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Is it time to get a GPU server?
This article is part of our VPS, Dedicated Servers & Infrastructure resource section.
Everyone sees the benefits of having a powerful server with a high-end CPU, quick resolution of routine tasks and an efficient use of time. However, when the load is heavy, nothing beats having a high-performance GPU (Graphics Processing Unit) to boost the processing speed by many times. Hostkey and satisfy any requirement exclusively employing high-performance GPUs – NVIDIA GTX 1080/1080Ti and RTX 2080TI and NVIDIA TESLA V100/P100. The use of GPUs in servers has skyrocketed since the GPGPU (General-purpose computing on graphics processing units) came on the market.
Before comparing GPU configurations, it helps to understand what a server is and how it works. A server supplies computing resources and services to connected devices, while a GPU server adds specialized processors capable of handling many calculations simultaneously.
The main advantage lies in the sheer number of cores in a GPU. Although less powerful individually, they collectively process data at a higher rate working in tandem, a tandem that can range into the hundreds or even thousands of cores simultaneously processing a large number of data streams in parallel. This net effect of this is an overall high rate of data processing, which can significantly affect your bottom line.
Your choice between virtual and dedicated infrastructure should depend on the workload, required performance, and available budget. Our guide on how to choose the right VPS server explains which resources and provider features should be considered when a complete dedicated GPU machine is unnecessary.
Graphic processing
The primary concern of anyone engaged in graphics rendering is cutting that processing time. So, why not let your graphics card handle it? It was designed for that job after all. That in conjunction with a high-performance CPU will deliver the shortest rendering times. Industry tests confirm this proposition. In one controlled industry test, a powerful NVIDIA GPU with 2700 CUDA cores outperformed an 8-core 3.4GHz Xeon when rendering the same image via V-ray. The difference was more than 6 times, an astounding difference of 19 minutes for the CPU and a mere 3 minutes for the GPU to render the image in the same resolution.
Neural Networks
Thinking outside the box can save you time and money. It might not seem obvious at first to use a GPU server to train a neural network instead of a CPU, but the performance speaks for itself. The time savings can be colossal, especially when training vast neural networks. Using powerful graphics cards can reduce processing times from weeks or even months to mere days. Our GPU servers with TensorFlow pre-installed are available now. The applications are widespread as is their usage, from meteorological modeling, transcription of medieval texts, to image or face recognition software.
After a neural network has been trained, it must be deployed efficiently to produce predictions. The NVIDIA Triton Inference Server helps organizations serve AI models across compatible frameworks and manage inference workloads on GPU-powered infrastructure.
Virtual Desktop Infrastructure (VDI)
If you need a high-performance and secure server for applications such as ArchiCAD or to provide streaming video, you will need a server with a VDI (Virtual Desktop Infrastructure). This is cost-effective not only in hardware, but it greatly improves security and better yet, it is remotely accessible from anywhere on almost any device.
Automating routine administration can make remotely accessed infrastructure easier to maintain. Administrators using Microsoft environments can learn how to automate Windows Server with Attune to create repeatable workflows and reduce time spent on manual server-management tasks.
There is no limit to the applications of a GPU: data science, mining, tele-medicine, video transcoding, facial recognition and more.
HOSTKEY offers GPU dedicated servers with VPS NVIDIA GTX 1080/1080Ti and RTX 2080Ti and NVIDIA TESLA V100/P100 GPUs that can handle any processing task both efficiently and cost-effectively.
