Our Solutions

Compute platform for Data Science

Jumpstart your virtual environment for data Science! Platform featured with RoCM, CUDA, Python, Tensorflow, PyTorch, MXNet frameworks; associated libraries; Standard Datasets (for trials); etc.

Platform for 3D CAD Software’s

High Performance & Low latency graphics rendering! Custom platform featured for 3D Softwares such as SolidWorks, Siemens NX, 3DS-CATIA, AutoCAD and Pro/E

Platform For Accelerated Gaming

Enhanced performance throughput to enjoy power packed action games! Loaded with turbo option to boost the gaming performance

Compute Platform for Data Science

GPUONCLOUD offers you technology, tools and workflows on a scalable, integrated platform for Data Science. While the technology & tools does its work on the Data Science Platform, your team’s remain focused on the substance of the data science, to achieve predictive and prescriptive analysis for business.

With range of options to choose from, the GPUONCLOUD platform provides you options for instant start on the platform with chosen datasets, defined & trained deep learning models to execute on for business outcomes.

The technology powered stack on GPUONCLOUD takes care of maintaining the environments required for development, testing and production workflows. Choose from readily available options for the environments to execute the operations instantly.

GPUONCLOUD provides secured integration options to integrate your business partners who are having on-premise datacenter presence, on-cloud presence and/or by onboarding the business partners.

You would need to select Platform Configurable Components from below table, to launch your Artificial Intelligence environment –

1. Select the Compute Components from AI-C1 to AI-C6 options
2. Select the GPU, basis expected TFLOPS performance from GPU-1 to GPU-3 options
3. Select between Network Connectivity or Server Console access Options for connecting to your compute remotely
4. Select Public IP requirements, if required
5. Select Public Network Bandwidth Option

  • Tensorflow; Kera
  • PyTorch
  • MXNet
  • Docker
  • OS- Ubuntu 16.04 TLS and above is configured for selected Instance

GPU – 1

  • AMD Radeon RX570-4GB
  • RoCM
  • OpenGL 4.5
  • Maximum 6 GPU’s per Compute leading to allocation of 5.1 TFLOPS upto 30.6 TFLOPS of cumulative performance per instance

GPU – 2

  • Nvidia Tesla K80-12GB
  • OpenACC
  • CUDA
  • Maximum 3 GPU’s per Compute leading to allocation of 8.73 TFLOPS upto 26.9 TFLOPS of cumulative performance per instance

GPU – 3

  • Nvidia Tesla V100-32GB
  • OpenACC
  • CUDA
  • Maximum 3 GPU’s per compute leading to 100 TFLOPS to 300 TFLOPS of cumulative performance per instance

 

  • S2S VPN
  • C2S VPN
  • OPENVPN (2-free device connections for 1st year)
  • 256 bit encryption
  • Software based VPN
  • Secured Remote Desktop Access
  • SSH
  • Custom solution for Ubuntu
  • SSH access through public IP or Domain Name
  • Static
  • Up to 4 IP’s
  • Shared
  • Dedicated
  • Up to 50MBPS

Platform for 3D-CAD Software’s

Time to market is the key factor for product designs – GPUONCLOUD offers the platform with multiple GPU options providing essential speed in simulation of the computer aided designs thereby enhancing the productivity at work.

GPUONCLOUD enables enterprises with an option to instantly scale up the design capacity in order to cater to sudden spikes in the demand or to accelerate the design cycle.

GPUONCLOUD offers competitive custom built platform to optimize the costs involved in designing, building, upgrading, procuring the high-end workstations for 3D-CAD designs.

You would need to select Platform Configurable Components from below table, to launch your 3D-CAD Software environment –

1.Select the Compute Components from 3D-C1 to 3D-C3 options
2. Select the GPU, basis expected TFLOPS performance between GPU-1 to GPU-2 options
3. Select between Network Connectivity or Server Console access Options for connecting to your compute remotely
4. Select Public IP requirements, if required
5. Select Public Network Bandwidth Option

  • SolidWorks
  • 3DS-CATIA
  • Siemens – NX
  • Pro/E
  • Autodesk
  • Windows OS is configured for selected Instance

Please note – Network license essential for portability

GPU – 1

  • AMD Radeon RX570-4GB
  • OpenGL 4.5
  • OpenGL 4.5
  • Single GPU allocation leading to 5.1 TFLOPS of performance per instance

GPU – 2

  • Nvidia Tesla K80-12GB
  • OpenACC
  • CUDA
  • Maximum 3 GPU’s per Compute leading to allocation of 8.73 TFLOPS upto 26.9 TFLOPS of cumulative performance per instance
  • S2S VPN
  • C2S VPN
  • OPENVPN (2-free device connections for 1st year)
  • 256 bit encryption
  • Software based VPN
  • Secured Remote Desktop Access
  • Custom solution for Windows
  • Static
  • Up to 4 IP’s
  • Shared
  • Dedicated
  • Minimum 2MBPS up to 50MBPS

Accelerated Gaming Platform

GPUONCLOUD offers cost effective, dedicated gaming platform enabled with boost options customized for specific games.

Options to choose are to have the direct access to the powerful gaming desktop or to run the games through standard browsers from any device.

Enjoy installing any game of your choice and unlimited hours of gaming!

You would need to select Platform Configurable Components from below table, to launch your Accelerated Gaming environment –

1.Select the Compute Components from AG-C1 to AG-C3 options
2.Select the GPU, basis expected TFLOPS performance between GPU-1 to GPU-2 options
3.Select between Game Access method
4.Select Public IP requirement
5.Select Public Network Bandwidth Option

  • Selected games in from collection
  • Windows OS is configured for selected Instance
  • Please note – Network license essential for portability

GPU – 1

  • AMD Radeon RX570 -4GB
  • OpenGL 4.5
  • Single GPU allocation leading to 5.1 TFLOPS of performance per instance

GPU – 2

  • Nvidia Tesla K80-12GB
  • OpenACC
  • Maximum 3 GPU’s per Compute leading to allocation of 8.73 TFLOPS upto 26.9 TFLOPS of cumulative performance per instance
  • Secured Remote Desktop Access
  • Standard Internet browser
  • Custom solution for Windows
  • Static
  • 1 IP per gaming desktop
  • Shared
  • Dedicated
  • Minimum 4MBPS up to 50MBPS

GPUONCLOUD typical solutions to product mapping

Solutions Products A typical Product Configuration Upgrades CUSTOM
Compute platform for data science

  • Ubuntu OS 16.04 TLS & Above
  • From 1vCPU/1GiB-RAM/50GB -HDD upto 12vCPU/240GiB-RAM/5TB -HDD
  • 5.1 TFLOPS upto 300 TFLOPS per instance
  • Tensorflow/PyTorch/MXNet framework

  • + 1vCPU/1GiB-RAM/20GB-HDD
  • + 5.1 TFLOPS
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Platform for 3D-CAD Software’s

  • Windows
  • rom 1vCPU/1GiB-RAM/30GB-HDD upto 7vCPU/120GiB-RAM/1TB-HDD
  • 5.1 TFLOPS upto 30.6 TFLOPS per instance
  • 3DS-CATIA; AutoCAD; UX; Pro/E license portability

  • + 1vCPU/1GiB/20GB-HDD
  • + 5.1 TFLOPS
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Gaming Platform

  • Windows
  • From 1vCPU/1GiB-RAM/30GB-HDD upto 7vCPU/120GiB RAM/1TB-HDD
  • 5.1 TFLOPS upto 30.6 TFLOPS
  • Multiple Boost Options

  • + 1vCPU/1GiB-RAM/20GB-HDD
  • + 5.1 TFLOPS
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