FarmShare 2

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FarmShare 2 is intended for use in coursework and unsponsored research; users participating in sponsored research should investigate the Sherlock service, instead. Like the legacy FarmShare environment, FarmShare 2 is not approved for use with high-risk data, and is subject to University policies on acceptable use.

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Cluster description

rice.stanford.edu

These are the login nodes for the new environment, which replace corn.stanford.edu. There are currently 14 systems in service; each has 8 cores and 48 GB of memory. Like corn systems they can be used for interactive work, but some resource limits are enforced to ensure multiple users can comfortably share a node:

  • 1 core and 8 GB of memory are reserved for the system
  • Each user is currently allowed:
- an equal share of CPU under load
- 12 GB of memory, some of which may be swap under memory pressure
- 128 GB of /tmp storage, with space regularly reclaimed from files older than 7 days
  • No single user may consume more than 75% of total CPU time under any conditions

Interactive sessions that require resources in excess of these limits, exclusive access to resources, or access to a feature not available on rice (e.g., a GPU), must be submitted to a compute node:

srun --pty --qos=interactive $SHELL -l
srun --pty --partition=gpu --gres=gpu:1 --qos=interactive $SHELL -l
srun --pty --partition=bigmem --mem=96G --qos=interactive $SHELL -l

These are the only systems with access to AFS in the new environment; see below.

wheat.stanford.edu

These are managed (compute) nodes similar to barley.stanford.edu in the old environment. There are currently 17 systems:

  • 5 nodes with 12 cores and 96 GB of memory
  • 2 large-memory nodes with 16 cores and 768 GB of memory
  • 10 nodes with 16 cores and 128 GB of memory

To submit to the large-memory nodes you need to run on the bigmem partition (see below), and request a minimum of 96 GB of memory:

srun --partition=bigmem --qos=bigmem --mem=96G
sbatch --partition=bigmem --qos=bigmem --mem=96G

oat.stanford.edu

These are GPU nodes similar to rye.stanford.edu in the old environment. There are currently 10 systems, each with 16 cores, 128 GB of memory, and one Tesla K40 GPU. Unlike the rye systems, these nodes are managed: you must submit a job to run on oat systems, and you must explicitly request access to a GPU when doing so:

srun --partition=gpu --qos=gpu --gres=gpu:1
sbatch --partition=gpu --qos=gpu --gres=gpu:1

Slurm

The new environment uses Slurm rather than Grid Engine for job management. If you have used Sherlock the system should be familiar to you. A package that provides limited compatibility with GE commands has been installed, but we encourage users to learn and use the native Slurm commands whenever possible.

Partitions and Qualities-of-Service

There are separate Slurm partitions for the standard compute nodes (normal), the large-memory nodes (bigmem), and the GPU nodes (gpu); there are corresponding Slurm qualities-of-service, as well as qualities-of-service for long-running (long) and interactive (interactive) jobs. Normal jobs have a maximum runtime of 2 days and long jobs a maximum of 7. Each user is currently allowed one interactive session with a maximum runtime of 1 day.

Be sure to request explicitly the resources you need when submitting a job.

Remote display

X11 forwarding is supported using the -X or -Y options for ssh. FarmVNC is no longer supported, but TurboVNC server is installed as a module, and we hope to have better support for VNC use-cases in the future.

AFS and scratch space

AFS is accessible on the rice systems only, and is not used for home directories. Instead, home directories are served from a dedicated file server, and per-user quota is currently 48 GB. A link to users’ AFS home directories, ~/afs-home, is provided as a convenience, for transferring data between the old and new environments, but locations in AFS should not be used as working directories for batch jobs. /farmshare/user_data is mounted everywhere, and can be used for additional (scratch) storage.

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