Increase GPU Throughput During training

Prashant Kumar answered . 2024-12-21 00:34:01

I used my own binary file reader based on looking at the built in png reader functions and my code above. It is a huge speedup, and now I am able to eliminate the ReadFcn but still have my custom reader. The only issue I didn't solve was how to pass the dims variable into the reader instead of hard coding it.

 function net = run_training_public(nbatch, lr, nepoch)
    % Add custom image type to imread registry
    create_custom_image_format()
    % Load Data
    ds = imageDatastore('./data/set3','IncludeSubfolders',true,...
                        'LabelSource','foldernames',...
                        'FileExtensions','.dat');
    % load neural network structure
    network = cnn1;
    % Setup options for training and execute training
    options = trainingOptions('adam','MaxEpochs',nepoch,'MiniBatchSize',...
                               nbatch,'Shuffle','every-epoch',...
                              'InitialLearnRate',lr,...
                              'ExecutionEnvironment','gpu','Verbose',true);
    net = trainNetwork(ds,network,options);
 end

 function create_custom_image_format()
    fmts = imformats; % don't add if already in registry
    if ~any(contains([fmts.ext],'dat'))
        out.ext = 'dat';
        out.isa = @isdat;
        out.info = [];
        out.read = @custom_image_reader;
        out.write = [];
        out.alpha = 0;
        out.description = 'Custom Data Format';
        imformats('add',out);
    end
 end

 function tf = isdat(filename)
    % Returns true if file is type .dat
    [~,~,extn] = fileparts(filename);
    tf = strcmp(extn,'.dat');
 end

 function [X, map] = custom_image_reader(filename)
    dims = [$m $n]; % <-HARD CODE DIMENSIONS OF DATA HERE
    f=fopen(filename,'r');
    X = reshape(fread(f,'*int16'),dims(2), dims(1)).';
    fclose(f);
    map = [];
 end

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