silas/imdd_silas
1
0
Fork 0
Code Issues Pull Requests Actions Packages Projects Releases Wiki Activity

work on MPI

Browse Source
This commit is contained in:
Silas Oettinghaus
2026-07-13 15:25:45 +02:00
parent a6cf742121
commit ef0a74cb7f
16 changed files with 2894 additions and 705 deletions
Download Patch File Download Diff File Expand all files Collapse all files

139
projects/Diss/MPI_revisit/investigate_mpi_algorithms.m
View File

@@ -3,8 +3,8 @@ dsp_options = struct();
dsp_options.mode = "run_id";
dsp_options.recipe = @mpi_recipe_dev;
dsp_options.append_to_db = false;
dsp_options.start_occurence = 2;
dsp_options.max_occurences = 1;
dsp_options.start_occurence = 1;
dsp_options.max_occurences = 15;
dsp_options.debug_plots = false;
dsp_options.database_type = "mysql";
@@ -23,95 +23,58 @@ db = DBHandler("dataBase", [dsp_options.dataBase],...
"user", dsp_options.user, "password", dsp_options.password);
%%
fp = QueryFilter();
fp.where('Runs','run_id','GREATER_EQUAL',3153);
fp.where('Runs', 'symbolrate', 'EQUALS', 112e9);
fp.where('Runs', 'fiber_length', 'EQUALS', 0);
fp.where('Runs', 'interference_path_length', 'EQUALS', 1000);
fp.where('Runs', 'sir', 'LESS_EQUAL', 20);
fp.where('Runs', 'db_mode', 'EQUALS', '"no_db"');
% fp.where('Runs', 'is_mpi', 'EQUALS', 1);
fp.where('Runs', 'pam_level', 'EQUALS', 4);
% fp.where('Runs', 'v_bias', 'EQUALS', 2.65);
[dataTable,~] = db.queryDB(fp, db.getTableFieldNames('Runs'));
pamformats = [4,6,8];
baudrates = [112e9,96e9,72e9];
% [~, uniqueSirRows] = unique(dataTable.sir, "stable");
% dataTable = dataTable(uniqueSirRows, :);
for i = 1:3
B = baudrates(i);
M = pamformats(i);
fp = QueryFilter();
fp.where('Runs','run_id','GREATER_EQUAL',3153);
fp.where('Runs', 'symbolrate', 'EQUALS', B); % 72 96 112
fp.where('Runs', 'fiber_length', 'EQUALS', 0);
fp.where('Runs', 'interference_path_length', 'EQUALS', 1000);
fp.where('Runs', 'sir', 'LESS_EQUAL', 20);
fp.where('Runs', 'db_mode', 'EQUALS', '"no_db"');
% fp.where('Runs', 'is_mpi', 'EQUALS', 1);
fp.where('Runs', 'pam_level', 'EQUALS', M);
% fp.where('Runs', 'v_bias', 'EQUALS', 2.65);
[dataTable,~] = db.queryDB(fp, db.getTableFieldNames('Runs'));
[~, sortIdx] = sort(dataTable.sir, 'descend');
dataTable = dataTable(sortIdx, :);
run_ids = dataTable.run_id;
%% === Warehouse setup ===
dsp_options.userParameters = struct();
dsp_options.userParameters.block_update = 1;%[1,2,4,8,16,32,64,112,224,448,512,1024,2048,2048*2,2048*4];%%logspace(-3.8,-1,22);%[linspace(2,4096,22)];
wh = DataStorage(dsp_options.userParameters);
%%
n_realizations = (dsp_options.max_occurences - dsp_options.start_occurence + 1);
n_userparams = prod(wh.dim);
n_run_ids = numel(run_ids);
parallel_jobs = n_userparams * n_run_ids;
queried_jobs = n_realizations * n_userparams * n_run_ids;
fprintf("-> [ %d run_id(s) × %d userParam combination(s) = %d parallel job(s) ] × %d realizations = %d total jobs \n", ...
n_run_ids, n_userparams, parallel_jobs, n_realizations, queried_jobs);
%% === Run ===
% submitJobs returns the raw per-job results and the filled Warehouse. For a
% single run_id and remove_dc = [0, 1], results is a 2-by-1 cell array.
[results, wh] = submitJobs(run_ids, dsp_options, processingMode.serial, ...
"wh", wh, ...
"waitbar", true);
% savepath = fullfile("C:","Users","Silas","Documents","MATLAB","imdd_simulation","projects","Diss","MPI_revisit","algorithms",sprintf("pam_%d_results.mat",M));
% save(wh,savepath)
[~, sortIdx] = sort(dataTable.sir, 'descend');
dataTable = dataTable(sortIdx, :);
dataTable = dataTable(1, :);
run_ids = dataTable.run_id;
if isempty(run_ids)
error("run_minimal_recipe:MissingRunIds", ...
"Set run_ids to one or more known run IDs before running this example.");
end
%% === Warehouse setup ===
dsp_options.userParameters = struct();
% dsp_options.userParameters.smoothing_length = [0,linspace(100,1000,10),2500,5000,10000];
wh = DataStorage(dsp_options.userParameters);
%%
n_realizations = (dsp_options.max_occurences - dsp_options.start_occurence + 1);
n_userparams = prod(wh.dim);
n_run_ids = numel(run_ids);
parallel_jobs = n_userparams * n_run_ids;
queried_jobs = n_realizations * n_userparams * n_run_ids;
fprintf("-> [ %d run_id(s) × %d userParam combination(s) = %d parallel job(s) ] × %d realizations = %d total jobs \n", ...
n_run_ids, n_userparams, parallel_jobs, n_realizations, queried_jobs);
%% === Run ===
% submitJobs returns the raw per-job results and the filled Warehouse. For a
% single run_id and remove_dc = [0, 1], results is a 2-by-1 cell array.
[results, wh] = submitJobs(run_ids, dsp_options, processingMode.serial, ...
"wh", wh, ...
"waitbar", true);
%% Analyze
storageNames = fieldnames(wh.sto);
result = wh.sto.(storageNames{1});
result = result(:).';
% Each stored entry is a package cell containing one or more occurrences.
ber_all = cell(1,numel(result));
for result_idx = 1:numel(result)
packageCell = result{result_idx};
if isempty(packageCell)
ber_all{result_idx} = NaN;
continue
end
ber_values = nan(1,numel(packageCell));
for package_idx = 1:numel(packageCell)
if isstruct(packageCell{package_idx}) && isfield(packageCell{package_idx},"metrics")
ber_values(package_idx) = packageCell{package_idx}.metrics.BER;
end
end
ber_all{result_idx} = ber_values;
end
maxPackages = max(cellfun(@numel,ber_all));
ber_mat = nan(maxPackages,numel(ber_all));
for k = 1:numel(ber_all)
ber_mat(1:numel(ber_all{k}),k) = ber_all{k};
end
ber = mean(ber_mat,1,"omitnan");
x = dataTable.sir(:).';
if numel(x) ~= numel(ber)
x = 1:numel(ber);
end
figure(2026); clf; hold on
plot(x,ber);
for k = 1:numel(x)
scatter(repmat(x(k),maxPackages,1),ber_mat(:,k))
end
beautifyBERplot("logscale",true,"setcolors",false,"setmarkers",true);