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NVIDIA Base Command

Cluster Management Software for Industrial HPC
NVIDIA Elite Partner

Base Command Platform is one of the key NVIDIA tools for making AI infrastructure accessible to developers.  The NVIDIA Base Command Platform enables an intuitive, fully featured development experience for AI applications. It was built to serve the needs of the internal NVIDIA research and product development teams. Now, it has become an essential method for accessing on-demand compute resources to train neural network models and execute other accelerated computing experiments. 

Base Command Platform simplifies AI experimentation workflows by providing a cohesive service that integrates users, jobs, and data. It provides easy access to a private registry to host custom containers as well as the breadth of software from the NGC Catalog. It offers all these features without sacrificing reliable NVIDIA performance, flexibility, and scalability. You can use Base Command Platform for experiments requiring a single GPU or a data center’s worth of them.

Base Command Platform interface and features

Base Command Platform supports a CLI, API, and web interface, all built into the NGC portal. The integrated web interface makes software discovery in the NGC Catalog and subsequent use in Base Command Platform smooth.

You don’t have to transition between tools not designed to be used together.

In addition to providing access to the public NGC Catalog, you also gain access to a private registry dedicated to the Base Command Platform environment. The private registry is useful for keeping containers, models, and software private and secure, as dictated by developer requirements.


Simple yet powerful hardware abstraction

In Base Command Platform, the managed hardware resources are presented to the user through two concepts: accelerated computing environments (ACEs) and instances within an ACE. 

An ACE is a composition of a set of hardware resources: compute, network, and storage. An instance selects the CPU, RAM, and GPU resource quantities that a job requires from a system within an ACE. 

ACEs can support a variety of instance types depending on their underlying hardware composition. Administrators can restrict the use of these resources through a quota for GPU hours, as well as completely restricting instance type availability for specific users in the org. 

The scheduler in Base Command Platform is designed to take advantage of interconnect topology awareness to provide optimal resource use for jobs as they are submitted.


The Best of NVIDIA Software 


AI Job Scheduling and Workload Orchestration 


Comprehensive Cluster Management 

The same software that supports NVIDIA's thousands of in-house developers, researchers and AI practitioners is now available featuring best of breed developer software, infrastructure management and accelerated infrastructure libraries. 

Base Command delivers an easy-to-use, enterprise-proven scheduling and orchestration solution based on well-established enterprise standards. 

NVIDIA base Command Manager provides full-featured cluster management. 

NVIDIA Bright Cluster Manager Solutions

Clusters for HPC This is an integrated solution for building and managing HPC clusters that reduces complexity, accelerates time to value, and provides enormous flexibility.

Clusters for Machine Learning With a pretested catalog of popular machine learning frameworks and libraries, as well as integration with Jupyter Notebooks, end users can be as productive as possible, wasting no time managing their work environment.

Clusters for Edge Computing Organizations can deploy and centrally manage distributed computing resources as a single clustered infrastructure from a single interface.

Clusters as a Service Organizations can quickly and efficiently spin up high-performance clusters on demand using resources in VMware vSphere or public clouds.

Clusters for Hybrid Cloud This solution automates the process of building and managing a Linux cluster, as well as the process of extending an on-premises cluster to the public cloud. 

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