Clusters for Machine Learning

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Overview

The promise of machine learning is pulling every organization in every industry into the realm of high-performance computing. Many organizations have little or no experience with these systems, and even the most experienced high-performance computing practitioners will tell you that building and managing high-performance Linux clusters is no easy task. With hundreds or thousands of hardware and software elements that must work in unison, spanning compute, networking and storage, the skills, knowledge and experience required to do this is often more than an organization can cope with. Bright Cluster Manager software offers an integrated solution for building and managing machine learning clusters that reduces complexity, accelerates time to value and provides enormous flexibility. Bright Cluster Manager also provides a pre-tested catalog of popular machine learning frameworks and libraries, as well as integration with Jupyter Notebook, to ensure that data scientists can be as productive as possible and not waste time managing their work environment.

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Bright Cluster manager

Automated cluster
provisioning & setup

  • Provisions nodes from bare metal
  • Sets-up network, user directory & security
  • Configures and deploys Kubernetes
  • Includes pre-configured machine learning frameworks and libraries, Jupyter Notebook integration and supports NGC containers
  • Runs pre-checks across the entire cluster prior to deployment
  • Provisions nodes from bare metal
  • Sets-up network, user directory & security
  • Configures and deploys Kubernetes
  • Includes pre-configured machine learning frameworks and libraries, Jupyter Notebook integration and supports NGC containers
  • Runs pre-checks across the entire cluster prior to deployment

Automated problem
detection and isolation

  • Provides detailed monitoring metrics & health-checks
  • Reports resource usage by application and user
  • Allows automated corrective actions to be taken
  • Automatically detects and images replacement nodes

Automated change
management

  • 1-step propagation of updates
  • Auto-update nodes without reimaging
  • Easily add more servers & new components
  • Replace failing nodes without disruption
  • Prevents image-drift amongst nodes

Unparalleled
Flexibility

  • Supports mixed processor, accelerator and Linux combinations within the same cluster
  • Run jobs on bare-metal, VMs or containers in the same cluster
  • Extend to the public cloud for additional resources
  • Dynamically allocate resources where they’re needed based on demand
  • Re-image nodes on the fly to host new applications
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WATCH THE VIDEO: BRIGHT CLUSTER MANAGER AUTOMATES BUILDING & MANAGING LINUX CLUSTERS THAT SPAN FROM EDGE TO CORE TO CLOUD
Linux clusters are powering a whole new generation of business innovation. Powerful new hardware, applications and software have system administrators struggling with complexity, while providing  a system that is both flexible and reliable for end-users. Bright Cluster Manager eliminates complexity and enables flexibility by allowing users to deploy complete clusters over bare metal and manage them reliably from edge to core to cloud.
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WHAT'S NEW IN BRIGHT CLUSTER MANAGER 9.0

Bright 9.0 provides several new capabilities for forward-thinking organizations:

  • Deploy any number of workload clusters across your enterprise from the edge to core to cloud
  • Simplified management for clusters that use multiple software images and/or hardware architectures
  • Powerful data management capabilities that enable cloud jobs to run sooner while reducing file transfers to the cloud
Click the banner to see the latest updates to our enterprise-grade cluster management solution.
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Machine Learning Resources

img-rc-BCM4DS80-ds-241Data Sheet: Bright Cluster Manager for Data Science

Find out more about the Data Science add-on for Bright Cluster Manager in our product data sheet.

NVIDIA WPRealize the Massive Potential of your AI Infrastructure

Learn more about Bright Cluster Manager on NVIDIA DGX Systems.

 

 

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