GPU Computing – Series G 

Leverage E2E Networks GPU instances for compute and graphics-intensive workload. Our GPU’s offer high performance and cost-effective means for compute and graphics-intensive processing power, helping you to fuel innovation. It is ideal for workloads such as machine learning, artificial intelligence, graphics rendering, video editing, remote visualization, high-performance computing and many other parallel workloads.

E2E Networks GPU instances are based on NVIDIA’s GeForce® GTX 1080 Ti-series graphics cards which are powered by Pascal™ microarchitecture to deliver breakthrough performance. It can act as a co-processor or can be used for graphics acceleration, thanks to its CUDA cores.

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Why GPU?


GPU is a massively parallel compute architecture which can significantly run a larger number of IOPS than the CPU. The initial GPU usage was for computer graphics (OpenGL/Direct3D) but with CUDA, a parallel computing platform and API allows developers to directly access GPU’s virtual instruction set and parallel computational elements.

The applications such as big data analytics, machine learning, deep learning, Artificial Intelligence can take the benefit of parallelization and can perform the operations much faster than a CPU, yielding performance improvements.

GPU Features

NVIDIA’s GeForce® GTX 1080 Ti

  • 3584 CUDA cores
  • 484 GB/s maximum bandwidth
  • Nvidia GPU Boost 3.0 Technology

Do More with CUDA

  • Run massively parallel workload – Run non-graphic code on a massively parallel hardware
  • Easy to code – A programming language based on C which makes it easy to code
  • Software development kit – Includes libraries, debugging, profiling and compiling tools

E2E’s Advantage

Transparent Pricing Model

Low-cost GPU instances with transparent pricing model & no hidden costs.


High-Performance Compute with the latest gen. CPU + RAM + GPU + SSD.


No upfront cost and up to 60% cost savings as compared to competitors

Accelerate Processes

Ideal for parallel processing workloads to process large block of data at once.

Beneficial for Workloads

E2E Networks Cloud GPU’s can boost Artificial Intelligence, Deep learning, HPC & other massively parallel workloads. 

Artificial Intelligence

E2E Networks is responding to the demand of GPU’s for Artificial Intelligence (Ai), Machine Learning (ML), and particularly Deep Learning (DL) by providing solutions that are computationally more powerful and are extremely flexible to manage in a production environment. These Applications can take advantage of our GPU’s to perform a large number of computations on a vast data.Highly suitable for image recognition applications, video content identification, business intelligence, machine learning and other applications.

Train your Deep learning models efficiently by processing more data with our GPUs and making them learn from images, videos or text data automatically without any human hand-coded rules. No boundaries or hardware limitations with our cloud GPU’s as the more the data you introduce, the higher will be predictive accuracy. Easily perform tasks such as speech recognition, language translation, object identification, face recognition and many other with high-performance and low cost.

E2E Networks Cloud GPU’s can help in Artificial Intelligence (Ai), Machine Learning (ML), and particularly Deep Learning (DL) models beneficial for researchers and data scientists. The developers can rely on E2E Networks cloud GPU platforms for the cloud, embedded device or autonomous cars, to deliver high-performance, low-latency inference to train deep neural networks.

Design & Visualization

E2E Networks GPU instances are ideal to Render, Video and Display solutions. Our GPU instances help researchers, scientists, and developers across industries to benefit from the thousands of Graphics computing cores with the power of accelerated Video processing.

Physics Processing

Our GPU instances can help to produced results of Physics processing engines for particles, fluids, rigid bodies, destruction sequences and are capable to handle large, irregular graph-based models consisting of millions of states and arcs.

Rendering – 2D/3D Graphics, Architects

Push loads of more polygons for your modeling and rendering tasks which means that our Cloud GPUs can handle VFX, 3D rendering and similar tasks like a breeze. Run highly optimized geometry on E2E Networks cloud GPUs and extract your app’s potential.

Video Encoding/Decoding

Accelerate your video editing capabilities which require pixel-level manipulation and huge sized files and a lot of processing power which can be quicken with GPUs

Image processing

Our cloud GPUs can efficiently encode and decode images or perform tasks like the color conversion of images. Such types of applications are changing product plans, customer experiences, predictive support and leading to findings and innovations which were not previously imaginable.


E2E Networks cloud GPU’s are capable to handle simulation workloads and are ideal for Computer-Aided Design, Simulation, Analysis across various industries. Do not get limited by a local server capacity, E2E Networks Cloud GPU’s can make significant performance improvements to your simulation platform and processes with an overall reduction in cost.

Driving/Flight Simulation models

Use E2E’s GPU’s for driving/flight simulators for training and scenario modeling purposes.

Autonomous Driving

E2E Networks Cloud GPU’s can help autonomous driving simulations companies to avoid the expense of considerable upgrades to their infrastructure that would normally require high initial investments in hardware.


Check our plans to get started

₹ 17,249** Per Month or
₹ 23.63* Per Hour
OS: CentOS / Ubuntu
Dedicated RAM: 30 GB
Disk Space: 450 GB SSD
GPU: 1 X NVIDIA GP102 [GeForce GTX 1080 Ti]
₹ 34,499** Per Month or
₹ 47.26* Per Hour
12 VCPUs
OS: CentOS / Ubuntu
Dedicated RAM: 62 GB
Disk Space: 900 GB SSD
GPU: 2 X NVIDIA GP102 [GeForce GTX 1080 Ti]

*  Price is exclusive of 18% GST Rate
**Monthly Prices shown are calculated using an assumed usage of 730 hours per month; actual monthly costs may vary based on a number of days in a month.

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Designed to jump-start your GPU Computing with optimized and Integrated Software Stack, including TensorFlow, GPU drivers, and NVIDIA CUDA for various workloads.