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Currently support exists for :

• Sun Grid Engine - via addprocs_sge(np::Integer, queue="") or addprocs(SGEManager(np, queue)) and addprocs_pbs(np::Integer, queue="") or addprocs(PBSManager(np, queue))

• Scyld - addprocs_scyld(np::Integer) or addprocs(ScyldManager(np))

• HTCondor - addprocs_htc(np::Integer) or addprocs(HTCManager(np))

• Slurm - addprocs_slurm(np::Integer; kwargs...) or addprocs(SlurmManager(np); kwargs...)

• Local manager with CPU affinity setting - addprocs(LocalAffinityManager(;np=CPU_CORES, mode::AffinityMode=BALANCED, affinities=[]); kwargs...)

See section http://docs.julialang.org/en/latest/manual/parallel-computing/#clustermanagers

using ClusterManagers

# Arguments to the Slurm srun(1) command can be given as keyword
# arguments to addprocs.  The argument name and value is translated to
# a srun(1) command line argument as follows:
# 1) If the length of the argument is 1 => "-arg value",
#    e.g. t="0:1:0" => "-t 0:1:0"
# 2) If the length of the argument is > 1 => "--arg=value"
#    e.g. time="0:1:0" => "--time=0:1:0"
# 3) If the value is the empty string, it becomes a flag value,
#    e.g. exclusive="" => "--exclusive"
# 4) If the argument contains "_", they are replaced with "-",
#    e.g. mem_per_cpu=100 => "--mem-per-cpu=100"
addprocs(SlurmManager(2), partition="debug", t="00:5:00")

hosts = []
pids = []
for i in workers()
	host, pid = fetch(@spawnat i (gethostname(), getpid()))
	push!(hosts, host)
	push!(pids, pid)
end

# The Slurm resource allocation is released when all the workers have
# exited
for i in workers()
	rmprocs(i)
end

• 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