MATLAB GPU Tutorial

Run a MATLAB script that performs a regression test comparing the computation time of a non-GPU-based computation with that of a GPU-based computation.

MATLAB Script

% gpu-bench.m
for i = 300:100:700
    fprintf('i = %d\n', i);

    % Generates a random matrix X of size 1000i by 800 and a vector Y of size 1000i by 1
    X = random('unif', 0, 1, 1000*i, 800);
    Beta = [1:801]';
    allones = ones(1000*i, 1);

    % Add a constant term
    X = [allones, X];
    Y = X * Beta + random('norm', 0, 1, 1000*i, 1);

    % Non-GPU computation
    disp('Time for non-GPU:');
    tic;
    Bestimate = inv(X'*X) * (X'*Y);
    Bestimate = inv(X'*X) * (X'*Y);
    Bestimate = inv(X'*X) * (X'*Y);
    Bestimate = inv(X'*X) * (X'*Y);
    toc;

    % Now do it on the GPU
    % Copy the data to the GPU and create gX and gY in the GPU
    disp('Load time for GPU:');
    tic;
    gX = gpuArray(X);
    gY = gpuArray(Y);
    gBestimate = gpuArray(zeros(801, 1));
    toc;

    % GPU computation
    disp('Time for GPU compute:');
    tic;
    gBestimate = inv(gX'*gX) * (gX'*gY);
    gBestimate = inv(gX'*gX) * (gX'*gY);
    gBestimate = inv(gX'*gX) * (gX'*gY);
    gBestimate = inv(gX'*gX) * (gX'*gY);
    toc;

    % Copy estimates back
    disp('Copy estimates back:');
    tic;
    Bestimate = gather(gBestimate);
    toc;
end

The script generates a random matrix X of size 1000i by 800 and a vector Y of size 1000i by 1. 

It then adds a column of ones to X to account for the intercept term in the regression model.

Next, it computes the regression coefficients (Bestimate) using the ordinary least squares (OLS) method for the non-GPU-based computation, and it computes the regression coefficients (gBestimate) using the OLS method on the GPU.

Slurm Script

#!/bin/bash
#
# [ gpu-bench.sbatch ]
#SBATCH --job-name=gpu-bench
#SBATCH --output=gpu-bench.%j.out
#SBATCH --export=ALL
#SBATCH --gpu-bind=closest
#SBATCH --time=00:9:00
#SBATCH --mem=32G
#SBATCH --mail-type=END,FAIL
#SBATCH --partition=gpu
#
# `--partition=gpu` specifies that we want to run it on the GPU node
#
# This script runs a MATLAB program saving the output into a files called:
# gpu-bench_#.out, where the # represents the jobID.  See below.
#
#
#
# You SUBMIT this 'gpu-bench.sbatch' script to the grid with the  sbatch  command:
#
#
#     sbatch  gpu-bench.sbatch
#
# Specify the software and version to use, and run the MATLAB program:
  echo "Running on node: `hostname`"
  echo ""


  module  purge
  module  load    matlab/2019a

  matlab -nojvm < gpu-bench.m

You can run the following command to execute the script:

sbatch gpu-bench.sbatch

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