Clusterone is a deep learning platform that makes it simple and fast to run deep learning workloads of any scale and complexity on any infrastructure. Clusterone puts data scientists first. It removes the time sink of infrastructure management and setup for data science teams by providing a ready-to-use platform and essential tools. For organisations, it reduces project costs by maximizing the efficiency of their data science teams and hardware resources.

Zero DevOps + Maximum Efficiency

Clusterone fully automates infrastructure orchestration and reallocates resources seamlessly to maximise efficiency

Scalability

Clusterone enables running many concurrent experiments. Training large-scale distributed deep learning models becomes effortless

Full Flexibility

Clusterone integrates into any existing technology stack and supports TensorFlow, PyTorch, as well as custom Docker containers

Essential Tools & Interfaces for Data Scientists

User-friendly web and command line interfaces, Jupyter notebooks, TensorBoard®, and experiment-sharing are available

Infrastructure-Agnostic

Clusterone can run on any public cloud (AWS, GCP, Azure, etc), private cloud, or on-premises. Easily switch between solutions without changing any workflows

Lower Infrastructure Cost

Clusterone optimises resource utilization and enables lower computing costs through its innovative cluster management technology

Created by Data Scientists for Data Scientists

Deep learning scientists are rare and can be difficult to recruit. So when an organisation succeeds in assembling a team of them, the prime goals should be to keep them productive and motivated. Yet because their teams are small, they often get overlooked when it comes to technical help in setting up the optimal infrastructure for their work. Clusterone - created by deep learning scientists for deep learning scientists—takes the pain and lost time out of provisioning resources, deploying clusters, creating orchestrations, and managing projects. Clusterone helps organizations maximize the efficiency of their deep learning scientists, while at the same time enhancing satisfaction of these scientists by off-loading tedious, but essential tasks.

Clusterone helps organizations to get the maximum value from their hardware resources. Clusterone’s Elastic GPU Scheduler detects unused processors and makes them available to others on the team when working with on-premises boxes. When working in the cloud, Clusterone’s dynamic scheduling and auto-scaling can spin up and spin down resources - this means scientists always have the resources their work requires without incurring billing for idle hardware instances.

Data Scientists
Apps
Interface
OS
Infrastructure

Professional Services – The Applied AI Team

In addition to the efficient, scalable, and easy-to-use deep learning platform, Clusterone offers professional services through the Applied AI Team. Scan can work with you and leverage resource from the Applied AI Team to help your organisation with design and installation of Clusterone resources. We can also advise on modelling, training, and related areas to bring an organization swiftly up to production speed.

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