Carina Resources

Overview

The Carina platform offers access to Stanford-managed compute resources for research projects using high-risk data.

The platform is designed for interactive data analytics and offers access to Stanford-managed high-memory servers and GPU-enabled servers.

Disaster recovery and long-term access to data are provided via a combination of on-premise and cloud archive solutions.

A typical suite of analytics tools such as Jupyter, R, Python, and SAS are available.

All available servers can also run traditional jobs through the Slurm scheduler.

Collaboration with other researchers within Stanford is controlled via Stanford workgroups.

The On-Premise vs. Cloud page has some more detailed information about the differences between the Carina On-Prem and Nero GCP environments.

Hardware Technical Specifications


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 Available to everyone
GPU nodes	6	Dual Core Intel Xeon Silver 4114 (10C 2.2GHz), 256 GB RAM, Quad NVIDIA Tesla V100 Available to everyone
GPU nodes	6	Dual Core Intel Xeon Gold 6330 (28C 2GHz), 512 GB RAM, Quad NVIDIA A100 (40GB) Dedicated GPUs, not available to everyone
OS		Ubuntu 20.04
Total Cores	1,032	across 3 CPU models
Total GPUs	52	across 3 GPU models
Ethernet Switches	9
Storage	4.5PB	research data storage

Requesting a Carina On-Premise Project

1. Take a look at the Carina versus Nero GCP cheat sheet to identify whether you need an on-premise solution, a cloud solution or both.

2. Request a Carina On-Premise project using this ServiceNow Carina On-Prem form. Carina On-Prem projects are exclusively designed for projects using high-risk data. Per Stanford University's guidance, a Data Risk Assessment may be required as part of your work with high-risk data. Find out more here.

3. Wait for an email notification confirming your Carina resources are ready.

Request Carina On-Premise