Deep learning is a subset of machine learning which is completely based on artificial neural networks. As the neural network is going to copy the human brain, so deep learning is also a kind of copy of the human brain. The idea of deep learning was started a few years back, but it is gaining more popularity nowadays because earlier, we did not have that much processing power GPU servers and cloud computing, which allows hourly billing.
Since now, we have much more processing power machines like NVIDIA Tesla V100 GPU servers, but cost still remains an issue. There are free options like Google Colab but are only recommended for testing purposes, or you need to go for other vendors, which comes with a hefty cost of GPU servers.
To solve cost concern for companies and individuals/ students, E2E has come up with NVIDIA Tesla V100 with 70% cost savings as compared to other vendors in the market.
E2E GPU Cloud seamlessly lets you run deep learning workloads based on various frameworks and libraries like TensorFlow, PyTorch, Theano, Caffe2, MXNet, and many more popular deep learning libraries.
Another advantage of the E2E GPU Cloud is that the GPU cards NVIDIA Tesla V100 come attached dedicatedly to the Cloud Instances, and they not shared with any other customer. This will ensure that your workloads running on GPU instances will have 100% access to the processing power of the underlying GPU cards.
E2E GPU offers NVIDIA Tesla V100 Instances with 32GB on-board graphics memory, making it highly-efficient for handling large data volumes of your deep learning workloads.
So, if you would like to learn more about E2E GPU Cloud offerings and evaluate the performance, please reach out to email@example.com