HPE Open Source
Open source collaboration is in HPE's DNA. We believe open source technologies and communities can help deliver innovative solutions securely and at scale. HPE is proud to provide, support, use and contribute to several open source projects.
LL-Mesh—Democratizing Gen AI
Join us on December 18, 2024 to learn more about this pioneer initiative by HPE.
Getting started with HPE Open Source
HPE has a long and deep history of engineering collaboration and open source engagement. We have broad development goals which leverage a number of targeted GitHub organizations.
HPC & AI
Security & UX
Open Source resources and on-demand workshops
Open Source foundations
Cloud Native Computing Foundation (CNCF)
Silver 2024
HPE engages in fundamental cloud-native, container, monitoring, edge, and AI projects such as Kubernetes, Istio, Prometheus, etcd, Kubeflow, SPIFFE/SPIRE, etc. These communities and technologies are important for HPE GreenLake, Ezmeral, security, and developer offerings.
DAOS Foundation
Founding Member
DAOS is highly scalable data-centric software for high-performance shared access to current and next-generation solid state storage devices. HPE is involved in the DAOS Foundation to help grow the ecosystem of DAOS developers and consumers and to create highly scalable data-centric software for high-performance shared access to current and next-generation solid state storage devices. In particular, HPE’s HPC Storage team is contributing source code, testing, and governance to the DAOS project.
Open Programmable Infrastructure Project
Silver 2024
The Open Programmable Infrastructure (OPI) Project, under The Linux Foundation, fosters a standards-based ecosystem that provides operator-tenant isolation in a cloud native infrastructure using emerging technologies such as Data Processing Unit (DPU). HPE participates in the Device Provisioning and Lifecycle workgroup that defines standard methods to discover, boot, provision and manage DPUs.
ML Commons
HPE actively participates in MLPerf research groups and publishes performance results for HPC, Storage, AI Training, AI Inference, AI Safety, & other areas. MLPerf is a set of open industry-standard benchmarks, datasets, and research measuring quality and performance of HPC and AI workloads.