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HPE Machine Learning Development Environment Software 8+ GPU 1yr Managed Service Subscription E‑RTU

S2E66AAE

HPE Machine Learning Development Environment Software 1‑8 GPU 1yr Managed Service Subscription E‑RTU

S2E65AAE

HPE ML Dev Env SW 1‑19 GPU 1yr Sub E‑RTU

R8W23AAE

HPE ML Dev Env SW 20‑99 GPU 1y Sub E‑RTU

R8W26AAE

HPE ML Dev Env SW 100+ GPU 1yr Sub E‑RTU

R8W27AAE

HPE ML Dev Env 3yr Sub E‑RTU

R9H29AAE

HPE Machine Learning Development Environment 4‑year Subscription E‑RTU

R9Y51AAE

HPE Machine Learning Development Environment 5‑year Subscription E‑RTU

R9Y52AAE

Key Features

Train Models Faster with Cutting-Edge Distributed Training Strategies and Techniques

HPE Machine Learning Development Environment Software integrates with DeepSpeed for 3D-Parallel (data-, model-, and pipeline-parallel) distributed training, to speed up training of large models like GPT-NeoX.

Enable Horovod for easy-to-use data-parallel distributed training.

Provide PyTorch Distributed Data Parallel (DDP) for flexibility and choice of distributed training strategies.

Find Better Model Configurations Efficiently with Cutting-Edge Hyperparameter Tuning Techniques

HPE Machine Learning Development Environment Software features production-grade implementation from the creators of the Asynchronous Successive Halving (ASHA) Hyperband algorithm for HPE search and optimization.

Define your own logic to coordinate across multiple trials within an experiment.

Implement your own custom hyperparameter search algorithms, ensembling, active learning, neural architecture search, and reinforcement learning.

Easily Share GPUs and Accelerators with ML Workflow-Aware Smart Scheduling and Resource Management

With HPE Machine Learning Development Environment Software, you can easily share your on-premises or cloud GPUs and accelerators with your ML development and operations teams.

Run ML and HPC jobs alongside each other on the same cluster, with support for workload managers like Slurm or PBS, and secure container runtimes like Singularity/Apptainer, Podman, or NVIDIA® Enroot.

Seamlessly use spot or preemptible instances to manage cloud costs.

Train models on NVIDIA or AMD GPUs without any code changes, with foundational support for accelerator heterogeneity.

Consistent user experience for deployments on your laptop to a supercomputer, and everything in-between including: baremetal, virtual machine (including cloud and on-premises IaaS solutions), Kubernetes, Slurm, and PBS.

Track and Reproduce your Work with Integrated Experiment Tracking and the Model Registry

HPE Machine Learning Development Environment Software provides built-in experiment tracking that covers model code, configuration, hyperparameters, metrics, and checkpoints.

Version, annotate, and organize trained models so that MLOps teams can effectively collaborate with model developers to manage your models' lifecycle.

AMD is a trademark of Advanced Micro Devices, Inc. GCP is a registered trademark of Google LLC. Linux is the registered trademark of Linus Torvalds in the U.S. and other countries. NVIDIA is a trademark and/or registered trademark of NVIDIA Corporation in the U.S. and other countries. Red Hat is a registered trademark of Red Hat, Inc. in the United States and other countries. All third-party marks are property of their respective owners.

* Prices may vary based on local reseller.

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