Enhance the speed of complex processing required for machine learning, deep neural networks, artificial intelligence models, medical analysis, seismic exploration, video transcoding and scientific simulations.
Extract essential compute performance from parallel computing leveraging GPUs on GPUONCLOUD platforms to handle your most complex compute-intensive tasks.
GPUONCLOUD offers platforms to gain access to – GPUs capable of teraflops of performance, custom built platform and framework for Deep learning, 3-D design & modeling, and accelerated gaming.
GPUONCLOUD platforms are powered by AMD and NVidia GPUs featured with associated hardware, software layers and libraries.
Gain access to this special purpose built platforms, having AMD and NVidia GPU’s, featuring deep learning framework like TensorFlow, PyTorch, MXNet, TensorRT, and more in your virtualized environment!
Jumpstart your virtual environment for data Science! Platform featured with RoCM, CUDA, Python, Tensorflow, PyTorch, MXNet frameworks; associated libraries; Standard Datasets (for trials); etc.
GPUONCLOUD offers scalable platforms & products, catering to high performance parallel computing needs on cloud. The GPUONCLOUD platforms provides jumpstart for virtualized environment, powered with scalable Teraflops of GPU performance and associated frameworks – enabling instant start for artificial intelligence based models, 3D Computer Aided Design (CAD) and accelerated gaming.
- Compute platform for data science
- Platform for 3D-CAD Software’s
- Platform for Accelerated Gaming
Deep learning, 3D modeling, simulation, and molecular modeling takes few hours instead of days by leveraging on GPUONCLOUD platforms & products, having AMD and NVidia GPUs. GPUONCLOUD platform is designed with an option for cumulative parallel computing performance connecting to multiple GPU’s at the same time thereby availability of numerous Cores and thousands of concurrent threads to maximize floating point throughput.
GPUONCLOUD scalable compute
|Microsoft Windows Workstation and Server OS
Ubuntu 16.04 LTS (Xenial Xerus) & above
|Multi cores 1 to 12 cores of Intel CPU’s 2.4 GHz to 4.2 GHz per core||1GiB to 256 GiB||Nvidia Tesla V100;
Nvidia Quadro M4000;
AMD Radeon RX-470/570
1 to 6 numbers of GPU’s per instance –
|50GB to 5TB|
OpenGL 4.5 & DirectX API access and library support, Deep Learning frameworks including TensorFlow, PyTorch, MXNet, Caffe/2, and more.
3D-CAD Software’s such as 3DS-CATIA, Siemens-UX, Autodesk, Pro/E etc.
Accelerated Gaming Software’s