OFFarmLab/simOfflow.m at restructure · Hugo-build/OFFarmLab · GitHub

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clc
clear
close all
set(0,"defaultfigurecolor","w")

% Initialize offarmLab MATLAB paths
if ~exist('core/offarmLab', 'dir')
    error('core/offarmLab directory not found');
elseif ~exist('initOffarmLab', 'file')
    error('initOffarmLab function not found');
else
    addpath("core/offarmLab");
    initOffarmLab(nargout=0);
end


%% Run single case
addpath("usr0")
file_inp = 'usr0/INPUT_manifest.json';

resultsPre                = struct();
resultsPre.nCase          = 2;
resultsPre.batchCasesID   = 1;
resultsPre.caseMatrix     = [5, 11, 0.5, 0, 0];
resultsPre.infoList       = "Hs=5;Tp=11;Uc1=0.5;waveDir=0;currentDir=0";
resultsPre.savingDir      = 'results';

diary_filename = [ 'diary_'  '.txt'];
diary(diary_filename);
simOffarm(file_inp, resultsPre);
diary off


%% Set up multiple cases
resultsPre                = struct();
resultsPre.nCase          = 2;
resultsPre.batchCasesID   = 2;
resultsPre.caseMatrix     = [5, 10, 0.5, 0, 0;
                             5, 10, 0.5, 0, 90];
resultsPre.infoList       = {"Hs=5;Tp=11;Uc1=0.5;waveDir=0;currentDir=0";...
                             "Hs=5;Tp=11;Uc1=0.5;waveDir=0;currentDir=90"};

resultsPre.savingDir      = 'results';

diary_filename = [ 'diary_'  '.txt'];
diary(diary_filename);
simOffarm(file_inp, resultsPre);
diary off


%% SETTING parallel

%  ---- Create a cluster object -----------------------------------------
cluster = parcluster();

% Get the number of workers available in the cluster
numWorkers = cluster.NumWorkers;

% Display the number of workers
disp(['Number of workers available: ', num2str(numWorkers)]);


% ---- Arribute clusters and threads ------------------------------------

% Define the number of parallel workers
numWorkers = 4;

% Create a cluster object
cluster = parcluster();

% Set the number of workers for the cluster
cluster.NumWorkers = numWorkers;


% ---- Arribute Jobs and Groups of batch --------------------------------

% Determine jobs
numCases = resultsPre.nCase;
casePerJob = 100;
numJobs = ceil(numCases/casePerJob);
IdxCase2Run = cell(numJobs,1);
for iJob = 1: numJobs
    IdxCase2Run{iJob,1} = (iJob-1)*casePerJob +1:(min(iJob*casePerJob,numCases));
end

% Determine groups
groupSize = cluster.NumWorkers;
numGroups = ceil(numJobs/groupSize);


%% RUNNING parallel

for iGroup = 1:numGroups
    startIdx = (iGroup-1) * groupSize + 1;
    endIdx   = min(iGroup * groupSize, numJobs);

    % Submit the current group of jobs
    jobs = cell(1, groupSize);
    for j = startIdx:endIdx
        resultsPre.batchCasesID = IdxCase2Run{j,1};
        jobIdx = j - startIdx + 1;
        jobs{jobIdx} = batch(cluster, @simOffarm, 0, {file_inp, resultsPre, jobIdx});
        disp([num2str(jobIdx) ' job is distributed; ' num2str(numel(IdxCase2Run{j,1})) ' cases are under iteration'])
        pause(3.)

    end
     disp(['The ' num2str(iGroup) '/' num2str(numGroups) 'th Group is created'])
    % Wait for the current group of jobs to complete
    for j = startIdx:endIdx
        jobIdx = j - startIdx + 1;
        wait(jobs{jobIdx});
    end

    % Optionally, clear completed jobs to free up memory
    clear jobs;
    disp(['The ' num2str(iGroup) '/' num2str(numGroups) 'th Group is accomplished'])

end