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Graphic Processing Units, commonly abbreviated as GPUs, are primarily associated with gaming and graphics. What most of us fail to realize, however, is that GPU servers could play other instrumental roles too. 

GPUs arose from a need to have improved computer processing as technology evolved. The erstwhile popularly used CPUs were strained and unable to keep up with the growing technology needs and demands. 

That’s where graphic processing units came in to save the day. The latter technology relies on parallel processing methods to allow computer chips to handle many separate tasks on your PCs simultaneously. This article shall delve into concerns such as how GPU servers function, their costs, pros and cons, and how GPUs can benefit your businesses. 

What are a GPU server and its function?

A Graphics Processing Unit, GPU, refers to a collection of computer chips used for image and graphic rendering. To achieve better graphics rendering, GPUs perform complex and rapid mathematical calculations. Today, this technology has found applications in both personal computers and mainframe computing. 

Whereas GPUs were previously used for 2D and 3D rendering, nowadays, they’re increasingly being used in AI, deep learning, finance, agriculture, weather, and so many other unrelated fields. 

Graphic Processing Units are designed using multiple processors which execute parallel processing operations. These multiple processors effectively split tasks into smaller parts for quicker execution. One peculiar aspect about GPUs is that they have RAM access. This random access memory allows the processors to store data such as images. 

The RAM allocates space for each pixel for quicker retrieval. This RAM is also linked to a digital-to-analog converter, abbreviated as DAC. The DAC converts the stored images into analog signals before they get rendered on the output monitor. At times, these processors come with built-in Video RAM for refined graphics rendering. 

What Makes A GPU Server Distinct From Other Types Of Servers?

GPU servers are unique in their abilities to simultaneously handle multiple transactions without slowing down. With other types of servers, the threads are designed to handle a single process at a go, which slows down the runtime. On the other hand, GPU servers rely on the parallel processing method to concurrently work on multiple processes simultaneously. Another distinct feature of GPUs is that they’re mostly run on the cloud. This allows them to handle huge amounts of data without slowing down. 

Does a server need a graphic card?

Yes, servers need to be powered by GPUs. Depending on the scale and intensity of the handled data, it becomes necessary to backup your servers with integrated or discrete processor chips. GPUs are comprised of thousands of tiny CPUs with thousands of cores for quicker data handling. Therefore, it’s in your best interest to arm your servers with GPUs for enhanced efficiency. GPUs operate using the SIMD protocols. SIMD refers to Single Instruction, Multiple Data handling. This is where your processors focus entirely on a single task until they completed it before commencing on the next task. These processors will, however, slow up your systems. The slowed speeds are, in turn, compensated by the improved latency. 

Do You Need A GPU For A Gaming Server?

Games, be it 2D or 3D games, require advanced graphics rendering. GPUs are used to accelerate the rendering of the game’s content for a seamless playing experience. Graphic processing units allow you to handle the intensive computation involved in games comfortably. The processors give your monitors a high refresh rate, and they make it possible for you to enjoy games on 4K resolutions. Connecting your gaming servers to high-performing GPUs is the way to go if you want to enjoy the latest video games. 

How Do Graphic Processing Units Work?

There exist two types of graphic processor units. These are the integrated and discrete GPUs. The difference separating the two types is where they’re located on the motherboard. While discrete GPUs are located on a separate motherboard, integrated types are embedded on the default GPUs. GPUs come integrated into the electrical motherboard alongside the CPU chipsets. Moreover, you can trace the rendering processors on the graphics card of your servers or PCs. GPUs and CPUs bear lots of resemblances. The slight difference is that graphic processor units are deliberately designed to improve geometric and arithmetic calculations. Due to the intensity and complexity of their functions, processors contain many transistors compared to CPUs. 

Some of the Contemporary applications of GPU servers

Graphic processing units accelerate workloads for the enhanced rendering of graphics. These processors have allowed for smoother gaming experiences, and they’re now used in AI applications. 

GPUs are used for accurate floating-point calculations. These processors ensure your personal computers have zero errors when crunching complex arithmetic. This accuracy results from the processors’ abilities to execute tens of thousands of single threads simultaneously. 

GPUs also play an essential role in helping free up your system resources. These processors free up your hard drives, and that allows your systems to have a fairly consistent performance. In most instances, people delegate complex tasks to their GPUs while maintaining the CPUs to handle the core processes. This strategy enables your end-users to have better and faster deliveries. 

GPUs help you to set up a parallel computing environment. Such an environment makes it possible for your systems to perform repetitive operations quicker. The multiple cores help split up the workload into easily manageable tasks to speed up voluminous data handling. 

Graphic processing units also benefit the environment. This technology allows you to operate energy-efficient systems. These systems require a fraction of the energy used by conventional CPUs to perform the same tasks. An ideal GPU server is capable of processing 400 as much data as a CPU. 

Dedicated GPU servers are increasingly being used to train Machine Learning models. These processors are used to develop and run deep learning algorithms with excellent results. That strategy has enabled companies to seamlessly track and monitor consumer patterns and trends for improved ROI. 

How Can A GPU Benefit Your Business? 

GPU servers confer many benefits to businesses, both small and large. This technology enables quicker handling of data, and that speeds up service deliveries. Here are some of the ways GPUs benefit your businesses. Virtual GPUs are great for carrying out creative production tasks such as data mining rendering, streaming, analysis, and 3D data modeling. Here are some of the core GPU applications for businesses. 

Video Streaming 

Video streaming services are essential for gaming companies and brands involved in streaming services. Make use of GPUs, especially those hosted on the cloud, to put out a seamless live broadcast. Cloud-hosted GPUs allow for an uninterrupted broadcast. No viewer will tune in to your live broadcasts if it’s of low quality. GPUs ensure you have a remarkably stable connection throughout your broadcasts regardless of the loads you’re outputting. 

Rendering 

GPU servers are great for rendering visualizations and multi-streams. These servers are often powered by Nvidia processors to enhance the output quality of multi-streamed content. These tools make it easier and quicker for rendering professionals to get the job done. 

Editors prefer using GPU renders to output models for their speed and improved capabilities. A single graphic processor unit will comfortably render a task that would require up to 20 CPUs to complete. Getting rendering tasks done ASAP means your customers will always keep on coming back for your quality services. 

VDI Technology Development 

VDI, which stands for virtual desktop infrastructure, has gained popularity in recent years as more people opt to work remotely. GPUs are also needed to ensure that your VDI applications run smoothly for uninterrupted remote working. 

3D modeling 

GPU servers are a crucial component when working with 3D modeling software. 3D modeling software is used by professionals such as architects, engineers, industrial and product designers, among others. This software helps to up the productivity of these professionals while reducing the time required to complete complex tasks. Faster turnarounds are always positive for your clients. Use GPUs to achieve this and so much more. 

Artificial Intelligence Tasks

We live in an age powered by AI, or Artificial Intelligence. AI is being used to further ambitions like deep training. Here, models are trained on how to make faster and more accurate predictions and analyses from rudimentary data. Neural networks developed to reduce the training time significantly, and that allows businesses to capitalize on curated data faster and with a guarantee. GPU servers are an integral part of AI-influenced training, and that’s why you should invest in them today!

GPU vs. CPU

From the outside looking inwards, GPUs can very easily be confused with CPUs. Upon close inspection, however, you’ll realize there’s a world of differences separating these systems. The architecture of both components is similar, but the core functioning is slightly different. The difference arises from the number of cores in the CPU and GPUs. 

GPU 

GPUs are built for quick image and video rendering purposes. Graphic processing units apply data-parallelism protocols to render output. This method ensures that the processor components focus on the same instruction until the desired output is found. GPUs focus on enhancing the output graphics. 

They have around 4 to 10 cores per single thread. GPUs stand out for their impressive parallel-processing architecture. This system exponentially speeds up the rendering process. These systems are capable of performing multiple processes at a go 

CPU 

CPUs are primarily designed to respond and react to basic system instructions in your computers. In other words, CPUs interpret the commands provided by the computer user. CPUs are designed to handle multiple instructions concurrently. CPUs often come with around 4 to 8 cores, but it’s not unheard of to get some with up to 32 cores.

Each core is assigned a unique task or thread. The number of threads is higher than the corresponding number of cores since some cores can be virtually divided during operations. CPUs have the upside of having higher clock speeds, however. This speed allows them to execute instructions like calculations at a faster rate than their counterparts.  

Can You Run the Whole System On a GPU? 

A common question posed by users is whether it’s possible to configure or program entire systems to run from GPU servers. Well, the answer is simple. Most systems or programs don’t require the robust power provided by GPUs. However, some applications require these servers for optimal performance. 

Yes, you can write an entire OS or Operating System on a GPU by using programming languages like low-level C, but you’re bound to run into several issues. For instance, most graphic processing units don’t have exception handling protocols, and they also don’t support interrupts. 

What are Some of the Applications in Which a GPU Does Better? 

GPUs are preferred for compute-intensive applications such as Bitcoin mining, 3D modeling, rendering, and gaming. These tasks require multiple processors to run simultaneously, and that’s precisely what this cloud-hosted server is designed to achieve. Other applications that call on users to use GPUs include:

• Big data analysis 
• Stock market trends
• Geospatial visualization
• Animation and CAD rendering 
• Image recognition and classification 
• Medical imaging
• Password recovery 
• Speech to text processing 

Can a GPU Support Applications For a Commodity Server?

Yes, GPUs can be used to monitor and analyze complex data from commodity servers. The commodities’ indices are always changing and, it would be impossible for you to predict movement patterns using CPUs. GPUs internalize that behemoth data, and using the parallelism methods, they’re able to make informed and accurate commodity price predictions. 

How Does a GPU Server Cost?

You can either purchase your GPU servers or rent them on an hourly or monthly basis. The latest servers can go for up to $8,500 per month, depending on the resources available. Cloud instances, however, have very favorable rates. For instance, you can rent out an instance that comes with 1X Tesla K80 Pascals for roughly $0.9 per hour. 

You’ll pay more for extra Tesla K80 power. You should also factor in the power costs involved in keeping your servers on to the total costs. Most server rates start at $0.099 per hour. You have the option of signing up for a free trial version to determine the capabilities of the GPUs you’re intending on renting from the cloud. Notably, Cloud GPUs are 80% cheaper than the AWS options. 

At Virtual Systems, we offer revolutionary computing hardware with high performance at affordable rates with 1Gbps unlimited bandwidth. If you can foot up at least $250 per month, you’re good to go. Additionally, our servers are powered by NVIDIA GeForce GTX 1080 TI / 11GB GDDR5X Memory. Whether you want custom configs with a dual GPU or a single GPU, we’ve got you covered. 

Pros and Cons of a GPU Server

Like any other server, a GPU server has both strengths and weaknesses. Let’s explore the various pros and cons that you’re likely to encounter. 

Pros of GPU Servers 

Increased Computer Capacities 

GPU servers will increase your businesses computing capacities by significant margins. Rental GPUs hosted on clouds will up your storage and computing capacities for a fraction of the total cost you’d have incurred with physical servers. 

Scalability and Flexibility 

Users on GPU servers have the flexible options of switching their server configurations on demand. As a customer, you won’t need to worry about the server’s default configurations as the devices come loaded with your technical preferences. Before you use any cloud-hosted GPU, you’re brought up to speed on the server’s performance, speed, and other security features beforehand. 

24/7 Real-Time Monitoring 

GPUs hosted on the clouds allow you to track your machines in real-time. These processors reside in the Tier-3 data center, where they’re constantly being monitored by experts. That means, in case of any malfunction, these experts get notified, and they begin working to restore proper functioning. Therefore, your business clients will never experience server blackouts and other such frustrating delays. 

Cost-Effectiveness 

Buying a dedicated GPU server is quite expensive. The latest models fetch many dollars. However, once you’ve made this initial investment, you’ll most certainly never have to dole out cash to carry out computing-intense tasks. Alternatively, you have the cheaper option of renting out cloud-hosted servers to accomplish your 3D modeling, rendering, and other AI-affiliated tasks. 

The rental option gives you the freedom to explore options such as hourly or monthly rates, the number of SSD, GPU, and their specific RAMs. Partner up with an accredited cloud-services operator who provides maintenance and initial configuration to their customers for a hassle-free experience. 

DDoS Protection

Your sensitive data is always secured by DDOs protection. Therefore, you never have to worry about your client’s sensitive data getting into the wrong hands while it’s hosted on the rental cloud. 

99% Network Uptime

Most, if not all, of the GPU cloud-hosted servers, assure clients that their content will always be available to the end-users. In stark contrast with the physical servers, these option guarantees you don’t lose clients due to unending downtime.  

Cons of GPU Servers

Latency 

The high latency of the GPU servers takes away the fun from the gaming experience. Players experience way too much lag between the game sequences. There’s a momentary delay between when you click on an action and when it gets executed on the screen. 

Limited Coverage 

For a seamless cloud-GPU server experience, your area needs to be sufficiently covered by the supporting infrastructure. This infrastructure allows the IP traffic to hop from one relay node to the next ensuring an uninterrupted end-user delivery. It can be expensive for your local broadband providers to set up sufficient coverage, more so when you’re away from the urban areas. 

The Best GPU Server Solutions For Your Business – VSYS

The best consumer GPU servers to consider in 2021 include:

The NVIDIA Titan V 

The Titan V is a robust server that’s designed for high performance. It features 12GB RAM, a 3,072-bit memory bus, 4.5MB L2 cache, and it delivers 110 teraflops performance. You can also go for the premium version with improved specs. 

NVIDIA Titan RTX

This GPU features an impressive architecture that features advanced RT and Tensor Core Technologies. The RTX has a 32 GB RAM, 6MB cache, a 4,096-bit memory bus, and it delivers 125 teraflops performance.  

NVIDIA GeForce RTX 2080 Ti 

This GPU is designed for robust performance. It has impressive specs such as a 352-bit memory bus, 120 teraflops performance, 11GB RAM, and a 6MB cache capacity.