Multiple GPU slower than single GPU or even CPU

I have an image processing code that uses multiple GPU, however, the multi-gpu process is slower than single GPU and even CPU. Moreover, the single GPU and the CPU processing time is about the same. Does anyone know what's wrong?

clc
clear all 
close all 
ImageFolder = uigetdir('D:\', 'Select Image Directory');
[parentFolder, thisFolder] = fileparts(ImageFolder);
fileListing = dir(parentFolder);
fileListing(ismember( {fileListing.name}, {'.', '..'})) = []; 
areAFolder = [fileListing.isdir];
folderListing = fileListing(areAFolder); 
    RawImage = [dir([ImageFolder '/*.tif']);dir([ImageFolder '/*.tiff']);...
                      dir([ImageFolder '/*.png']); dir([ImageFolder '/*.jpg']);...
                      dir([ImageFolder '/*.dcm']); dir([ImageFolder '/*.fits']);...
                      dir([ImageFolder '/*.fts']); dir([ImageFolder '/*.img']);...
                      dir([ImageFolder '/*.raw']); dir([ImageFolder '/*.his']);...
                      dir([ImageFolder '/*.hdr']); dir([ImageFolder '/*.nitf'])]; 
    RawFileNames= {RawImage(:,1).name}'; 
    RawFilenames = fullfile(ImageFolder, RawFileNames);
    RawImageData = cellfun(@ReadInputImage, RawFilenames , 'uniformoutput', 0);
    
 for k = 1 : length(folderListing)
	thisFolder = fullfile(folderListing(k).folder, folderListing(k).name); 
    [~, theFolder] = fileparts(thisFolder);
    if matches(theFolder, ["Bright","bright","gain","Gain"])    
        BrightImage=  [dir([thisFolder '/*.tif']);dir([thisFolder '/*.tiff']);...
                      dir([thisFolder '/*.png']); dir([thisFolder '/*.jpg']);...
                      dir([thisFolder '/*.dcm']); dir([thisFolder '/*.fits']);...
                      dir([thisFolder '/*.fts']); dir([thisFolder '/*.img']);...
                      dir([thisFolder '/*.raw']); dir([thisFolder '/*.his']);...
                      dir([thisFolder '/*.hdr']); dir([thisFolder '/*.nitf'])];
        BrightFileNames= {BrightImage(:,1).name}'; 
        BrightFilenames = fullfile(thisFolder, BrightFileNames);
        BrightImageData = cellfun(@ReadInputImage, BrightFilenames , 'uniformoutput', 0);
    elseif matches(theFolder, {'Dark', 'dark', 'Offset', 'offset'})
         DarkImage= [dir([thisFolder '/*.tif']);dir([thisFolder '/*.tiff']);...
                      dir([thisFolder '/*.png']); dir([thisFolder '/*.jpg']);...
                      dir([thisFolder '/*.dcm']); dir([thisFolder '/*.fits']);...
                      dir([thisFolder '/*.fts']); dir([thisFolder '/*.img']);...
                      dir([thisFolder '/*.raw']); dir([thisFolder '/*.his']);...
                      dir([thisFolder '/*.hdr']); dir([thisFolder '/*.nitf'])];   
         DarkFileNames= {DarkImage(:,1).name}'; 
         DarkFilenames = fullfile(thisFolder, DarkFileNames);
         DarkImageData = cellfun(@ReadInputImage, DarkFilenames , 'uniformoutput', 0);
    end 
 end
    if ~exist('BrightImageData','var') || isempty(BrightImageData) || ~exist ('DarkImageData','var') || isempty(DarkImageData)
       msgbox(sprintf('Either Bright or Dark Images Not Found','warn'));
    end
tic; 
parpool('local',gpuDeviceCount);
parfor ii = 1:numel(RawImageData)
    G = gpuArray(RawImageData{ii});
    FilterImage{ii}=medfilt2(G,[5,5]);
end
delete(gcp('nocreate'));
toc; 

Answer 1

[Shadaab Siddiqie]

When training with multiple GPUs, each image batch is distributed between the GPUs. This effectively increases the total GPU memory available, allowing larger batch sizes. Because it improves the significance of each batch, you can increase the learning rate. A good general guideline is to increase the learning rate proportionally to the increase in batch size. For more information refere this link.

[Muhammad Abir]

Did you see my code? It’s not about deep learning. It’s about image processing

[Shadaab Siddiqie]

From my understanding in this case reading the images is taking much more time than processing thus, you are not seeing any improvent by using multiple GPU.

[Muhammad Abir]

That;s okay. But I have many functions like medfilt2 that I want them to run in multiple GPU. I don't find any solution to that problem.