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General
The on-premise infrastructure is based on the Kubernetes framework, an open-source container-orchestration framework for automating deployment, and management of containerized applications. The infrastructure consists of high memory servers and GPU enabled servers backed by CEPH storage.
The platform is designed for Big Data analytics and a typical suite of analytical tools such as Jupyter, R, Python, SAS and Slurm are available.
The infrastructure is located at the Stanford Research Computing Facility (SRCF). SRCF is a Stanford data center located on the SLAC campus, designed specifically to host high density, power-consumptive computing equipment.
Cost for using Nero On-Premise
On-premise Nero is currently fully subsidized to users.
Prerequisites to Getting Started
Please review the User Prerequisites here.
Primary Methods for Utilizing Nero Resources
| Method | Description |
|---|---|
| Jupyter Lab | JupyterLab is an interactive development environment for working with notebooks, code and data |
| Interactive Session w/ Slurm | Access Nero via Linux Login Node to configure scripts and environment. Then request compute resources via the Slurm Job Scheduler |
Base Storage Allocations
| Type | Size | Replication | Path |
|---|---|---|---|
| Home Directory | 10GB | yes | /home/$SUNETID |
| PI Directory | 1TB | yes | /share/pi/$PISUNETID |
PI Directories are best suited for storing data collaboratively with other members of your group. Each Nero user is part of a PI-Group. View your membership with “id $SUNETID” and look for “$PISUNET-pi” for this information.
Hardware Technical Specs
| Type | Qty | Details |
|---|---|---|
| Login nodes | 1 | |
| Compute nodes | 16 | Dual Core Intel Xeon Gold 6130 (16C 2.1GHz), 384 GB RAM |
| GPU nodes | 2 | Dual Core Intel Xeon Gold 6130 (16C 2.1GHz), 384 GB RAM + Dual P100 GPUs |
| GPU nodes | 6 | Dual Intel Xeon Silver 4114 (10C 2.2GHz), 256 GB RAM, Quad NVIDIA Tesla V100 |
| OS | Ubuntu 16.04 |