Deep learning is part of the machine learning methods that use one of a set of algorithms to learn high-level representations of data. Such algorithms have been successfully applied to a large variety of problems ranging from image classification to natural language processing and speech recognition.
Graphics Processing Units (GPU) have proved to accelerate deep learning research with thousands of computational cores. Operations are hundred times faster when compared to central processing units (CPU) alone.
Caffe2, Cognitive Toolkit, Mxnet, Pytorch, Tensorflow and others rely on GPU-accelerated libraries such as CUDNN and NCCL conform the software needed to deliver High Performance multi-GPU accelerated training.
In collaboration with Amber MD development team, we have developed Deep Learning Workstations, featuring NVIDIA GPU technology, for developers to get started with deep learning and AI research now.
LinuxVixion Deep Learning GPU Solutions are fully turn-key and designed for rapid development and deployment of optimized deep neural networks with multiple GPUs.
We offer a dev box stack for developers who want pre-installed frameworks. Our packs contain GPU drivers, libraries and software for deploying your own DL environment with the flexibility of containerization. This is all software included:
The NVIDIA Deep Learning GPU Training System (NVIDIA Digits) is an interactive deep learning development tool for scientists and researchers to quickly design deep neural networks (DNN) using real-time network behavior visualization.
NVIDIA Digits is a complete system for developing an optimized neural network for a single data set or training multiple networks on many data sets.
Full turnkey solutions ready to use
Installation of complete software stack
Validated and certified GPU systems
Secure and fast shipping to all Europe