I’m going to show you how you can use existing functionality to run a Mathematica script across a managed HPC cluster. Before I start, I must be upfront with you: though the individual commands are documented, this method, as a whole, is not. Thus, support for this procedure is outside the scope of Wolfram Technical Support. However, I’m hoping that once the ground-work has been laid, that Wolfram Community members can work together to fill in the missing details.
My assumptions:
- Mathematica is installed and properly licensed on the managed cluster
- once your job has been given resources, that you can freely SSH between them
(1) This is up to your local cluster’s System Admin to figure out by talking with their organization and a Wolfram Sales Representative, and possibly Wolfram Technical Support (support.wolfram.com).
(2) Again, this is up to your local SysAdmin to ensure. It’s also known as a public/private key pair between nodes.
In the following, I’m assuming the cluster uses Torque (Torque SysAdmin Guide), but in principle other managers can be used. A generic Mathematica script job submission may look like the following:
#PBS -N Job_name
#PBS -l walltime=10:30
#PBS -l nodes=4:ppn=6
#PBS -m be
math -script hpc.wl
In this example,
- the job is called “Job_name”
- the job will finish in 10 and a half minutes
- it is requesting 4 nodes with 6 processors-per-node, for a total of 24 resources (CPU cores)
- an email will be sent to the account associated with the username when the job (b)egins and when it (e)nds
If you are not familiar with job submissions to a managed HPC cluster, then I suggest you read any guides provided by your organization
The Wolfram Language script “hpc.wl” does the rest of the work. It generically follows this order:
-
gather the environment variables associated with the list of provided resources
-
launch remote subkernels for each CPU core
-
do the parallel computations
-
close the subkernels
-
end the job
(*get association of resources, name of local host, and remove local host from available resources*) hosts = Counts[ReadList[Environment["PBS_NODEFILE"], "String"]]; local = First[StringSplit[Environment["HOSTNAME"],"."]]; hosts[local]--; (*launch subkernels and connect them to the controlling Wolfram Kernel*) Needs["SubKernels`RemoteKernels`"]; Map[If[hosts[#] > 0, LaunchKernels[RemoteMachine[#, hosts[#]]]]&, Keys[hosts]]; (* ===== regular Wolfram Language code goes here ===== *) Print[ {$MachineName, $KernelID} ] (* ===== end of Wolfram Language program ===== *) CloseKernels[]; Quit
On Torque there is the environment variable “PBS_NODEFILE” (Torque environment variables) that lists the different nodes that are provided to the job. It is my understanding that the name is repeated for each CPU core. That’s why a simple Count of the node list tells us everything. The other piece of information, which is probably not necessary, is “HOSTNAME”. This is where the Wolfram controlling kernel is running. In the above, we remove it from the list of available resources, but I don’t believe this is necessary. According to the documentation (3), this may be known as “PBS_O_HOSTNAME”.
The Mathematica script should not need to change save for the code between the commented lines. I’m also assuming that $RemoteCommand (provided by Subkernels`RemoteKernels`) is the same on each node. This is usually the case as most clusters use a cloned file system.
SLURM should be very similar except that the environment variables will be different. It is my understanding that
headNode = Environment["SLURMD_NODENAME"];
nodes = ReadList["!scontrol show hostname $SLURM_NODELIST",String];
provides the headnode and list of resources.
I encourage discussion.
