AI, ML, and analytics

Is your enterprise class storage holding you back because you are tied down administering, tuning, and supporting infrastructure? Are you looking to shift to a cloud everywhere experience with the same agility, simplicity, and cloud consumption for every application?

HPE Alletra powers your data from edge-to-core with the cloud experience for all your apps. For business-critical workloads, HPE Alletra 6000 delivers fast, consistent performance and industry leading data efficiency. It enables IT to shift from owning and maintaining data infrastructure to simply accessing and utilizing it on-demand, as-a-service. Eliminate performance and efficiency trade-offs with no knobs or configurations to adjust and always-on data services. Get resilient storage with intelligence and a no single point of failure platform that together deliver 6x9s¹ availability guaranteed. Deliver on recovery SLAs with fast, integrated app aware backup and recovery, on-premises and in the cloud.

Do you need a powerful solution to meet today's supercomputing challenges?

HPE Cray supercomputers enable you to tackle infrastructure challenges that require the fusion of modeling and simulation workloads with analytics, AI, and the Internet of Things (IoT) to create a single business-critical workflow. Today's high-performance computing systems must be able to handle these massive and converged workloads, leading to a supercomputing sea-change.

With the imperative to navigate increasingly diverse and complex workloads, the next generation of supercomputers will be differentiated by exascale performance, data-centric workloads, and diversification of processor architectures.
HPE Cray supercomputers deliver application HPC and AI performance at scale, provide a flexible solution for tens to hundreds to thousands of nodes, and deliver consistent, predictable, and reliable performance, facilitating high productivity on large-scale workflows.

Are business insights and innovation slowed by restricted access to data? HPE Ezmeral Data Fabric securely works around data silos to aggregate different data types and formats into a single data backbone that accelerates analytics and AI without complex ETL processes or copying of data. Customers report faster data management, building of models 75% faster¹ and the ability to handle more types of data and modeling algorithms than ever before.  

Layer on open source tools and frameworks from the certified ecosystem to process data at its point of creation across hybrid, edge, and multicloud environments. 

Empower data teams to search and pinpoint the exact data with metadata and data intelligence from BigID. Truncate data discovery from days/weeks to minutes, identify unprotected sites, then apply remediation policies, encrypt or move data. Ensure that data is being accessed and used to organizational policies.

Together, HPE and Qumulo simplify your data anywhere and with the choice to consume as-a-Service via HPE GreenLake. Reliably store and manage billions of files that can be securely accessed via rich file protocols and an S3 API with instant control at lower cost, higher performance, at the edge, in the datacenter and in the cloud. With purpose-built all-NVMe flash and NVMe-accelerated hybrid flash systems forged from industry leading HPE Apollo 4000 and HPE ProLiant DL servers, you can achieve the ideal mix of price, performance, and capacity to address your specific unstructured data needs now and into the future. HPE Solutions for Qumulo empower you to store, transform, protect, and deliver file data at petascale.

Are your most demanding compute jobs slowed by performance bottlenecks? Workloads in financial services, life sciences, manufacturing, and artificial intelligence (AI)/machine learning (ML) need a modern data platform that eliminates those performance barriers. HPE Solutions for Weka is a scalable data platform that is ideal for performance-intensive workloads. The WEKA Data Platform is built on WekaFS, a data-efficient, flash-native, POSIX file system that delivers the high IOPS and low-latency throughput needed for demanding compute requirements. The platform provides policy-based tiering, so data can span between NVMe flash to object storage in a single namespace for easy management and cost-effective economics. The same software is available in the cloud with integrated data mobility. For performance-intensive workloads the WEKA Data Platform employs an innovative storage architecture to provide performance at exabyte scale to solve today’s biggest data-intensive problems.

Does your organization need an on-premises cloud storage solution for modern data-intensive applications? HPE Solutions for Scality provide object storage for scalable unstructured data archives and tiers behind primary storage arrays. Now, cloud-native applications and high-performance analytics tools are increasingly using object and the S3 API as their persistent storage layer. To meet this need, Hewlett Packard Enterprise and Scality® offer two solutions that scale easily from terabytes to petabytes on a full portfolio of customizable platforms and media types.

For Enterprise IT:
Scality RING enable enterprises to quickly build on-premises object storage in scalable clusters, with native S3 API and file access protocols.

For Application Developers:
Scality ARTESCA is a fully-containerized object storage solution with built-in multi-cloud federated data management for S3-centric data workloads and ultra-reliable dual-level erasure coding.

The HPE Ezmeral Unified Analytics solution modernizes legacy data and applications to optimize data-intensive workloads from edge to cloud to deliver the scale and elasticity required for advanced analytics.

Organizations in every industry are looking to leverage AI and ML to harness the power of their data and deliver business innovation through data science. But even when they achieve some measure of success with machine learning pilot programs, many organizations face challenges when they seek to scale these programs to production: security concerns, legacy hardware, siloed data and workflows, inefficient processes, and daunting costs.

To deliver the value of ML and data science to your enterprise, the HPE GreenLake platform delivers an enterprise-grade ML cloud service that enables developers and data scientists to rapidly build, train, and deploy ML models—from pilot to production, at any scale. This solution comprises an optimized hardware stack and is powered by HPE Ezmeral ML Ops. It provides data scientists with self-service access to a sandbox environment for prototyping and testing, to eliminate IT provisioning delays, ensure repeatability, and accelerate time-to-value.

Most enterprises store diverse data types across multiple platforms, such as on-premises data centers, multiple clouds, and at the edge. Each environment becomes an independent silo that restricts access to the data and the insights they contain. This means slower time to modernize analytics and gain the insights that you need to innovate and drive your business.

The HPE GreenLake platform offers a fully managed, on-premises service containing an analytics-ready data fabric for hybrid environments. From a single management view, it allows you to set up, administer, and manage globally distributed data sets across edge-to-cloud deployments. It lowers risk by providing infrastructure in a pay-per-use model, while HPE Ezmeral Data Fabric modernizes analytics and data management, unifying different data types across on-premises, multi-cloud, and edge, and delivering seamless access to a trusted source of data.

To help you mine continuous streams of value locked in your data, HPE GreenLake delivers a trusted, enterprise-grade AI/ML and analytics cloud-like experience so you can accelerate your data modernization initiatives, from edge to cloud. With a cloud-native architecture, support for open source data science tools, and AI accelerators and frameworks, it provides choice and an elastic, unified analytics platform for data and applications on-premises, at the edge, and in public clouds. The consistent experience helps data, IT teams, developers, and analysts simplify the complexities of machine learning lifecycles and data management at scale, leading to better, faster decisions no matter where your data resides.