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  • Higher compute and storage density options with HPE Alletra Storage MP modules for AI and large-scale, performance-oriented unstructured data lakes5
  • Ultra-efficient all-NVME with inline similarity data reduction (de-deduplication and compression) that works even for previously compacted data
  • Acceleration of Artificial Intelligence (AI), Machine Learning (ML) and Deep Learning (DL) training and inferencing in conjunction with the consolidation of other workloads
  • End-to-end HPE GreenLake experience for unstructured data management

主要功能

Accelerate with Enterprise Performance at AI Scale that Spans all the Stages of AI

HPE GreenLake for File Storage MP delivers enterprise performance at AI scale for the most demanding data-intensive applications using disaggregated-shared-everything (DASE) architecture.  Unlock more value from all your data with faster time to insights and discovery for competitive advantage.

The architecture is designed to scale to exabytes and offers independent scaling of performance and capacity.  Unlock more value from all your data with faster time to insights and discovery for competitive advantage.

With 80x faster performance1 than legacy NAS and 100s of GB/sec of throughput and beyond for read performance3, HPE GreenLake for File Storage MP delivers high performance for all of your file data without tiering.

It provides 99.9999% availability 2, is completely fault tolerant, provides more resiliency than direct-attached storage systems, and is capable of withstanding rack failure for superior protection at scale.

Simplify at AI Scale with an Intuitive Cloud Experience

HPE GreenLake for File Storage MP provides radically simple file data management that is cloud-resident and delivers rich data services including file share vending, lifecycle management, hybrid cloud backup, and disaster recovery, all via HPE GreenLake edge-to-cloud platform.

Configured systems are automatically discovered and on-boarded in minutes. Empower data scientists and LOB application owners with increased productivity and focus on discovery and innovation rather than wasting time working with cumbersome legacy file systems.

Instantly see usage, activity, and throughput at any level of the unified directory structure no matter how many files are in the file system. Identify problem areas and hot spots to optimize resource utilization.

Leverage real-time visibility to set quotas at user and/or capacity level with configurable alerts on quota breaches in real time.

Enhance Efficiency at AI Scale Productivity for Increased ROI

Superior, highly efficient data reduction and protection storage technologies that deliver low cost/TB for higher ROI.4

Optimize GPU utilization with InfiniBand, GPU-direct, and RDMA support.

Efficient scaling with flexible disaggregated shared-everything architecture that meets storage demands without overprovisioning. Efficient, flexible AI storage as a service.

Achieve high sustainability with capacity density, data center footprint, power, and cooling efficiencies for reduced carbon footprint.6

1 80x faster performance: https://www.hpe.com/psnow/doc/a00058506enw

2 99.9999% availability: https://www.hpe.com/psnow/doc/a00058506enw

3 100s of GB/sec of throughput for read performance: https://www.hpe.com/psnow/doc/a00058506enw

4 Data reduction: Up to 2:1 for life sciences data; 3:1 for pre-reduced backups, pre-compressed log files, and HPC and animation data; and 8:1 for uncompressed time-series data: https://www.hpe.com/psnow/doc/a00058506enw

5 2X throughput; 2X performance per TB density

6 4X capacity per U density; half the power

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