GPU rendering solutions and what’s best for me

You found your way here probably because you have a project you’re working on or will be working on any time soon and you know that the few years old PC or Mac you own likely won’t be able to render this beautiful CG animation within a reasonable time.

Assuming your render engine of choice is one of the capable GPU rendering powerhousesRedshift or Octane, you will have a few options to consider to prepare yourself for the upcoming rendering terror.

If you do it right, the terror can turn into an enjoyable walk in the park. If done wrong, well, it’s not the end of the world. You will be left with your computer rendering your frames for days or even weeks. If you happen to own two computers or have a lot of time on your hands, then that might be an acceptable condition. For those of us who don’t have that much of a luxury, we will try to approach this situation with a sound plan.

First, let’s take a 10,000-foot view of the options we have. We don’t want to jump into conclusions too soon while we don’t want to stay with our heads in the clouds for too long either. We want to be pragmatic.

GPU rendering solutions

We could look at all the possible GPU rendering solutions available out there at this time. However, I’m worried that this post would potentially turn into one of those SIGGRAPH technical papers you wish you had time to read. I will look at three viable solutions any of the 3D artists or small studios could implement without too much effort now. I considered these solutions because they are accessible, they are affordable (with certain levels of variance), and most importantly anyone who has very little technical knowledge and no IT experience at all can implement them by themselves.

The solutions are:
– hardware upgrade
– GPU server rental
– cloud render farm

Hardware upgrade

When I was a kid (6th or 7th grade) and got my first PC I was astounded. I loved everything about it. I was really curious about what’s inside and how it worked. I would replace some parts and even take the whole computer apart (with the help of my older friend). That was many years ago, and even though I still feel like I’m that kid inside, now I prefer simpler out of the box solutions.

That being said, I would rather not spend too much time tinkering with the hardware, researching what’s the latest and best CPU or GPU, and then building my computer from scratch. I would rather spend more time using the computer and doing creative work.

There is something that I would do though and I think anyone else can do as well and it is to upgrade or invest in certain hardware parts in a computer I already have (I’m a PC user so I can’t speak for you Apple lovers out there).

Getting a good motherboard with enough PCIe lanes (for multi GPU setups), good power supply, and a good graphics card isn’t that hard and it doesn’t require that much effort. It does require some time to do basic research though. The parts might not be that cheap either if we’re going for a rendering machine that will serve us well at least 3 to 5 years down the line.

Let’s take a look at a few key parts and their prices. I’m not going to go into details because I’m not an expert. I just want you to get a general idea of what’s out there.

Motherboard

AMD: Gigabyte X570 Aorus Ultra – AMD 3rd Gen Ryzen supported motherboard with 2x PCIe x16 slots (2x GPU cards), great for upper mid-range PC builds // $300 (link)

Intel: Gigabyte Z490 Aorus Ultra – 10th Gen Intel supported motherboard with 2x PCIe x16 slots (2x GPU cards), great for upper mid-range PC builds // $300 (link)

Power supply

Corsair AXi 1600 Watt will handle 4x RTX 2080Ti cards, 64GB RAM, TBs of storage, and extra cooling // $550 (link)

Here’s a useful link to a PSU calculator.

Graphics card

RTX 2080Ti – 304 OctaneBench 4 – a beast of a GPU card but very pricey // $2,000
RTX 2060 – 170 OctaneBench 4 – probably best GPU per dollar spent //  $350

Check out this super useful performance per dollar benchmark results based on OctaneBench 4.

Alternatively, if you have some decent savings or got an upfront payment for a large project, you could also invest in a PC built by BOXX, for instance, who are known for building rendering beasts. You can choose a model of a GPU rendering workstation that matches your needs, simply customize the parts you want like the CPU, RAM, storage, GPU cards, and you will have a render box delivered to your door. It’s pricey but if you want peace of mind and want to save time, then go for it. Here’s one of their rendering workstations – APEXX x4 (with 4 GPU slots).

Price: $9,395
– Intel i9-10900X 3.7Ghz
– 128GB RAM
– 1x RTX 2080Ti 11GB (with additional 3 slots for possible GPU upgrade)
– 1TB SSD NVMe + 500GB SSD SATA

APEXX x4 workstation https://www.boxx.com/guru/apexx-x4

Now, it’s a bit of an investment to get a PC like this but as with any good investment, it should yield good returns over time. Another upside is that with the setup like this you could buy a few more GPU cards in the future and get a substantial speed boost without much hassle.

GPU server rental

When I say server rental I mean servers in the cloud we can connect to and work on via remote desktop. You could also rent a physical server. Some companies specialize in building powerful rendering rigs and they rent them per day. Those tend to be expensive and we won’t talk about them here.

So why would I need some server in the cloud?

Well, the answer is quite simple – speed and price. Contrary to a still common belief that has stuck around since the dawn of modern cloud computing 20 or so years ago (AWS launched in 2006, also read: a brief history of cloud computing), the cloud isn’t expensive. It used to be but it isn’t anymore.

Another belief is that using cloud computers or cloud rendering as a whole is too difficult and too technically challenging. I’m here to tell you that it isn’t true. Again it might have been true 10 years ago and even 5 years ago but now it’s a very different story. Now we have SaaS (Software as a Service) clouds that are very friendly.

Technology and tools have improved to the point that there are artists who thought they would never be able to understand what’s all the deal with the cloud, now use it daily (I’m one of them). True, they still might not understand how it works (me again) but the point is it has been made possible thanks to artist-friendly services built on top of the complex cloud technology.

These services allow you to rent a powerful server, one that you could only dream of owning, at an affordable price. You can get access to GPU rendering servers that can easily cost upwards of $25,000 (what!) at the fraction of the cost. Who wouldn’t want that?

Imagine having a machine with 10x 1080Ti on board? You can have one just like it a few clicks and a few minutes later. How about a server with multiple Tesla V100? Yes, please! I might even have two!

GPU servers available through Xesktop https://xesktop.com/features/

It’s very simple and takes no time to set up. You create an account, log in to the web dashboard, select the type of machine you want to use, give it a name, and hit “start”. A few minutes later you have a machine you can connect to remotely. It’s like having your computer, the difference is you don’t need to spend thousands of dollars to buy it.

You can install your 3D software and any tools that you normally use for work. You can shut it down any time you’re done using it. You can rent it for a few minutes or a few days at a time. You are in full control of how you use it and when you use it.

You might think “I’d rather buy my computer, it’s cheaper”. Fair enough. Not everyone can afford to invest a hefty amount of money upfront in hardware. You could save up and get your own computer like that. The problem is it’s practically impossible to have the latest graphics card or CPU because as soon as you buy one, there will be a new one 3-6 months from now. Not to mention, while one rendering rig is great to have when you’re just starting or don’t do much animation work, at some point you will need more rendering power.

Services that offer GPU server rental give you a lot of flexibility and peace of mind. You can use them as your main go-to-rendering solution or have it as a backup plan for unexpected tight deadlines or large projects. However you choose to use it, it’s a great addition to your current GPU rendering pipeline. Don’t take my word for it. Test it for yourself. For example, through Xesktop service you can get a trial that will allow you to test the powerful GPU machines and see if you like what you see before you commit.

Cloud render farms

You might have heard the term render farm quite a few times by now. You might have even considered building your render farm. It’s not that hard putting a few Xeon render nodes together after all, isn’t it? Well, honestly it takes quite a bit of time and effort so probably it isn’t a solution for someone like me (but you should decide for yourself, some useful pointers).

Cloud render farms as a service is something that has been around for over a decade. In its early days, the technology wasn’t sophisticated enough nor there was a high enough demand for rendering in the cloud and thus cloud rendering wasn’t popular at all. On top of that, the common concern was questionable security and bandwidth limitations. In 2020, we don’t need to worry about security or internet speed anymore (for the most part). The demand for rendering has been gradually increasing and technological development reached a point where cloud rendering isn’t only a viable option for studios but also freelance artists.

There are a few large public cloud providers like Google Cloud, AWS, and Microsoft Azure with massive infrastructures and thousands of machines available for processing and rendering. They don’t provide a cloud render farm as a service themselves, however, if you’re tech-savvy or are a studio with an IT team, you can build your private render farm on top of their cloud computing platform. IBM has a very good learning resource exploring basic cloud computing topics https://www.ibm.com/cloud/learn/cloud-computing.

There are also dedicated cloud render farm services either built on top of those large public clouds or they have their own private clouds (a.k.a. their own data centers and their own hardware). These types of services are much higher in numbers these days which is a good thing because competition often breeds innovation. One service that knows a lot about innovation and what it means to be artist-friendly is GarageFarm. You might want to check out their GPU rendering offer, you won’t regret it https://garagefarm.net/gpu.

Now, I talked about the server rental services earlier and how they are easy to get started and how affordable they are. Cloud render farms have gone a long way too and what you can get today is really a game-changer.

But first, you might be wondering.

What is the real difference between a GPU server rental service and a cloud render farm service?

Simple answer, they both are GPU cloud services and they both are GPU rendering solutions. However, their approach to the solution is a little different.

The GPU server rental services give you more control over the rendering process and, in general, offer more flexibility. It’s simply another computer you can use to render your project on, not much different from rendering locally on your machine. It also means you need to install your own 3D software and render engine on the computer because usually, it’s a blank system.

The cloud render farms or the GPU cloud render farms (P.S. they aren’t always both CPU and GPU compatible), aren’t as flexible as they follow a certain workflow but are mostly automated systems. You basically install a plugin for your DCC app and send your project to the farm through their software. Then you interface with a web dashboard or some desktop app where you submit and manage your render jobs. You won’t be rendering your scenes on your computer and you won’t be rendering them through a 3D app GUI as you do locally. Instead, all the processing and rendering happens somewhere else on the farm’s end through the network rendering system, and what you get back, in the end, is your rendered frames downloaded to you.

Why would I want to use a cloud render farm?

Cloud render farms are very convenient and very powerful, much more powerful than renting a GPU server or a few servers (even the mightiest of them all). They are convenient because, for the most part, you don’t have to worry about installing and configuring any complex software. All you do is you work with the tools that you’re already using and are familiar with.

A quick and useful explainer about render farms (wish I had watched it years ago)

The render farm plugin for 3ds Max, Maya, Cinema 4D, Blender or any DCC app you’re using takes care of all the heavy lifting for you. It will detect all your settings and it will prepare the project for rendering on the farm automatically. After all, your data is uploaded to the farm and a few clicks later, you will get access to dozens or even hundreds of machines dedicated to your project. At this point, you just have to wait for the finished frames to download back to your computer.

Imagine having 20 or 50 or even more machines with powerful GPUs rendering all at the same time? At this speed, rendering a few hundred frame animation would be a breeze. And all that without any hassle, no upfront investment, and for the price that is accessible for most of the artists.

What’s best for me?

If you’re a freelancer with moderate rendering needs and do 1-2 projects a month, I would suggest investing in a good computer you can rely on. Occasionally, you might look into renting a GPU server for several hours here and there.

If you’re a freelancer with a high clientele often busting out high-end motion graphics and animations, you would need access to large GPU rendering power on-demand to chew through the projects efficiently. In this case, you should go either for GPU rental or use a GPU cloud render farm. Both will do. It’s up to your preference what solution suits you better and the frequency you use them with.

If you’re a small but growing studio with regular work coming in and increasing demand for high-end animation work, you would probably want to consider integrating your pipeline with a cloud render farm. You would want it to be always there as a tried and true tool in your CG toolbox.

Next step

Now that we discussed the most common viable solutions to GPU rendering and some use cases, it’s time for you to look at your needs more closely and think about where you are.

Are you a freelancer who is just starting out? Are you an established freelancer with high demand for animation work? Are you a studio taking on larger projects? How much money do you have saved up? How much can you invest in your business upfront without feeling the impact?

Even if you aren’t pressured by a looming deadline or don’t need to think about a rendering solution at this stage, you might want to consider educating yourself a little and maybe even taking a small step into the future and experimenting with what’s out there. You might be surprised how simple and harmless certain solutions are. You might discover that you could become a more effective, efficient, and capable artist or business. Who knows? It doesn’t take much effort and you have literally nothing to lose (a lot to gain though).

Happy rendering,
Lucas B.

Blender 2.8 beta + Xesktop: Harnessing the power of 10 GPU cards on benchmark scenes

Have you ever wondered what it would feel like to harness the power of ten GTX 1080 Ti cards? Wonder no more! Our dedicated GPU rental service does just that.

With Blender 2.8 well into its beta stage, we thought it would be fun to test one of our servers on the Blender open data benchmark scenes and let you guys have a look at the resulting render times for each. The Blender open data benchmarking tool itself is also in beta at the time of this recording, and sadly wasn’t working for us. In any case, here are manual renders of a frame from each of the benchmark scenes with the resulting times. None of the original render settings were manipulated (except of course for switching the device to GPU rendering and adjusting the tile sizes appropriately).

Here’s a quick rundown of the specs of our servers:

  • CPU: 2x Intel Xeon CPU E5-2620 v4 @ 2.10 GHz
  • RAM: 128GB
  • GPU: 10 x NVIDIA GeForce GTX 1080 Ti, 11GB
  • NVIDIA CUDA Cores: 10 x 3584
  • Octanebench score: 1753

When do we come in handy?

Having the performance capabilities of a server like ours can be a godsend when you’re dealing with turnarounds for complex scenes, or scenes with elaborate dependencies that would produce complications when rendering over a network. Some projects might actually even benefit from rendering over a couple of machines with multiple GPU cards. When working against a deadline, every second counts. Imagine what you could do with an additional workstation containing 10 GTX 1080 Ti’s!

many-Maya-memes 5 Situations in 3D Production Where GPU Power is a Must-Have

Our powerful, dedicated GPU servers are at your disposal for GPU 3d rendering, processing Big Data, or any task that can benefit from parallel processing. After registering, you get your very own web dashboard where you can easily create your personal windows instances on top of our servers, and go back to them just as you left them whenever you need to.

We offer our servers at the incredibly low rate of $6 an hour, creating and entering your servers takes just a few clicks, and best of all, we’ve got a team of specialists you can chat with anytime.

Xesktop is powered by GarageFarm.NET, which means if you’ve rendered at GarageFarm before, you can use your credentials to log into your Xesktop dashboard and rent servers with your existing GarageFarm credit balance.
If your local rig is struggling with a complex scene, you could bring it over to your Xesktop workstation, finish it there, and hit render, or send it over to GarageFarm for some good old fashioned CPU rendering – whatever you need. Think of Xesktop as another addition to your cloud based pipeline.

If you want to experience rendering your own scenes on a set up like this, give our service a try.

Happy Trails from all of us at Xesktop!

Real-time rendering and The CG industry

We’ve been seeing some rapid development in GPU technology, particularly in its advancements towards matching the realism achieved with offline renders on interactive media platforms, such as in gaming or VR. Oats Studios’ ADAM is a visually stunning short film created with the real-time rendering capabilities of Unity, a game development platform. Epic Games’ Unreal Engine 4 was used to render K2SO in Star Wars: Rogue One, and the list of examples is ever growing. With architectural and automotive visualization jumping on the bandwagon, it’s beginning to look like offline rendering will be left in the dust sooner rather than later. But what will this mean for the business ecosystem of 3d rendering?

Image credit OATS Studios

Today’s production pipeline is still reliant on traditional rendering, and will continue to be until real-time image analysis can catch up to offline ray tracing engines, which are continuously developed to render faster and faster. This parallel advancement of two different solutions may sometimes seem directed towards the same goal, in a way that would ultimately leave only one accepted and widely used in the future. It’s easy to think that if at some point, real-time rendering wins the race, the landscape of commercial CG will change immensely, and different service providers in that sector may have to reexamine their business models to accommodate this. Render farm or GPU rental services, for example, have been the means for studios to survive in the fast-paced industry because of their scalability and affordability. That we see high-quality 3d in commercials or TV these days is because render farms allow productions to manage render times while continuing to work on turnarounds or more content. If frames that would take hours to render using today’s engines could be reduced to minutes with real-time rendering, it wouldn’t seem reasonable for anyone to need to render on farms or rented GPU servers at all. Consequently, external render engines as we know them may then be obsolete, since all rendering will be saving snapshots of what’s already drawn on a 3d applications viewport, more or less.

Of course, all of this is conjecture, and this possibility has no doubt been mulled over by companies with a stake in all this. The fact that development for traditional renderers hasn’t slowed down means the above scenario isn’t going to happen for a while, or there are possibilities for both solutions that could contribute to rendering in different but equally important ways. Perhaps the evolutionary trajectory of real-time rendering, though reaching a level of usability in mediums dependent on offline rendering, stops short of where traditional rendering is going. We may see photorealism in offline renders reach new heights, at faster render speeds. V-Ray is already introducing Hybrid rendering, which makes use of both CPU cores and GPUs at the same time, which could pave the way for its competitors, and third-party rendering services. On the other side of the 3d world, Blender 2.8 is at its beta stage and features their own real-time rendering engine called EEVEE, as well as the ability to employ both GPU and CPU to speed up rendering. Real-time rendering may not overthrow offline rendering, but enhance productivity and pre visualization, as well as serve as a sufficient rendering alternative in certain cases. Netflix’s Love Death Robots, produced by Blur Studios, is a testament to the continuous development of traditional ray tracing, and the growing accessibility of 3d rendering for media other than mainstream cinema. In the end, only time will tell, but at very least, the evolution of real-time rendering is a sign of big changes in the world of CG.

So now that we’ve talked about real-time and traditional rendering, let’s have a little look at the processors that serve as the main driving force for each.

GPU vs CPU for 3d rendering

GPU rendering has nested itself in the imaginations of many 3d artists as the light at the end of the long and dismal production tunnel. Touted as the ultimate solution for render times and the future of 3d across many avenues, GPU rendering has definitely become quite the buzz word these past few years. But many CPU loyalists have offered credible arguments in favor of traditional rendering, and that many studios still rely heavily on CPU based render farms begs the question: what’s the catch?

Before looking at the caveats, let’s examine the distinguishing advantages of GPU rendering.

NVIDIA’s GPU RTX line (image credit: NVIDIA)

Scalability

With only rendering in mind, a GPU can outperform a CPU by executing the render instructions on many more cores, exponentially reducing render times. On top of that, multiple GPUs can be used for rendering a scene. The implication of this is that one workstation with multiple GPU cards is now an alternative to buying multiple CPUs which would require more physical space and upkeep, or being dependent on render farms, which, although arguably less costly, doesn’t provide the security or control of something in house.

Productivity

Real-time rendering is making its way to popular 3d programs such as Cinema 4d and Blender, and other apps are sure to follow suit, but this has been something inherent to GPU based renderers like Redshift and Octane. Being able to interact with a realized scene in the viewport makes the 3d creation process more streamlined than having to render previews all the time.

Efficiency is what GPU rendering is all about, and it’s this new level of effectiveness that’s getting the 3d community pumped, but the more skeptical users insist that this is all too good to be true, and for valid reasons. Here are some things about GPU rendering that need to be considered:

Memory

The high latency in communication between GPUs and system memory means each allocated GPU must itself, have enough memory to accommodate a scene, and if multiple GPUs are used, the card with the lowest memory determines whether the scene can be rendered at all. This limits what can be rendered on GPUs since even though there are several ways to optimize a scene for rendering, larger and more complex scenes are bound to need more than graphics cards can currently provide.

Stability

Because GPUs rely on drivers, the frequency in which these drivers are updated can pose stability issues with operating systems and some programs. Bugs need to be addressed with every update, which can hinder productivity on a GPU dependent pipeline.

Less GPU render farms on the market

Access to a cloud-based rendering solution is always a good thing to have despite the speed gains GPU rendering can provide, and the services that provide rendering for GPU based engines are limited. There is, however, a growing number of GPU server rental solutions that can be utilized for this purpose.

The increasing viability of GPU rendering will definitely shape the landscape of the 3d rendering industry in the years to come, but CPU rendering stands on solid ground, and the future holds a place for both solutions. The concept of hybrid rendering, which employs both the GPU and CPU is an example of the harmonious relationship we can expect from both rendering approaches. Where CG technology will bring us, only time can tell, but it’s safe to say that excruciatingly long render times will soon be a thing of the past.