Covalent Slurm Plugin
Project description
Covalent Slurm Plugin
Covalent is a Pythonic workflow tool used to execute tasks on advanced computing hardware. This executor plugin interfaces Covalent with HPC systems managed by Slurm. For workflows to be deployable, users must have SSH access to the Slurm login node, writable storage space on the remote filesystem, and permissions to submit jobs to Slurm.
Installation
To use this plugin with Covalent, simply install it using pip
:
pip install covalent-slurm-plugin
On the remote system, the Python version in the environment you plan to use must match that used when dispatching the calculations. Additionally, the remote system's Python environment must have the base covalent package installed (e.g. pip install covalent
).
Usage
The following shows an example of a Covalent configuration that is modified to support Slurm:
[executors.slurm]
username = "user"
address = "login.cluster.org"
ssh_key_file = "/home/user/.ssh/id_rsa"
remote_workdir = "/scratch/user"
cache_dir = "/tmp/covalent"
[executors.slurm.options]
nodes = 1
ntasks = 4
cpus-per-task = 8
constraint = "gpu"
gpus = 4
qos = "regular"
[executors.slurm.srun_options]
cpu_bind = "cores"
gpus = 4
gpu-bind = "single:1"
The first stanza describes default connection parameters for a user who can connect to the Slurm login node using, for example:
ssh -i /home/user/.ssh/id_rsa user@login.cluster.org
The second and third stanzas describe default parameters for #SBATCH
directives and default parameters passed directly to srun
, respectively.
This example generates a script containing the following preamble:
#!/bin/bash
#SBATCH --nodes=1
#SBATCH --ntasks=4
#SBATCH --cpus-per-task=8
#SBATCH --constraint=gpu
#SBATCH --gpus=4
#SBATCH --qos=regular
and subsequent workflow submission with:
srun --cpu_bind=cores --gpus=4 --gpu-bind=single:1
To use the configuration settings, an electron’s executor must be specified with a string argument, in this case:
import covalent as ct
@ct.electron(executor="slurm")
def my_task(x, y):
return x + y
Alternatively, passing a SlurmExecutor
instance enables custom behavior scoped to specific tasks. Here, the executor's prerun_commands
and postrun_commands
parameters can be used to list shell commands to be executed before and after submitting the workflow. These may include any additional srun
commands apart from workflow submission. Commands can also be nested inside the submission call to srun
by using the srun_append
parameter.
More complex jobs can be crafted by using these optional parameters. For example, the instance below runs a job that accesses CPU and GPU resources on a single node, while profiling GPU usage via nsys
and issuing complementary commands that pause/resume the central hardware counter.
executor = ct.executor.SlurmExecutor(
remote_workdir="/scratch/user/experiment1",
options={
"qos": "regular",
"time": "01:30:00",
"nodes": 1,
"constraint": "gpu",
},
prerun_commands=[
"module load package/1.2.3",
"srun --ntasks-per-node 1 dcgmi profile --pause"
],
srun_options={
"n": 4,
"c": 8,
"cpu-bind": "cores",
"G": 4,
"gpu-bind": "single:1"
},
srun_append="nsys profile --stats=true -t cuda --gpu-metrics-device=all",
postrun_commands=[
"srun --ntasks-per-node 1 dcgmi profile --resume",
]
)
@ct.electron(executor=executor)
def my_custom_task(x, y):
return x + y
Here the corresponding submit script contains the following commands:
module load package/1.2.3
srun --ntasks-per-node 1 dcgmi profile --pause
srun -n 4 -c 8 --cpu-bind=cores -G 4 --gpu-bind=single:1 \
nsys profile --stats=true -t cuda --gpu-metrics-device=all \
python /scratch/user/experiment1/workflow_script.py
srun --ntasks-per-node 1 dcgmi profile --resume
Release Notes
Release notes are available in the Changelog.
Citation
Please use the following citation in any publications:
W. J. Cunningham, S. K. Radha, F. Hasan, J. Kanem, S. W. Neagle, and S. Sanand. Covalent. Zenodo, 2022. https://doi.org/10.5281/zenodo.5903364
License
Covalent is licensed under the Apache License 2.0. See the LICENSE file or contact the support team for more details.
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