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Big Data
Business Honor
22 May, 2025
Together, HPE and NVIDIA combine advanced SDKs and AI-driven infrastructure to streamline big data plans.
NVIDIA and Hewlett Packard Enterprise (HPE) have deepened collaboration to accelerate enterprise big data strategies with AI-infused infrastructure. At the core of this initiative is HPE Private Cloud AI, which now enables feature branch model updates from NVIDIA AI Enterprise, such as AI frameworks, NVIDIA NIM microservices, and software development kits (SDKs)—all focused on making big data processing and AI model deployment more streamlined.
The feature branch model support gives developers the power to test, tune, and verify software improvements optimized for large-scale AI workloads, essential in big data analytics scenarios. Combined with production-level models featuring integrated safety guardrails, this release allows organizations to develop and grow agentic and generative AI (GenAI) applications securely on distributed systems.
One of the primary advancements in data intelligence is the availability of a new SDK for the HPE Alletra Storage MP X10000, natively integrated with the NVIDIA AI Data Platform reference architecture. This combination of power delivers a capability for enterprises to precisely manage and process unstructured data pipelines, enabling data ingestion, inference, training, and continuous learning on GPU-accelerated infrastructures.
Major big data capabilities are vector indexing, inline data processing, and metadata enrichment, which enable organizations to unlock value from large, complex data sets. The platform leverages Remote Direct Memory Access (RDMA) to stream data effectively between GPU, system memory, and storage, significantly reducing the path of data and increasing performance.
Built on composable, modular infrastructure, the X10000 enables businesses to independently scale storage and compute, meeting the needs of expanding data lakes and real-time analytics.
This joint effort between HPE and NVIDIA marks the beginning of a new age in big data architecture, facilitating real-time, AI-driven data access from the edge to the core to the cloud, and giving businesses the power to gain actionable insights from enterprise data at scale and speed like never before.