34 lines
1.2 KiB
Matlab
34 lines
1.2 KiB
Matlab
% Add the imdd_simulation framework to the path
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if ispc
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addpath(genpath('C:\Users\Silas\Documents\MATLAB\imdd_simulation'));
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else
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% Linux path on the cluster
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addpath(genpath('/work_beegfs/sutef391/imdd_simulation'));
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end
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% Quiet the ambiguous CET warning (best is to set TZ in sbatch; see below)
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warning('off','MATLAB:datetime:AmbiguousTimeZone');
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% How many workers?
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cpus = str2double(getenv('SLURM_CPUS_PER_TASK'));
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if ~isfinite(cpus) || cpus < 1, cpus = max(1, feature('numcores')); end
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% Use a per-job, node-local JobStorageLocation to avoid stale locks on $HOME
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% Prefer $TMPDIR if your cluster provides it, else tempdir().
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tmpbase = getenv('TMPDIR');
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if isempty(tmpbase), tmpbase = tempdir; end
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jsl = fullfile(tmpbase, sprintf('matlab_jobstorage_%s_%s', ...
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getenv('USER'), getenv('SLURM_JOB_ID')));
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if ~exist(jsl,'dir'); mkdir(jsl); end
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% Configure the local cluster explicitly and start the pool
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c = parcluster('local');
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c.NumWorkers = cpus;
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c.JobStorageLocation = jsl;
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p = gcp('nocreate');
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if isempty(p) || p.NumWorkers ~= cpus
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if ~isempty(p), delete(p); end
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p = parpool(c, cpus); % avoids the “queued” state
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end
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fprintf('parpool up with %d workers; JobStorage=%s\n', p.NumWorkers, c.JobStorageLocation); |