Berkelium: High-Performance Kubernetes for LBNL Science
The dedicated, multi-tenant Kubernetes platform engineered by LBNL Science IT to empower laboratory scientists with elastic container orchestration, GPU-accelerated computing, JupyterHub environments, and high-throughput scientific data pipelines.
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Accelerated Scientific Workloads & GPUs
Berkelium connects high-performance NVIDIA compute (A100, H100, L40S) directly to modern containerized workflows. Run distributed PyTorch, TensorFlow, AlphaFold, Ray, or MPI jobs with native Kubernetes scheduling.
- NVIDIA GPU Operator with MIG (Multi-Instance GPU) support
- Interactive JupyterLab & Kubeflow notebook environments
- High-throughput pipeline automation via Argo Workflows & Nextflow
- Direct integration with LBNL parallel storage systems
Self-Service Multi-Tenant Namespaces
Scientists and research groups can provision dedicated, isolated Kubernetes namespaces in seconds with tailored CPU, memory, and GPU quotas, authenticated via your institutional LBNL OneID credentials.
- Instant self-service namespace provisioning and quota tier management
- LBNL LDAP / Single Sign-On (SSO) authentication & RBAC
- Automated kubeconfig and CLI token generation
- Granular network policies and secret management via Vault
Backed by LBNL Science IT Expertise
Our team of computational scientists and infrastructure engineers provides direct consultation, containerization support, and workflow optimization to help your project thrive.
- Hands-on container migration (Docker, Apptainer, Singularity)
- Weekly office hours & Slack support at #berkelium-users
- Continuous monitoring, Prometheus/Grafana metrics, and automated backups
- Seamless bridging between Kubernetes and HPC/Slurm clusters
Trusted by Research Teams Across Berkeley Lab
See how scientists across LBNL divisions utilize Berkelium to streamline simulations, AI/ML models, and experimental beamline data processing.
Berkelium allowed our beamline data analysis pipeline to automatically autoscale with live X-ray diffraction streams. The self-service namespace made deployment straightforward for our postdocs.
Dr. Elena Vance
Staff Scientist, Advanced Light Source (ALS)
Having instant access to dedicated A100 GPUs for structural biology and cryo-EM model training without complex queue waiting has increased our group's publication throughput significantly.
Dr. Marcus Chen
Computational Biologist, Biosciences Area
Science IT's support on Berkelium is world-class. Integrating our microservices with the lab's OIDC authentication and Ceph storage volumes took less than an afternoon.
Sarah Lin
Data Systems Engineer, Energy Sciences Network (ESnet)
The bridge between Kubernetes containers and HPC storage gave our detector simulation group the agility of cloud-native development right on Berkeley Lab premises.
Dr. Rajiv Patel
Research Fellow, Physics Division
Ready to run your scientific computation on Berkelium?
Join hundreds of LBNL researchers scaling their science. Sign in with your LBNL credentials, claim your project namespace, and download your kubeconfig in minutes.
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