Parallel computing in Octave on a single machine -- package and example

Question

I would like to parallelize a for loop in Octave on a single machine (as opposed to a cluster). I asked a question about a parallel version of Octave a while ago parallel computing in octave

And the answer suggested that I download a parallel computing package, which I did. The package seems largely geared to cluster computing, but it did mention single machine parallel computing, but was not clear on how to run even a parallel loop.

I also found another question on SO about this, but I did not find a good answer for parallelizing loops in Octave: Running portions of a loop in parallel with Octave?

Does anyone know where I can find an example of running a for loop in parallel in Octave???

Answer 1

I am computing large number of RGB histograms. I need to use explicit loops to do it. Therefore computation of each histogram takes noticeable time. For this reason running the computations in parallel makes sense. In Octave there is an (experimental) function parcellfun written by Jaroslav Hajek that can be used to do it.

My original loop

histograms = zeros(size(files,2), bins^3);
  % calculate histogram for each image
  for c = 1 : size(files,2)
    I = imread(fullfile(dir, files{c}));
    h = myhistRGB(I, bins);
    histograms(c, :) = h(:); % change to 1D vector
  end

To use parcellfun, I need to refactor the body of my loop into a separate function.

function histogram = loadhistogramp(file)
  I = imread(fullfile('.', file));
  h = myhistRGB(I, 8);
  histogram = h(:); % change to 1D vector
end

then I can call it like this

histograms = parcellfun(8, @loadhistogramp, files);

I did a small benchmark on my computer. It is 4 physical cores with Intel HyperThreading enabled.

My original code

tic(); histograms2 = loadhistograms('images.txt', 8); toc();
warning: your version of GraphicsMagick limits images to 8 bits per pixel
Elapsed time is 107.515 seconds.

With parcellfun

octave:1> pkg load general; tic(); histograms = loadhistogramsp('images.txt', 8); toc();
parcellfun: 0/178 jobs donewarning: your version of GraphicsMagick limits images to 8 bits per pixel
warning: your version of GraphicsMagick limits images to 8 bits per pixel
warning: your version of GraphicsMagick limits images to 8 bits per pixel
warning: your version of GraphicsMagick limits images to 8 bits per pixel
warning: your version of GraphicsMagick limits images to 8 bits per pixel
warning: your version of GraphicsMagick limits images to 8 bits per pixel
warning: your version of GraphicsMagick limits images to 8 bits per pixel
warning: your version of GraphicsMagick limits images to 8 bits per pixel
parcellfun: 178/178 jobs done
Elapsed time is 29.02 seconds.

(The results from the parallel and serial version were the same (only transposed).

octave:6> sum(sum((histograms'.-histograms2).^2))
ans = 0

When I repeated this several times, the running times were pretty much the same all the time. The parallel version was running around 30 second (+- approx 2s) with both 4, 8 and also 16 subprocesses)