ClusterManagers.jl

The ClusterManagers.jl package implements code for different job queue systems commonly used on compute clusters.

Warning

This package is not currently being actively maintained or tested.

We are in the process of splitting this package up into multiple smaller packages, with a separate package for each job queue systems.

We are seeking maintainers for these new packages. If you are an active user of any of the job queue systems listed below and are interested in being a maintainer, please open a GitHub issue - say that you are interested in being a maintainer, and specify which job queue system you use.

Available job queue systems

In this package

The following managers are implemented in this package (the ClusterManagers.jl package):

Job queue system	Command to add processors
Local manager with CPU affinity setting	addprocs(LocalAffinityManager(;np=CPU_CORES, mode::AffinityMode=BALANCED, affinities=[]); kwargs...)

Implemented in external packages

Job queue system	External package	Command to add processors
Slurm	SlurmClusterManager.jl	addprocs(SlurmManager(); kwargs...)
Load Sharing Facility (LSF)	LSFClusterManager.jl	addprocs_lsf(np::Integer; bsub_flags=``, ssh_cmd=``) or addprocs(LSFManager(np, bsub_flags, ssh_cmd, retry_delays, throttle))
Kubernetes (K8s)	K8sClusterManagers.jl	addprocs(K8sClusterManager(np; kwargs...))
Azure scale-sets	AzManagers.jl	addprocs(vmtemplate, n; kwargs...)

Not currently being actively maintained

Warning

The following managers are not currently being actively maintained or tested.

We are seeking maintainers for the following managers. If you are an active user of any of the following job queue systems listed and are interested in being a maintainer, please open a GitHub issue - say that you are interested in being a maintainer, and specify which job queue system you use.

Job queue system	Command to add processors
Sun Grid Engine (SGE) via qsub	addprocs_sge(np::Integer; qsub_flags=``) or addprocs(SGEManager(np, qsub_flags))
Sun Grid Engine (SGE) via qrsh	addprocs_qrsh(np::Integer; qsub_flags=``) or addprocs(QRSHManager(np, qsub_flags))
PBS (Portable Batch System)	addprocs_pbs(np::Integer; qsub_flags=``) or addprocs(PBSManager(np, qsub_flags))
Scyld	addprocs_scyld(np::Integer) or addprocs(ScyldManager(np))
HTCondor	addprocs_htc(np::Integer) or addprocs(HTCManager(np))

Custom managers

You can also write your own custom cluster manager; see the instructions in the Julia manual.

Notes on specific managers

Slurm: please see SlurmClusterManager.jl

For Slurm, please see the SlurmClusterManager.jl package.

Using LocalAffinityManager (for pinning local workers to specific cores)

• Linux only feature.
• Requires the Linux taskset command to be installed.
• Usage : addprocs(LocalAffinityManager(;np=CPU_CORES, mode::AffinityMode=BALANCED, affinities=[]); kwargs...).

where

• np is the number of workers to be started.
• affinities, if specified, is a list of CPU IDs. As many workers as entries in affinities are launched. Each worker is pinned to the specified CPU ID.
• mode (used only when affinities is not specified, can be either COMPACT or BALANCED) - COMPACT results in the requested number of workers pinned to cores in increasing order, For example, worker1 => CPU0, worker2 => CPU1 and so on. BALANCED tries to spread the workers. Useful when we have multiple CPU sockets, with each socket having multiple cores. A BALANCED mode results in workers spread across CPU sockets. Default is BALANCED.

Using ElasticManager (dynamically adding workers to a cluster)

The ElasticManager is useful in scenarios where we want to dynamically add workers to a cluster. It achieves this by listening on a known port on the master. The launched workers connect to this port and publish their own host/port information for other workers to connect to.

On the master, you need to instantiate an instance of ElasticManager. The constructors defined are:

ElasticManager(;addr=IPv4("127.0.0.1"), port=9009, cookie=nothing, topology=:all_to_all, printing_kwargs=())
ElasticManager(port) = ElasticManager(;port=port)
ElasticManager(addr, port) = ElasticManager(;addr=addr, port=port)
ElasticManager(addr, port, cookie) = ElasticManager(;addr=addr, port=port, cookie=cookie)

You can set addr=:auto to automatically use the host's private IP address on the local network, which will allow other workers on this network to connect. You can also use port=0 to let the OS choose a random free port for you (some systems may not support this). Once created, printing the ElasticManager object prints the command which you can run on workers to connect them to the master, e.g.:

julia> em = ElasticManager(addr=:auto, port=0)
ElasticManager:
  Active workers : []
  Number of workers to be added  : 0
  Terminated workers : []
  Worker connect command :
    /home/user/bin/julia --project=/home/user/myproject/Project.toml -e 'using ClusterManagers; ClusterManagers.elastic_worker("4cOSyaYpgSl6BC0C","127.0.1.1",36275)'

By default, the printed command uses the absolute path to the current Julia executable and activates the same project as the current session. You can change either of these defaults by passing printing_kwargs=(absolute_exename=false, same_project=false)) to the first form of the ElasticManager constructor.

Once workers are connected, you can print the em object again to see them added to the list of active workers.

Sun Grid Engine (SGE)

See docs/sge.md