MatrixBenchmark.java

/*
 * Encog(tm) Java Examples v3.4
 * http://www.heatonresearch.com/encog/
 * https://github.com/encog/encog-java-examples
 *
 * Copyright 2008-2016 Heaton Research, Inc.
 *
 * Licensed under the Apache License, Version 2.0 (the "License");
 * you may not use this file except in compliance with the License.
 * You may obtain a copy of the License at
 *
 *     http://www.apache.org/licenses/LICENSE-2.0
 *
 * Unless required by applicable law or agreed to in writing, software
 * distributed under the License is distributed on an "AS IS" BASIS,
 * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 * See the License for the specific language governing permissions and
 * limitations under the License.
 *   
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 */
package org.encog.examples.neural.benchmark;

import org.encog.Encog;
import org.encog.mathutil.matrices.Matrix;
import org.encog.mathutil.matrices.MatrixMath;

public class MatrixBenchmark {

	public static Matrix generateRandomMatrix(final int size) {
		final Matrix result = new Matrix(size, size);
		for (int row = 0; row < size; row++) {
			for (int col = 0; col < size; col++) {
				result.set(row, col, Math.random() * 100);
			}
		}
		return result;
	}

	public static void main(final String args[]) {
		long start, stop;

		start = System.currentTimeMillis();
		final Matrix a = MatrixBenchmark.generateRandomMatrix(500);
		final Matrix b = MatrixBenchmark.generateRandomMatrix(500);
		stop = System.currentTimeMillis();
		System.out.println("Setup matrix: " + ((stop - start)) / 1000.0);

		start = System.currentTimeMillis();
		MatrixMath.multiply(a, b);
		stop = System.currentTimeMillis();
		System.out.println("Multiply matrix: " + ((stop - start)) / 1000.0);
		Encog.getInstance().shutdown();
	}
}