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harvyso/MathLibBenchmark.java

Forked from thomasjungblut/MathLibBenchmark.java
Created March 22, 2020 18:55
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  1. @thomasjungblut thomasjungblut created this gist May 26, 2013.
    80 changes: 80 additions & 0 deletions MathLibBenchmark.java
    View file
    Original file line number Diff line number Diff line change
    @@ -0,0 +1,80 @@
    package de.jungblut.benchmark;

    import java.util.Random;

    import com.google.caliper.Param;
    import com.google.caliper.Runner;
    import com.google.caliper.SimpleBenchmark;

    import de.jungblut.math.DoubleMatrix;
    import de.jungblut.math.cuda.JCUDAMatrixUtils;
    import de.jungblut.math.dense.DenseDoubleMatrix;

    public class MathLibBenchmark extends SimpleBenchmark {

    @Param({ "10", "20", "40", "60", "80", "100", "500", "1000", "2000" })
    private int n;

    @Param
    CalcType type;

    private DenseDoubleMatrix mat;
    private DenseDoubleMatrix mat2;

    public enum CalcType {
    GPU, JBLAS, TJ_MATH
    };

    @Override
    protected void setUp() throws Exception {
    mat = new DenseDoubleMatrix(n, n, new Random());
    mat2 = new DenseDoubleMatrix(n, n, new Random());
    }

    public void timeCalculate(int reps) {
    for (int rep = 0; rep < reps; rep++) {
    int sum = 0;
    switch (type) {
    case JBLAS:
    sum = jblas(sum);
    break;
    case TJ_MATH:
    sum = tjmath(sum);
    break;
    case GPU:
    sum = gpu(sum);
    break;
    default:
    break;
    }
    System.out.println(sum);
    }

    }

    private int gpu(int sum) {
    DenseDoubleMatrix multiply2 = JCUDAMatrixUtils.multiply(mat, mat2);
    sum += multiply2.getColumnCount();
    return sum;
    }

    private int tjmath(int sum) {
    DoubleMatrix multiply = mat.multiply(mat2);
    sum += multiply.getRowCount();
    return sum;
    }

    private int jblas(int sum) {
    org.jblas.DoubleMatrix jblasThis = new org.jblas.DoubleMatrix(mat.toArray());
    org.jblas.DoubleMatrix jblasOther = new org.jblas.DoubleMatrix(
    mat2.toArray());
    org.jblas.DoubleMatrix jblasRes = new org.jblas.DoubleMatrix(n, n);
    jblasThis.mmuli(jblasOther, jblasRes);
    sum += jblasRes.columns;
    return sum;
    }

    public static void main(String[] args) {
    Runner.main(MathLibBenchmark.class, args);
    }
    }