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caubet_m 2021-01-29 13:12:34 +01:00
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pages/merlin6/03 Job Submission/slurm-configuration.md
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@ -156,7 +156,7 @@ The limits are described below.
#### Per job limits #### Per job limits
These are limits applying to a single job. In other words, there is a maximum of resources a single job can use. These are limits applying to a single job. In other words, there is a maximum of resources a single job can use.
Limits are defined using QoS, and this is usually set at the partition level. Limits are described in the table below and are showed in format: `SlurmQoS(limits)`, Limits are defined using QoS, and this is usually set at the partition level. Limits are described in the table below with the format: `SlurmQoS(limits)`,
(list of possible `SlurmQoS` values can be listed with the command `sacctmgr show qos`): (list of possible `SlurmQoS` values can be listed with the command `sacctmgr show qos`):
| Partition | Mon-Sun 0h-24h | | Partition | Mon-Sun 0h-24h |
@ -165,13 +165,13 @@ Limits are defined using QoS, and this is usually set at the partition level. Li
| **gpu-short** | gpu_week(cpu=40,gres/gpu=8,mem=200G) | | **gpu-short** | gpu_week(cpu=40,gres/gpu=8,mem=200G) |
With these limits, a single job can not use more than 40 CPUs, more than 8 GPUs or more than 200GB. With these limits, a single job can not use more than 40 CPUs, more than 8 GPUs or more than 200GB.
Any job exceeding such limits will stay in the queue with error **`QOSMax[Cpu|GRES|Mem]PerJob`**. Any job exceeding such limits will stay in the queue with the message **`QOSMax[Cpu|GRES|Mem]PerJob`**.
Since there are no more QoS during the week which can increase job limits (this happens for instance in the CPU **daily** partition), the job needs to be cancelled and requested resources must be adapted according to the above resource limits. Since there are no more existing QoS during the week temporary overriding job limits (this happens for instance in the CPU **daily** partition), the job needs to be cancelled, and the requested resources must be adapted according to the above resource limits.
#### Per user limits for CPU partitions #### Per user limits for CPU partitions
These limits apply exclusively to users. In other words, there is a maximum of resources a single user can use. These limits apply exclusively to users. In other words, there is a maximum of resources a single user can use.
Limits are defined using QoS, and this is usually set at the partition level. Limits are described in the table below and are showed in format: `SlurmQoS(limits)`, Limits are defined using QoS, and this is usually set at the partition level. Limits are described in the table below with the format: `SlurmQoS(limits)`,
(list of possible `SlurmQoS` values can be listed with the command `sacctmgr show qos`): (list of possible `SlurmQoS` values can be listed with the command `sacctmgr show qos`):
| Partition | Mon-Sun 0h-24h | | Partition | Mon-Sun 0h-24h |
@ -180,7 +180,7 @@ Limits are defined using QoS, and this is usually set at the partition level. Li
| **gpu-short** | gpu_week(cpu=80,gres/gpu=16,mem=400G) | | **gpu-short** | gpu_week(cpu=80,gres/gpu=16,mem=400G) |
With these limits, a single user can not use more than 80 CPUs, more than 16 GPUs or more than 400GB. With these limits, a single user can not use more than 80 CPUs, more than 16 GPUs or more than 400GB.
Jobs sent by any user already exceeding such limits will stay in the queue with error **`QOSMax[Cpu|GRES|Mem]PerUser`**. In that case, job can wait until some of the running resources by this user are freed. Jobs sent by any user already exceeding such limits will stay in the queue with the message **`QOSMax[Cpu|GRES|Mem]PerUser`**. In that case, job can wait in the queue until some of the running resources are freed.
Notice that user limits are wider than job limits. In that way, a user can run up to two 8 GPUs based jobs, or up to four 4 GPUs based jobs, etc. Notice that user limits are wider than job limits. In that way, a user can run up to two 8 GPUs based jobs, or up to four 4 GPUs based jobs, etc.
Please try to avoid occupying all GPUs of the same type for several hours or multiple days, otherwise it would block other users needing the same Please try to avoid occupying all GPUs of the same type for several hours or multiple days, otherwise it would block other users needing the same