HPE Machine Learning Development System
Scale AI model training from idea to impact with minimal code rewrites or infrastructure changes.
Uncover hidden insights
Learn how HPE Machine Learning Development System enables you to focus on innovation, not infrastructure.
Speed innovation and reduce IT complexity for AI/ML model training
Out-of-the-box performance profiles and on-site installation, configuration and set-up reduce IT complexity and frees up your teams to focus on AI/ML model development.
Purpose built, validated and pre-configured
Integrated hardware, software and services solution ready for model development and training on day one. Quickly respond to users by delivering the compute and technical infrastructure required for successful model development.
Future proof your AI-infrastructure
Choose from a range of compute and storage configurations to stay in front of evolving needs and build a foundation for heterogeneous accelerators. This purpose built, validated and pre-configured solution delivers an integrated hardware, software and services solution ready for model development and training on day one.
HPE Machine Learning Development System Independent Evaluation Results
ESG recently evaluated the HPE Machine Learning Development System, exploring how the system can help organizations accelerate their time to insight, providing tools to accelerate and simplify model development and training. The team reviewed the productivity, ease of use, flexibility, performance, and investment value of the solution.
Take the next steps
Ready to get started? Explore purchasing options or engage with HPE experts to determine the best solution for your business needs.
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Technical specifications
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Pre-configured, fully installed and performant out of the box
Out-of-the-box performance means reduced IT complexity
Focus time and resources on model-development.
On site installation, configuration and standard model setup.
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Manageability and observability
Monitor infrastructure and model metrics through single interface.
Improved experiment tracking and collaboration between ML engineers.
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Component architecture
Compute Node – Apollo 6500 Gen10+ with NVIDIA® A100 8 way 80GB GPU.
Management Node – Proliant DL325.
Cluster Manager - HPCM.
Storage – HPE Parallel File System.
NVIDIA Infiniband.
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Software and hardware supported
Software: HPE Machine Learning Development Environment, HPE. Performance Cluster Manager, Red Hat Linux, SUSE Linux.
Hardware: HPE Apollo 6500 Gen 10 plus NVIDIA® A100 8-way 80GB. GPU, HPE Proliant DL325, NVIDIA Infiniband, HPE Parallel File System.