001/** 002 * Copyright (c) 2011, The University of Southampton and the individual contributors. 003 * All rights reserved. 004 * 005 * Redistribution and use in source and binary forms, with or without modification, 006 * are permitted provided that the following conditions are met: 007 * 008 * * Redistributions of source code must retain the above copyright notice, 009 * this list of conditions and the following disclaimer. 010 * 011 * * Redistributions in binary form must reproduce the above copyright notice, 012 * this list of conditions and the following disclaimer in the documentation 013 * and/or other materials provided with the distribution. 014 * 015 * * Neither the name of the University of Southampton nor the names of its 016 * contributors may be used to endorse or promote products derived from this 017 * software without specific prior written permission. 018 * 019 * THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND 020 * ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED 021 * WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE 022 * DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE LIABLE FOR 023 * ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES 024 * (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; 025 * LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON 026 * ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT 027 * (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS 028 * SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. 029 */ 030package org.openimaj.ml.benchmark; 031 032import java.util.Random; 033 034import org.openimaj.math.matrix.CFMatrixUtils; 035import org.openimaj.math.matrix.MeanVector; 036import org.openimaj.time.Timer; 037 038import no.uib.cipr.matrix.sparse.FlexCompRowMatrix; 039import gov.sandia.cognition.math.matrix.mtj.SparseColumnMatrix; 040import gov.sandia.cognition.math.matrix.mtj.SparseMatrix; 041import gov.sandia.cognition.math.matrix.mtj.SparseMatrixFactoryMTJ; 042import gov.sandia.cognition.math.matrix.mtj.SparseRowMatrix; 043 044/** 045 * 046 * @author Sina Samangooei (ss@ecs.soton.ac.uk) 047 */ 048public class CFMatrixMultiplyBenchmark { 049 050 public static void main(String[] args) { 051 SparseMatrix a = SparseMatrixFactoryMTJ.INSTANCE.copyMatrix(SparseMatrixFactoryMTJ.INSTANCE.createWrapper(new FlexCompRowMatrix(4, 1118))); 052 CFMatrixUtils.plusInplace(a, 1); 053 SparseRowMatrix xtrow = CFMatrixUtils.randomSparseRow(1118,22917,0d,1d,1 - 0.9998818947086253, new Random(1)); 054 SparseColumnMatrix xtcol = CFMatrixUtils.randomSparseCol(1118,22917,0d,1d,1 - 0.9998818947086253, new Random(1)); 055 056 System.out.println("xtrow sparsity: " + CFMatrixUtils.sparsity(xtrow)); 057 System.out.println("xtcol sparsity: " + CFMatrixUtils.sparsity(xtcol)); 058 System.out.println("Equal: " + CFMatrixUtils.fastsparsedot(a,xtcol).equals(a.times(xtcol), 0)); 059 MeanVector mv = new MeanVector(); 060 System.out.println("doing: a . xtcol"); 061 for (int i = 0; i < 10; i++) { 062 Timer t = Timer.timer(); 063 CFMatrixUtils.fastsparsedot(a,xtcol); 064 mv.update(new double[]{t.duration()}); 065 System.out.println("time: " + mv.vec()[0]); 066 } 067 068 069 mv.reset(); 070 System.out.println("doing: a . xtcol"); 071 for (int i = 0; i < 10; i++) { 072 Timer t = Timer.timer(); 073 a.times(xtcol); 074 mv.update(new double[]{t.duration()}); 075 System.out.println("time: " + mv.vec()[0]); 076 } 077 mv.reset(); 078 System.out.println("doing: a . xtrow"); 079 for (int i = 0; i < 10; i++) { 080 Timer t = Timer.timer(); 081 a.times(xtrow); 082 mv.update(new double[]{t.duration()}); 083 System.out.println("time: " + mv.vec()[0]); 084 } 085 } 086}