Fastest And Best GPU SERVERS PROVIDER

GPU Rendering Server, Rendering Graphic Cards Hosting, RTX Rendering

By using a GPU rendering server, users can save time and resources compared to traditional CPU-based rendering methods, as GPUs can perform the same tasks much faster. The service is accessible from anywhere with an internet connection, making it an ideal solution for professionals in fields such as architecture, film and video production, product design, and more.

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8 Reasons of Choosing GPU Rendering Server

GPU hosting can provide significant benefits for organizations and individuals that need access to high-performance computing resources. By renting access to GPU servers, you can save costs, access powerful computing resources, and scale up or down as needed, all while reducing the need for maintenance and management.

Speed Improvement

Many modern rendering systems are suitable for GPU software and hardware, which are designed for large-scale parallel tasks and can provide better overall performance.

Scalability

Many GPU servers support adding multiple GPU cards to adapt to high computing power needs. At GPU Mart, each GPU server supports up to two GPU cards.

Cost Reduction

Purchasing GPU cards needs to pay more fees at one time and can not be expanded at will. To meet increasing computing power needs, you can choose to rent GPU servers to reduce the hardware cost.

Driver Updates

The GPU relies on driver updates to ensure compatibility with new hardware. Professional GPU hosting services ensure that your 3D software is always compatible with the GPU server.

24/7/365 Free Tech Support

GPU server hosting experts provide high-quality managed technical services around the clock through live chats and emails. Most issues can be well taken care of within one hour or less.

High-Performance 3D Rendering

Rendering graphic cards give full play to their extreme performance and have the characteristics of high parallelism, high throughput, and low delay. GPU Rendering Server is the same as a dedicated server.

Dedicated GPU Benchmark Scores from OctaneBench

Benchmark Score does not always grow linearly. The rendering speed of two GPUs is improved by about 1.9 times. Having 4 GPUs sometimes increases rendering speed by about 3.6 times.
OctaneBench Benchmark Scores for GPUs

Multiple Render Engines Supported by GPU Dedicated Servers

 
 

How to Select a Rendering Dedicated Server

SSD Storage

SSD Storage

We use SSDs as the main drives that host your operating system and install Octane Render and other software. We will provide you with an extra SSD, which can also be used to reduce the load time further.
 
Memory

Memory

Although the amount of RAM you need will depend on your particular project, for OctaneRender (and general GPU rendering), we generally recommend at least 32GB, usually more.
 
GPU Memory

GPU Memory

If your scene is too large to fit into your GPU memory, the GPU rendering engine will need to access your system’s RAM or even exchange it to disk, which will greatly reduce the rendering speed.
 
Power Supply

Power Supply

We ensure that you get enough power for your system. The typical power consumption of most GPUs is about 180-250W. We use two transformers with a capacity of 3500 kVA to expand to 10MW.
 
CUDA Cores

CUDA Cores

Each CUDA core is performing a specific task, while its neighboring cores are trying to render other graphics. This creates an efficient system, in which no core is waiting for another core to complete its work, so the more CUDA cores, the better.
 
Benchmark Scores

Benchmark Scores

A benchmark is simply a test that helps you compare similar products. Each of our benchmarks produces a score. The higher the score, the better the performance.
 
RTX for Octane Render GPU Server

RTX for GPU Octane Render Server

The NVIDIA RTX platform has the fastest GPU rendering solution available today. By connecting NVIDIA RTX Or NVIDIA Quadro RTX graphics card with a combination of technology applications, designers and artists from all walks of life can introduce the most advanced rendering technology into their professional workflow.
 
DLSS Helps Octane Render Generate Clearer Images

DLSS Helps Octane Render Generate Clearer Images

DLSS represents deep learning supersampling. After rendering the game at a lower resolution, DLSS will infer information from its super-resolution image training knowledge base to generate an image that still looks like it is running at a higher resolution. The idea is to make a 1440p game look like 1440p when running a 4K or 1080p game.

FAQs of Best Rendering Dedicated Server Rental

A list of frequently asked questions about GPU servers for rendering.

Yes, Nvidia’s RTX GPU performs better than GTX GPU in GPU rendering. The reason is simple: RTX GPUs not only are higher level and more expensive GPUs, but also have better performance than Nvidia’s GTX series. They also have a ray-tracing core, which can additionally improve the rendering performance of the supporting engine.

People usually expect the equipped GPU to have as many CUDA cores and VRAM as possible. The time required to render the average frame on the GPU is almost inversely proportional to the number of CUDA cores owned by the GPU. Having many CUDA cores allows your server to render your projects fast.

The biggest difference between consumer GPUs and professional GPUs is software.
Nvidia’s Quadro card and AMD’s FirePro card are optimized specifically for high-end productivity applications, with extremely comprehensive compatibility guarantees with leading industry applications.
The main motivation for obtaining Quadro RTX card is enhanced 3D software support, stability and ECC RAM support.

Modern GPUs provide better processing power and memory bandwidth than traditional CPUs. In addition, GPU is more efficient in processing tasks that require multiple parallel processes. In fact, GPU rendering is about 50 to 100 times faster than CPU rendering.

It depends on the CUDA Cores, VRAM, and benchmark scores. Generally speaking, the higher the CUDA Core, VRAM, and benchmark scores, the better the performance of GPU in rendering. For the GPU server hosting, power supply, technical support, uptime, scalability, and other factors should also be considered.

Nvidia’s “Turing” architecture is the first to introduce RTX, which brings some new functions on top of the CUDA kernel (that is, RT and Tensor cores). In consumer GPUs, the Tensor kernel is used to implement DLSS (Deep Learning Supersampling) and other functions. It uses AI to improve image quality.
For professional purposes, the Tensor kernel can take advantage of its outstanding FP16/FP32 and INT4/8 functions, which makes them ideal choices for neural networks, deep learning, AI, etc.RT Core can also greatly speed up your rendering, at least in supported rendering engines. For example, Octane and Redshift are working on the implementation of RayTracing Core.

With a GPU rendering server, users can access the latest hardware and software technologies without having to invest in expensive equipment or manage a physical server. They only pay for the time they use the GPU, making it a cost-effective solution for many types of compute-intensive workloads.