small enterprises, the need to regularly update GPU software drivers and other licensing costs, can prove insurmountable. ⦁ In contrast, the CPU can be depended upon for versatile operations without worrying about updates or licensing or incompatibility with common render software. | Flexibility ⦁ GPU allow both scaling up and scaling out. Adding RAM or memory to a CPU maybe easier, but the scale that multiple GPUs deliver is unprecedented. Moreover, deploying one or more GPU to perform operations equivalent to several CPU consumes significantly less electricity. Thus, there is reduction in electricity as well as maintenance expenses down. ⦁ Note that each additional GPU requires an additional license and would have to be doubly checked for the same/ compatible generation to avoid system integration issues. |
| Precision ⦁ Connecting with the first point on comparative ability to handle complex tasks, it is easy to summarise that the GPU renders at exceptional speed, but the CPU delivers peak precision and superior quality of renders. Hence why many animation studios like Pixar use CPU render farm for their movies. ⦁ Many graphics rendering applications such as games can afford to take a hit on precision, but not cinematic productions or RT-supporting games. | Tech that gets better with Time ⦁ The development focus is on GPU, given its myriad possibilities across different industries. We are only at the starting point of exploring these possibilities. No wonder, we anticipate a fast-paced progression in the capabilities of the GPUs of the future. |
| Cost ⦁ Even a retail-level GPU is more expensive than a CPU render farm! Hence, it is pertinent to map the costs involved with the tasks at hand and the outcome you desire. ⦁ Given the breakneck velocity of GPU-accelerated processing, the initial deployment cost can be easily offset by savings on opportunity cost and time-to-market, but this is more relevant to AI/ ML and financial market use cases, rather than graphics rendering or video editing. | |
GPU or CPU? What to choose?
Once you’ve ticked off the above-mentioned metrics, the choice you make must be based upon whether CPU or GPU can execute your rendering/ video editing workloads to the best quality at optimal cost, time, and effort.
Summing this up:
- Speed: when the priority is speed, you must choose the GPU and compromise slightly on accuracy and stability.
- Graphics Fidelity: If looking for quality and not boxed in by looming deadlines, opt for CPU rendering.
- Cost: As covered earlier, the market is full of high-quality, economically priced CPU. GPU, whether discrete or integrated, are relatively exorbitant.
- Other factors: such as hands-on experience you may have gathered working on a specific render engine?
The Middle Path: What are Hybrid Render Engines?
Yes, it is not the decision between this or that. You can have the best of both worlds! Whereas most render engines are built to support either CPU or GPU, some like Chaos’s V-Ray and Blender’s Cycles can support both. You can leverage the capabilities of the CPU and the GPU simultaneously using these render engines, but it must be noted that the acceleration is only minimal vis-a-vis GPU-based render engines.
Conclusion
CPU and GPU – one cannot replace the other, both must synchronize to deliver any workload. CPU is the processor we are all accustomed to, and GPU is the booster shot for the CPU. It accelerates graphics rendering and other calculations, augments the output, and pitches in with intensive parallel computational abilities without which the CPU can become overwhelmed.
Consider all the metrics we discussed here, the nature of your graphics rendering/ video editing workload, but most importantly, consider speed, quality and cost factors. Don’t rush before you analyse, and if you decide on magnifying your rendering abilities with Cloud GPUs, we’re here to assist.
24th March
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