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Handbook / policy

policy

IDEAL Lab Euler Share Policy

Field Value
Owner IDEAL Lab IT administrator
Lab policy confirmed 2026-09-21
Student subgroup limits verified 2026-09-21
Other external/system facts verified 2026-08-04
Review by 2026-12-21

This page distinguishes IDEAL Lab policy from ETH-wide Euler behavior.

ETH-Wide Facts#

  • Euler is shared and schedules non-exclusive jobs on compute nodes.
  • The public share allows small CPU jobs, currently up to 48 CPU cores and 128 GiB RAM. It contains no GPUs and may have long waits.
  • GPU nodes are available only through shareholder accounts.
  • A shareholder entitlement is an average fair share, not exclusive ownership of named physical nodes.
  • Users should request resources accurately and normally avoid specifying a partition or hardware model unless the workload depends on it.

Student gate: no bulk jobs or --partition=bulk; use the normal student procedures. Configured ceilings are not a suggested first request or a promise of idle hardware.

Observed es_fuge Entitlement (2026-08-04)#

A read-only my_share_info check on 2026-08-04 reported:

  • 784 CPU cores;
  • 3136 GiB system RAM;
  • 18 GPUs.

The 2026-08-04 allocation observation includes two Nvidia RTX PRO 6000 GPUs. RTX 4090 remains the standard student GPU; the RTX PRO 6000 is a special-purpose 96-GiB, CUDA 13-compatible option requested with Slurm identifier pro_6000.

These dated numbers describe the observed shareholder entitlement, not resources that are always idle or exclusively reserved for IDEAL Lab users. Recheck with my_share_info before publishing or relying on these totals.

IDEAL Lab Student Policy#

This subsection is local lab policy for supervised BSc/MSc use of es_fuge:

  • Scheduler priority factor: 0.2 relative to regular staff within the lab share.
  • Per student: no per-student cap is currently configured.
  • Student group general pool collectively: at most 46 GPUs, 1920 CPU cores, and 7144 GiB system RAM.
  • Student group professional-GPU pool collectively: at most 1 professional GPU, 16 CPU cores, and 96 GiB system RAM.

These are separate category limits; do not add them together into a recommended job size. They are scheduling ceilings, not reserved capacity or recommended requests. RAM here means system RAM, not GPU VRAM; GPU jobs consume CPU cores and system RAM as well as GPU capacity. Although the lab entitlement includes two RTX PRO 6000 GPUs, the student subgroup can collectively use at most one professional GPU at a time. Most first jobs should use one CPU, modest memory, no GPU, and a short time limit.

Student Bulk-Job Restriction#

Students must not submit bulk jobs or use --partition=bulk. Euler support's current implementation does not yet apply the IDEAL student-subgroup controls correctly to bulk jobs. Use the normal student submission procedures instead. Do not switch accounts or partitions to bypass this restriction.

A five-minute administrative guard cancels bulk jobs submitted by effective members of mavt-ide-euler-students on es_fuge. If a cancellation appears incorrect, contact Soheyl with the job ID. The guard leaves a job untouched if its account, partition, state, or effective group membership cannot be verified unambiguously.

This restriction remains in force until Euler support clears student use and the lab IT administrator updates this policy. General statements about bulk accounting for regular staff jobs do not authorize student use.

Required Behavior#

  • Use --account=es_fuge for GPU jobs and supervised lab-share work.
  • Use --account=public only for CPU work that fits public-share limits.
  • Never add --gpus to a public job.
  • Prefer sbatch for training, sweeps, and unattended computation.
  • Keep euler-tunnel allocations short and stop them when interactive work ends.
  • Start arrays with a low explicit concurrency cap and count concurrency across every active array and ordinary job, not only within the newest array.
  • Inspect completed jobs with sacct and seff; use the evidence to right-size the next request.
  • Start with one GPU. Request multiple GPUs only after measuring useful scaling.

Exceptions#

A project blocked by the collective student limits must obtain supervisor approval before requesting a change or temporary exception. The supervisor and lab IT administrator should record its scope, reason, owner, and end date.

Sources#