Nvidea GPU Dedicated Server Plans

SSD GPU Server with Nvidea Card

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  • Server Type
  • DataCenter
  • RAM
  • CPU Core
  • Storage (SSD/HDD)
  • Flag
    Datacenter - USA
  • VMLG101
  • Intel Xeon X3440
  • CPU Quad-Core
  • RAM 16 GB
  • Storage 1080 GB SSD
  • Nvidia GeForce GT710
  • GPU RAM 1 GB
  • 120 Mbit/s port
  • 100Mbps Unmetered Bandwidth
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  • Out Of Stock
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Why GPU Dedicated Server

Server power is usually measured in terms of processors (or processors). GPU dedicated servers, however, can increase performance, while utilizing less energy. Utilizing graphics cards for specific tasks shows how GPU servers can be beneficial to your business.

How GPU Server is beneficial for you

Generally speaking, CPUs are made to handle anything thrown their way. A web browser, email server, or word processor, for example, are ideal for them. The advantage of this is that if the custom hardware is designed to perform a specific job, it will be faster than a CPU. GPUs are a good example of this.

CPUs have faster core speeds than GPUs but can run thousands of cores simultaneously. With floating-point number arithmetic and fast rendering, GPUs can produce realistic 3D graphics at high speeds. This means GPUs are faster than CPUs at certain mathematical operations.

The name GPU server refers to servers crammed with graphics cards, designed to take advantage of this raw processing power. With offloading, the CPU can separate specific tasks from the GPU, increasing performance. A Nvidia GeForce 1070 illustrations card is around 16x quicker than an Intel Core i7-7500U CPU when benchmarks are directed utilizing the TensorFlow AI structure.

It's faster and uses less energy as well, resulting in lower heat and power consumption. High-performance computing can be achieved with the ASUS ESC8000 G3, which accepts eight full-size PCI-E graphic cards. A dual-deck GPU server, the ASUS ECS8000 G3 supports up to eight GPUs at once.

What can GPU Dedicated Servers do?

A GPU is often used for high-performance graphics, but its architecture and high-speed mathematical algorithms also make it capable of handling some high-performance computing tasks. Using a GPU requires applications that offload specific tasks to the CPU. GPUs handle graphics processing, while CPUs handle other aspects of gameplay. The GPU's strength comes from its ability to hold parallel computing. Larger tasks can be divided into smaller and parallelized tasks by using thousands of cores.

Consequently, a GPU can perform some tasks much faster than a CPU. GPUs are often discussed in connection with supercomputers, such as those used to predict the weather or to sequence DNA. For general business use, GPU Dedicated Servers are still a proven solution, and they empower data analytics, big data processing, and database queries.

As well as applications designed for GPUs, Nvidia has its CUDA platform that enables developers to create their GPU-accelerated apps. GPUs will likewise control the following influx of AI applications and have additionally demonstrated famous for digital money mining. While GPU servers aren't the response to each business challenge, they can speed up your cycles and run complex inquiries quicker than a CPU, all while utilizing less energy.

GPUs: How they can help

Explore how GPUs can help with your mission


You can use IBM Cloud to deliver rich gaming experiences that perform and engage, whether you develop online games, develop game platforms or build gaming innovations.

Financial Services

Financial institutions of all sizes can run like startups with IBM Cloud's smart and secure solutions.

Scientific Research

Researchers and doctors can analyze massive amounts of seismic data faster and solve complex molecular modelling calculations.


With IBM Cloud, healthcare innovators can thrive in a hybrid, multi-cloud world. IBM's extensive collection of advanced data, AI tools, and HIPAA-compliant data sets make the journey to the cloud simple.

For what reason is the GPU utilized for profound learning?

GPUs are utilized for long time-synchronous calculations with fewer assets. While utilizing GPUs, you run over numerous assortments, even though NVIDIA is all around the market.

While we are planning a profound learning process, our choice ought to incorporate GPUs and consequently these components.

It can give appropriate transmission capacity to change huge datasets.

It has more scaling range than CPUs, which allows datasets to run quicker than at any other time.

Viability in long-running solitary undertakings is preferred in GPUs over in CPUs, and it is one more capable of the GPU.

Why us?

Our group has experts who have preparation and experience in programming and who work on every one of the main innovations. They are largely exceptionally experienced experts who have worked in this field for quite a while.

We at DedicatedServer.Tech ensure that you have the best help and data. Our experts supply all day, everyday client care so you get all the data you want.

We offer adjustable types of assistance and data regarding what is the most ideal decision for you acceptable for you. An all-around discussed administration with solid counsel and the right information can furnish you with the best help. Indeed, even after you pick any assistance and face issues, we will assist you with settling every one of the blunders you may confront.