maxconfig
maxconfig is available on all clusters and will display the recommended Slurm #SBATCH parameters for the maximum resource configuration (cores, memory, time) for specific partitions or accelerators.
Use the following command to see usage and SU charge rate per GPU
maxconfig -h
You can see the SUs that will be charged for your job script without submitting the job by using the -f option
maxconfig -f my_job_file.slurm
- The values in the following examples vary between clusters.
- Run maxconfig on the command line of the cluster you are using to see the maximum resources as well as the current GPU configuration and SU rates.
- Use the current maxconfig output on each cluster instead of copying from the webpage.
Usage
maxconfig -h
maxconfig will print maximum CPU cores, available memory and walltime for the cluster compute nodes in #SBATCH format.
The SUs calculations will also be displayed for clusters where SU charging is enabled.
You can select a specific partition using -p partition_name
Example Usage:
# select 1 x t4 GPU for 1 day (selecting 1 of 2 installed GPUs will scale available CPU cores and memory by 1/2)
maxconfig -g t4 -G 1 -d 1
Options:
-p partition show a specific partition (cpu, gpu, atsp)
-g gpu show parameters for a specific GPU (a10 a100 a30 a40 t4 (default for -p gpu: t4))
-G int number of GPUs; must also specify GPU type with -g;
Note: when using -G, selecting fewer GPUs than are on a node will scale down CPUs and memory so the other GPUs are available to other jobs
-1 show minimum CPU and memory parameters for 1 SU per hour rate (values for -c, -m, -g, -G, -d and -h will be ignored)
-e email add #SBATCH lines to receive email notifications about your job
-f filename estimate SUs for a job script file (ignores all other options)
-d int runtime days
-h int runtime hours
-n int nodes (default: 1)
-t int tasks per node (default: 1)
-c int cpus per task (default: 64)
-m int total memory in GB per node (default: 240)
-s output srun line for interactive jobs instead of #SBATCH parameters
-h show help
SU rate per GPU:
GPU SUs per hour
---- ------------
a10 128
a100 128
a30 128
a40 128
t4 64
Example output
default
maxconfig
partitions: cpu gpu atsp
GPUs in gpu partition: a100:16 a100:4 a100:8 a10:2 a10:4 a30:2 a40:2 a40:4 t4:2 t4:4 t4:8
Showing max parameters (cores, mem, time) for partition cpu
CPU-billing * hours * nodes = SUs
64 * 168 * 1 = 10,752
#!/bin/bash
#SBATCH --job-name=my_job
#SBATCH --time=7-00:00:00
#SBATCH --nodes=1
#SBATCH --ntasks-per-node=1
#SBATCH --cpus-per-task=64
#SBATCH --mem=240G
#SBATCH --output=stdout.%x.%j
#SBATCH --error=stderr.%x.%j
gpu
select 1 x t4 GPU for 1 day
maxconfig -g t4 -G 1 -d 1
partitions: cpu gpu atsp
GPUs in gpu partition: a100:16 a100:4 a100:8 a10:2 a10:4 a30:2 a40:2 a40:4 t4:2 t4:4 t4:8
Showing 1/8 of total cores and memory for using 1 x t4 GPU
(CPU-billing + (GPU-billing * GPU-count)) * hours * nodes = SUs
( 9 + ( 64 * 1)) * 24 * 1 = 1,752
#!/bin/bash
#SBATCH --job-name=my_job
#SBATCH --time=1-00:00:00
#SBATCH --nodes=1
#SBATCH --ntasks-per-node=1
#SBATCH --cpus-per-task=8
#SBATCH --mem=30G
#SBATCH --partition=gpu
#SBATCH --gres=gpu:t4:1
#SBATCH --output=stdout.%x.%j
#SBATCH --error=stderr.%x.%j