Snakemake executor plugin: lsf
LSF is common high performance computing batch system. This executor plugin allows to use it in a seamless and straightforward way.
Installation
Install this plugin by installing it with pip or mamba, e.g.:
pip install snakemake-executor-plugin-lsf
Usage
In order to use the plugin, run Snakemake (>=8.0) with the corresponding value for the executor flag:
snakemake --executor lsf ...
with ...
being any additional arguments you want to use.
Further details
Specifying Project and Queue
LSF clusters can have mandatory resource indicators for
accounting and scheduling, [Project]{.title-ref} and
[Queue]{.title-ref}, respectivily. These resources are usually
omitted from Snakemake workflows in order to keep the workflow
definition independent from the platform. However, it is also possible
to specify them inside of the workflow as resources in the rule
definition (see snakefiles-resources
{.interpreted-text role=”ref”}).
To specify them at the command line, define them as default resources:
$ snakemake --executor lsf --default-resources lsf_project=<your LSF project> lsf_queue=<your LSF queue>
If individual rules require e.g. a different queue, you can override the default per rule:
$ snakemake --executor lsf --default-resources lsf_project=<your LSF project> lsf_queue=<your LSF queue> --set-resources <somerule>:lsf_queue=<some other queue>
Usually, it is advisable to persist such settings via a configuration profile, which can be provided system-wide, per user, and in addition per workflow.
This is an example of the relevant profile settings:
jobs: '<max concurrent jobs>'
executor: lsf
default-resources:
- 'lsf_project=<your LSF project>'
- 'lsf_queue=<your LSF queue>'
Ordinary SMP jobs
Most jobs will be carried out by programs which are either single core
scripts or threaded programs, hence SMP (shared memory
programs) in nature. Any
given threads and mem_mb
requirements will be passed to LSF:
rule a:
input: ...
output: ...
threads: 8
resources:
mem_mb=14000
This will give jobs from this rule 14GB of memory and 8 CPU cores. It is advisable to use resonable default resources, such that you don't need to specify them for every rule. Snakemake already has reasonable defaults built in, which are automatically activated when using any non-local executor (hence also with lsf). Use mem_mb_per_cpu to give the standard LSF type memory per CPU
MPI jobs
Snakemake's LSF backend also supports MPI jobs, see
snakefiles-mpi
{.interpreted-text role=”ref”} for details.
rule calc_pi:
output:
"pi.calc",
log:
"logs/calc_pi.log",
threads: 40
resources:
tasks=10,
mpi='mpirun,
shell:
"{resources.mpi} -np {resources.tasks} calc-pi-mpi > {output} 2> {log}"
$ snakemake --set-resources calc_pi:mpi="mpiexec" ...
Advanced Resource Specifications
A workflow rule may support a number of resource specifications. For a LSF cluster, a mapping between Snakemake and LSF needs to be performed.
You can use the following specifications:
LSF |
Snakemake |
Description |
---|---|---|
|
|
the queue a rule/job is to use |
|
|
the walltime per job in minutes |
|
|
memory a cluster node must provide |
(mem: string with unit, mem_mb: i) |
||
|
|
memory per reserved CPU |
omit |
|
Allow splitting across nodes for MPI |
|
|
Processors per host. Reqires |
Other |
|
Other args to pass to |
Each of these can be part of a rule, e.g.:
rule:
input: ...
output: ...
resources:
partition: <partition name>
walltime: <some number>
walltime
and runtime
are synonyms.
Please note: as --mem
and --mem-per-cpu
are mutually exclusive,
their corresponding resource flags mem
/mem_mb
and
mem_mb_per_cpu
are mutually exclusive, too. You can only reserve
memory a compute node has to provide or the memory required per CPU
(LSF does not make any distintion between real CPU cores and those
provided by hyperthreads). The executor will convert the provided options
based on cluster config.
Additional custom job configuration
There are various bsub
options not directly supported via the resource
definitions shown above. You may use the lsf_extra
resource to specify
additional flags to bsub
:
rule myrule:
input: ...
output: ...
resources:
lsf_extra="-R a100 -gpu num=2"
Again, rather use a profile to specify such resources.
Clusters that use per-job memory requests instead of per-core
By default, this plugin converts the specified memory request into the per-core request expected by most LSF clusters.
So threads: 4
and mem_mb=128
will result in -R rusage[mem=32]
. If the request should be per-job on your cluster
(i.e. -R rusage[mem=<mem_mb>]
) then set the environment variable SNAKEMAKE_LSF_MEMFMT
to perjob
.
The executor automatically detects the request unit from cluster configuration, so if your cluster does not use MB, you do not need to do anything.