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GPU Cloud Computing 
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**Introduction**


A cost-effective way to run high-performance computations

Level up your cloud servers with GPU accelerators. Graphical processing units are mostly used for deep machine learning, architectural visualization, video processing, and scientific computing. 

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.. image:: images/gpun.png

TESLA

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We provide servers that are specifically designed for machine learning and deep learning purposes, and are equipped with following distinctive features:

* Modern hardware based on the NVIDIA GPU chipset, which has a high operation speed.
* The newest Tesla V100 & T4 cards with their high processing power.
* Bundled with CUDA technology 


**CUDA**


Parallel computing architecture designed by NVIDIA. The implementation of this architecture allowed to significantly increase the performance of GPU computing.

**Advantages of CUDA:**


* Using the common programming language C
* Applying technologies such as Parallel Data Cache and Thread Execution Manager
* Default libraries for FFT and BLAS
* Unification of hardware and software parts for GPU computing
* Multi-GPU Support
* Hardware Debugging
* Excellent scalability to different projects
* Special CUDA driver

All our GPU plans support are NVIDIA® CUDA-capable and cuDNN with the latest version.


* Pre-installed with Nvidia-Docker2
* Includes NVIDIA® GPU Cloud (NGC) Catalog CLI is a command-line interface for managing content within the NGC Registry
* Includes development tools based on the programming languages ​​Python 2, Python 3 and C ++.

You can choose OS flavors like Ubuntu 16, Ubuntu 18.04,Centos 7 or Windows 2016 with NVIDIA TESLA V100 and T4 GPU Servers.