What Is a GPU? Graphics Processing Units Defined
What Are GPUs Used For?
Two decades ago, GPUs were used primarily to accelerate real-time 3D graphics applications, such as games. However, as the 21st century began, computer scientists realized that GPUs had the potential to solve some of the world’s most difficult computing problems.
This realization gave rise to the general purpose GPU era. Now, graphics technology is applied more extensively to an increasingly wide set of problems. Today’s GPUs are more programmable than ever before, affording them the flexibility to accelerate a broad range of applications that go well beyond traditional graphics rendering.
GPUs for Gaming
Video games have become more computationally intensive, with hyperrealistic graphics and vast, complicated in-game worlds. With advanced display technologies, such as 4K screens and high refresh rates, along with the rise of virtual reality gaming, demands on graphics processing are growing fast. GPUs are capable of rendering graphics in both 2D and 3D. With better graphics performance, games can be played at higher resolution, at faster frame rates, or both.
GPUs for Video Editing and Content Creation
For years, video editors, graphic designers, and other creative professionals have struggled with long rendering times that tied up computing resources and stifled creative flow. Now, the parallel processing offered by GPUs makes it faster and easier to render video and graphics in higher-definition formats.
When it comes to performance, Intel provides no-compromise solutions for both the CPU and GPU. With Intel® Iris® Xe graphics, gamers and content creators can now get even better performance and new capabilities. Optimized for 11th Gen Intel® Core™ processors and perfect for Ultra-thin and light laptops, Intel® Iris® Xe graphics come integrated with the processor. Select laptops also include Intel® Iris® Xe MAX, Intel’s first discrete graphics product in 20 years.
Intel® Iris® Xe MAX was designed to provide advanced graphics performance and media capabilities, as well as enjoy seamless, immersive gameplay anywhere in 1080p. All while on a sleek lightweight laptop. Additionally, by combing 11th Gen Intel® Core™ processors, Iris® Xe MAX discrete graphics, and Intel® Deep Link Technology, you can experience 1.4X AI1 performance and 2X better performance encoding single stream videos2 than with a 3rd party discrete graphics.3
GPU for Machine Learning
Some of the most exciting applications for GPU technology involve AI and machine learning. Because GPUs incorporate an extraordinary amount of computational capability, they can deliver incredible acceleration in workloads that take advantage of the highly parallel nature of GPUs, such as image recognition. Many of today’s deep learning technologies rely on GPUs working in conjunction with CPUs.
FPGA vs. GPU for Deep Learning ›
Computer GPU Graphics Cards
More Processing power for your machine
The computer graphics card (also known as GPU) is the lifeblood of any gaming, content creation, or video editing machine. It's the primary component for handling video intensive tasks, taking over that process from the CPU to accelerate video processing workloads. In general, the more graphics processing power, the better the framerates and faster the render times. But with specs like clock speed, RAM, CUDA cores, and many others, even the most avid tech follower can be overwhelmed when choosing the right card for their needs and budget.
Here, we'll cut through the noise and break down some of the most popular graphics card options on the market today to help you choose what's right for your work or play.
Hardware Recommendations for V-Ray
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Hardware Recommendations for V-Ray
Processor (CPU) • Video Card (GPU) • Memory (RAM) • Storage (Drives)
Chaos Group posts basic system requirements for each version of their V-Ray rendering plugin on their official website, as well as the standalone variant. However, the focus in each case is on minimum requirements – not what performs the best. Moreover, there are actually two parts of V-Ray: Adv and RT, which each use different hardware in a computer. Because of this situation, we have taken the time here at Puget Systems to perform our own testing to determine what hardware runs V-Ray the best. Based on this testing, we have come up with our own list of recommendations.
How does V-Ray utilize the CPU?
V-Ray Next CPU (formerly called Adv) is the ‘normal’ version of V-Ray, and it uses the CPU to perform ray tracing and rendering. It scales very well with both clock speed and core count, and even across multiple physical CPUs in a single workstation. If that is the version you plan to use, you will want to spend the bulk of your funds on a powerful CPU – or two, if you have a big budget. Theoretically this should scale well to even a quad CPU workstation, but if you need that sort of horsepower (and can afford it) you might be better off with multiple computers running in a networked rendering configuration.
On the other hand, V-Ray Next GPU (formerly RT) began its life as a GPU-based rendering engine. We talk more about that in the next section, but it is worth mentioning that as of V-Ray 3.6 the CPU can now be used alongside the GPU(s) if you wish. Before this, only a basic CPU was needed for V-Ray RT – but now there is a good argument for getting a more powerful processor, especially if you first max-out the number of video cards. We have articles looking at how CPU performance scales alongside GPUs in V-Ray Next GPU, if you want more information.
What is the best CPU for V-Ray?
If you are planning to use the traditional CPU rendering capabilities of V-Ray, then you will want a high core count processor. The top workstation option for that is currently AMD’s Threadripper PRO line, and specifically the biggest model they offer: the Threadripper PRO 5995WX 64 Core. With 64 cores and greatly improved per-core performance, AMD has taken an even further lead over Intel in workstation processor performance – especially with well threaded applications like rendering. Because of its fairly high turbo speeds, this CPU also does well with modeling and animation.
If your focus is more on the GPU rendering side of things, then any high PCI-Express lane count processor will do well. If you are going to use V-Ray Next GPU, then packing in as many video cards as possible is the name of the game. To that end, processors which support a lot of PCI-Express lanes are the way to go… and things like core count matter a lot less. PCI-E lanes is another strong point of AMD’s Threadripper PRO line, but you wouldn’t need the top-end 64 core model. At minimum 1 core per video card (and ideally 2) is important, though, and keeping the high clock speed high helps too.
Recent V-Ray CPU Articles:
Video Card (GPU)
As with the CPU recommendation above, the choice here depends heavily on which version of V-Ray you plan to use. For V-Ray Adv, nothing special is needed from the video card. Your best bet there would be to select a card that is appropriate for whatever other software you plan to run alongside: Cinema 4D, Maya, 3ds Max, etc.
However, for V-Ray RT the video card selection is the biggest single factor in rendering speed / performance. RT has a couple of different modes, though not all plugin versions support both. An OpenGL mode exists in some versions for use with AMD graphics cards, but the main focus is on the CUDA mode for NVIDIA cards. We have tested that with up to four GPUs and found the scaling to be quite good. Faster cards also perform better, of course, so it really is a balancing act to find the combination of cards that best fit your budget.
What are the best video cards (GPUs) for V-Ray?
GeForce RTX 4080 16GB – A great choice if you want just one or two video cards and don’t work with overly complex scenes. It is also available with blower-style coolers, enabling use of multiple cards if desired.
A great choice if you want just one or two video cards and don’t work with overly complex scenes. It is also available with blower-style coolers, enabling use of multiple cards if desired. GeForce RTX 4090 24GB – Our go-to recommendation for most GPU rendering customers, the RTX 4090 provides the best performance in V-Ray while also having a tremendous 24GB of memory.
Our go-to recommendation for most GPU rendering customers, the RTX 4090 provides the best performance in V-Ray while also having a tremendous 24GB of memory. NVIDIA RTX A5000 24GB – For those who want to stack several video cards in the same system, NVIDIA’s professional GPUs are a solid option. The RTX A5000 is the top-end card that can be installed in a set of four in large tower and rackmount chassis within the limits of a 1600W power supply. If you need even more memory, the RTX A6000 has 48GB of VRAM but may be limited to three GPUs.
Should I use a professional video card for V-Ray?
It is also important to remember NVIDIA’s professional-grade video cards, as they can be a better choice than GeForce cards for some users. They do cost more, but for that increased price you get several benefits:
Higher VRAM options – up to 48GB on the RTX A6000
up to 48GB on the RTX A6000 Better multi-GPU support – thanks to the use of blower-style cooling systems and more constrained power consumption
thanks to the use of blower-style cooling systems and more constrained power consumption ECC memory on higher-end models – for increased stability
How well does V-Ray scale across multiple video cards (GPUs)?
V-Ray scales very well across multiple video cards, but the cooling systems on most GeForce models are not designed with multiple GPUs in mind. For the best overall performance, variants with a single fan that exhausts heat out the back (commonly called “blower” cards) are ideal – and most NVIDIA “professional” cards use such cooling systems. Stacking a few of those will give fantastic rendering performance, though it does require a larger chassis, strong power supply, and plenty of airflow from the case fans.
Note that if you don’t need the extra VRAM afforded by the RTX A6000, a pair of GeForce RTX 4090s will give similar performance to four of the A6000s!
Recent V-Ray GPU Articles:
How much memory (RAM) does V-Ray need?
While the exact amount of RAM you need is going to depend on your particular projects, for V-Ray Next GPU (and GPU rendering in general) we recommend double the amount of VRAM on the cards. So if you have four 8GB cards, totaling 32GB, we would advise 64GB of system memory.
V-Ray Next CPU is more likely to use additional memory, but in the end it comes down to how large and complex your scenes are. RAM is relatively cheap, so erring on the side of caution with 128GB or more is not a bad idea if you are unsure just how much you will need.
Storage (Hard Drives)
What is the best type of drive to use for V-Ray?
Thanks to their speed and relatively affordable price, we strongly recommend solid-state drives (SSDs) for the primary drive that will host your OS and the installation of V-Ray itself – along with any other software you use. The high speed of SSDs allows your system to boot, launch applications, and load files many times faster than any traditional hard drive. In particular, the newer NVMe type of SSDs utilize the latest connections like M.2 and offer the fastest transfer rates.
If your budget allows, it is also a very good idea to have a second SSD that can be used to store your active projects to further decrease load and save times. We highly recommend using an OS drive with a capacity of least 500GB to ensure you do not need to upgrade your primary drive (which is often a complicated process) in the near future.
What sort of drive is best for data storage and backup?
Since SSDs are still more expensive than platter drives per GB, for long term storage and backup we recommend using a traditional hard drive or even an external drive array. Network attached storage systems are a great way to go for that, as they can be shared between multiple workstations and usually offer features to provide some level of data redundancy (protection against losing files if one of the drives dies).