benchmark.html

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<title>Numeric Javascript: Benchmarks</title>
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We are now running a linear algebra performance benchmark; the results are plotted below. As we move right within each
test, the matrix size increases.<br><br>

<b>Performance (<a href="http://en.wikipedia.org/wiki/FLOPS">MFLOPS</a>; higher is better).</b>
<div style="width:1000px;overflow:hidden;font-size:14px;line-height:100%;">
<div id="placeholder" style="width:700px;height:500px;float:left;"></div>
<div id="legend" style="width:250px;height:100px;overflow:hidden;"></div>
</div>
<div id="meanscore">Geometric mean of scores: </div><br>

<table id="bench"></table>

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<script src="tools/benchlib.js"></script>

<script>
"use strict";

// Guess which browser needs this.
if (!('map' in Array.prototype)) {
    Array.prototype.map= function(mapper, that /*opt*/) {
        var other= new Array(this.length);
        for (var i= 0, n= this.length; i<n; i++)
            if (i in this)
                other[i]= mapper.call(that, this[i], i, this);
        return other;
    };
}

goog.require('goog.math.Matrix');
var bench = numeric.bench;
var geometricmeans = [0,0,0];
var mkA = function(n) { return numeric.random([n,n]); };
var mkV = function(n) { return numeric.random([n]); };
var benchmarks = [
	[
	'abs(vector)', [3,10,30,100,300,1000,3000],
	function(n) { var V = mkV(n); return bench(function() { numeric.abs(V); }); },
	function(n) { var V = new goog.math.Matrix([mkV(n)]); return bench(function() { V.toArray().map(Math.abs); }); },
	function(n) { var V = $V(mkV(n)); return bench(function() { V.map(Math.abs); }); }
	],
	[
	'Create identity', [3,10,30,100,300,1000],
	function(n) { return bench(function() { numeric.identity(n); }); },
	function(n) { return bench(function() { goog.math.Matrix.createIdentityMatrix(n); }); },
	function(n) { return bench(function() { Matrix.I(n); }); }
	],
	[
	'Matrix transpose', [3,10,30,100,300,1000],
	function(n) { var A = mkA(n); return bench(function() { numeric.transpose(A); }); },
	function(n) { var A = new goog.math.Matrix(mkA(n)); return bench(function() { A.getTranspose(); }); },
	function(n) { var A = $M(mkA(n)); return bench(function() { A.transpose(); }); }
	],
	[
	'Matrix-Vector product', [3,10,30,100,300,1000],
	function(n) { var A = mkA(n), V = mkV(n); return bench(function() { numeric.dot(A,V); }); },
	function(n) { var A = new goog.math.Matrix(mkA(n)), V = new goog.math.Matrix([mkV(n)]).getTranspose(); return bench(function() { A.multiply(V); }); },
	function(n) { var A = $M(mkA(n)), V = $V(mkV(n)); return bench(function() { A.multiply(V); }); }
	],
	[
	'Vector-Matrix product', [3,10,30,100,300,1000],
	function(n) { var A = mkA(n), V = mkV(n); return bench(function() { numeric.dot(V,A); }); },
	function(n) { var A = new goog.math.Matrix(mkA(n)), V = new goog.math.Matrix([mkV(n)]); return bench(function() { V.multiply(A); }); },
	function(n) { var A = $M(mkA(n)), V = $V(mkV(n)); return bench(function() { A.transpose().multiply(V); }); }
	],
	['Ax+b', [3,10,30,100,300,1000],
	function(n) { var A = mkA(n), x = mkV(n), b = mkV(n); return bench(function() { numeric.addeq(numeric.dot(A,x),b); }); },
	function(n) { var A = new goog.math.Matrix(mkA(n)), x = new goog.math.Matrix([mkV(n)]).getTranspose(), b = new goog.math.Matrix([mkV(n)]).getTranspose(); return bench(function() { A.multiply(x).add(b); }); },
	function(n) { var A = $M(mkA(n)), x = $V(mkV(n)), b = $V(mkV(n)); return bench(function() { A.multiply(x).add(b); }); }
	],
	[
	'Matrix-Matrix product', [3,5,10,20,30,50,75,100],
	function(n) { var A = mkA(n), B = mkA(n); return bench(function() { numeric.dot(A,B); }); },
	function(n) { var A = new goog.math.Matrix(mkA(n)), B = new goog.math.Matrix(mkA(n)); return bench(function() { A.multiply(B); }); },
	function(n) { var A = $M(mkA(n)), B = $M(mkA(n)); return bench(function() { A.multiply(B); }); }
	],
	[
	'Matrix-Matrix sum', [3,5,10,20,30,50,75,100],
	function(n) { var A = mkA(n); return bench(function() { numeric.add(A,A); }); },
	function(n) { var A = new goog.math.Matrix(mkA(n)); return bench(function() { A.add(A); }); },
	function(n) { var A = $M(mkA(n)); return bench(function() { A.add(A); }); }
	],
	[
	'Matrix inverse', [3,5,10,20,30,50,75,100],
	function(n) { var A = mkA(n); return bench(function() { numeric.inv(A); }); },
	function(n) { var A = new goog.math.Matrix(mkA(n)); return bench(function() { A.getInverse(); }); },
	function(n) { var A = $M(mkA(n)); return bench(function() { A.inv(); }); }
	],
    [
    'Sparse Laplacian LU', [5,10,20,30],
    function(n) { var A = numeric.ccsScatter(numeric.cdelsq(numeric.cgrid(n))); return bench(function() { numeric.ccsLUP(A); }); },
    function(n) { return 0; },
    function(n) { return 0; }
    ],
    [
    'Banded Laplacian LU', [5,10,20,30],
    function(n) { var A = numeric.cdelsq(numeric.cgrid(n)); return bench(function() { numeric.cLU(A); }); },
    function(n) { return 0; },
    function(n) { return 0; }
    ]
];

var pwr = [1,2,2,2,2,2,3,2,3,4,4];

var k=0,b=0;
var libs = ['Numeric '+numeric.version,'Closure 5 Dec 2011','Sylvester 5 Dec 2011'];
var datasets = [];
var l;
var colors = ["#000","#00f","#0f0","#f80","#f0f","#0ff"];
for(l=0;l<libs.length;l++) { 
	datasets[l] = { 
		data: [], 
		label: libs[l], 
		color: colors[l], 
		points: { show: true }, 
		lines: { show: true } 
		};
}
l=1;
var l0,xticks = [];
for(b=0;b<benchmarks.length;b++) {
	l0 = l;
	for(k=0;k<benchmarks[b][1].length;k++) {
		l++;
	}
	xticks.push([(l0+l)*0.5,benchmarks[b][0]]);
}
k=0;
b=0;
var count = 1;
var MSIE = (/MSIE (\d+\.\d+);/.test(navigator.userAgent));
numeric.precision = 6;
var c0 = [[],[],[]];
var counts = [0,0,0];
function invbench(b,k,lib,rep) {
	var ks,sz = benchmarks[b][1][k];
	var i,j,foo;
	ks = sz.toString();
	if(rep>0 && c0[lib][rep-1] < 10) { c0[lib][rep] = c0[lib][rep-1]; }
	else { foo = benchmarks[b][lib+2]; if(k===0) foo(sz); c0[lib][rep] = foo(sz); }
	rep++;
	if(rep === 1) { rep = 0; lib++; }
	if(lib+2 === benchmarks[b].length) {
		k++;
		lib=0;
		var cps = [];
		var mi = 1e6/Math.pow(benchmarks[b][1][k-1],pwr[b]);
		for(i=0;i<c0.length;i++) {
		    cps[i] = 0;
		    for(j=0;j<c0[i].length;j++) cps[i] += c0[i][j];
			cps[i] /= (c0[i].length*mi);
		}
		for(i=0;i<cps.length;i++) {
			if(MSIE || cps[i]) datasets[i].data.push([count,cps[i]]);
			if(cps[i]) {
			    counts[i]++;
			    geometricmeans[i] += Math.log(cps[i]);
			}
		}
		var foo = '<td>n='+ks+'</td>';
		var color = '', uncolor='';
		for(i=0;i<cps.length;i++) {
			foo +=  '<td>'+cps[i].toPrecision(8)+'</td>';
		}
		if(!MSIE) {
			var t = document.getElementById('bench');
			var r = t.insertRow(-1);
			if(k === 1) { 
				r.innerHTML = ('<td width=200px><b>'+benchmarks[b][0]+'</b></td>'
			    	          +'<td width=125px><b>Numeric</b></td>'
		            	      +'<td width=125px><b>Google Closure</b></td>'
		                	  +'<td width=125px><b>Sylvester</b></td>');
				r = t.insertRow(-1); 
			}
			r.innerHTML = foo;
		}
		$.plot($("#placeholder"), datasets, 
		    { 
		   	  legend: {container: '#legend'}, 
	    	  xaxis:  {ticks:xticks, tickLength:0, min:1, max: l-1},
	    	  yaxis:  {ticks:20}
    		});
	    c0 = [[],[],[]];
		count++;
	}
	if(k === benchmarks[b][1].length) {
		for(i=0;i<cps.length;i++) datasets[i].data.push(null);
		k=0; b++;
	}
	if(b < benchmarks.length) { 
		setTimeout('invbench('+b.toString()
		                  +','+k.toString()
		                  +','+lib.toString()
		                  +','+rep.toString()
		                  +')',MSIE?10:0); 
    } else {
        geometricmeans = numeric.exp(numeric.div(geometricmeans,counts));
        $('#meanscore')[0].innerHTML += numeric.prettyPrint(geometricmeans)+'MFLOPS';
    }
}
window.onload = function() { invbench(0,0,0,0); }
</script>

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