Lou*_*cci 35 javascript sorting algorithm optimization performance
_radixSort_0 = [0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,
0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,
0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,
0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,
0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,
0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,
0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,
0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,
0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,
0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,
0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,
0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,
0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,
0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,
0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,
0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0];
/*
RADIX SORT
Use 256 bins
Use shadow array
- Get counts
- Transform counts to pointers
- Sort from LSB - MSB
*/
function radixSort(intArr) {
var cpy = new Int32Array(intArr.length);
var c4 = [].concat(_radixSort_0);
var c3 = [].concat(_radixSort_0);
var c2 = [].concat(_radixSort_0);
var c1 = [].concat(_radixSort_0);
var o4 = 0; var t4;
var o3 = 0; var t3;
var o2 = 0; var t2;
var o1 = 0; var t1;
var x;
for(x=0; x<intArr.length; x++) {
t4 = intArr[x] & 0xFF;
t3 = (intArr[x] >> 8) & 0xFF;
t2 = (intArr[x] >> 16) & 0xFF;
t1 = (intArr[x] >> 24) & 0xFF ^ 0x80;
c4[t4]++;
c3[t3]++;
c2[t2]++;
c1[t1]++;
}
for (x=0; x<256; x++) {
t4 = o4 + c4[x];
t3 = o3 + c3[x];
t2 = o2 + c2[x];
t1 = o1 + c1[x];
c4[x] = o4;
c3[x] = o3;
c2[x] = o2;
c1[x] = o1;
o4 = t4;
o3 = t3;
o2 = t2;
o1 = t1;
}
for(x=0; x<intArr.length; x++) {
t4 = intArr[x] & 0xFF;
cpy[c4[t4]] = intArr[x];
c4[t4]++;
}
for(x=0; x<intArr.length; x++) {
t3 = (cpy[x] >> 8) & 0xFF;
intArr[c3[t3]] = cpy[x];
c3[t3]++;
}
for(x=0; x<intArr.length; x++) {
t2 = (intArr[x] >> 16) & 0xFF;
cpy[c2[t2]] = intArr[x];
c2[t2]++;
}
for(x=0; x<intArr.length; x++) {
t1 = (cpy[x] >> 24) & 0xFF ^ 0x80;
intArr[c1[t1]] = cpy[x];
c1[t1]++;
}
return intArr;
}
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到目前为止,最佳/唯一的主要优化是JS类型的数组.对正常基数排序的阴影数组使用类型数组已经产生了最好的结果.我还能够使用JS内置堆栈push/pop来快速挤出一些额外的快速排序.
Intel i7 870, 4GB, FireFox 8.0
2mil
radixSort(intArr): 172 ms
radixSortIP(intArr): 1738 ms
quickSortIP(arr): 661 ms
200k
radixSort(intArr): 18 ms
radixSortIP(intArr): 26 ms
quickSortIP(arr): 58 ms
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似乎标准基数排序确实是这项工作流程的王者.如果有人有时间尝试循环展开或其他修改,我将不胜感激.
我有一个特定的用例,我希望在JavaScript中尽可能快地实现排序.客户端脚本将访问大型(50,000 - 2mil),未分类(基本上是随机的),整数(32位有符号)数组,然后需要对这些数据进行排序和显示.
我已经实现了相当快速的基数排序和快速排序jsfiddle基准测试,但对于我的上限数组长度,它们仍然相当慢.快速排序在我的上限数组大小上表现更好,而基数排序在我的下限上表现更好.
defaultSort is the built-in JavaScript array.sort with an integer compare function
Intel C2Q 9650, 4GB, FireFox 3.6
2mil
radixSortIP(intArr): 5554 ms
quickSortIP(arr): 1796 ms
200k
radixSortIP(intArr): 139 ms
quickSortIP(arr): 190 ms
defaultSort(intArr): 354 ms
Intel i7 870, 4GB, FireFox 8.0
2mil
radixSortIP(intArr): 990 ms
quickSortIP(arr): 882 ms
defaultSort(intArr): 3632 ms
200k
radixSortIP(intArr): 28 ms
quickSortIP(arr): 68 ms
defaultSort(intArr): 306 ms
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gbl*_*zex 12
我测试了类型化数组,QSIP版本似乎在现代浏览器中很好:
2 000 000个元素
QSIP_TYPED | RDXIP_TYPED | QSIP_STD | RDXIP_STD
----------------------------------------------------------
Chrome | 300 1000 600 1300
Firefox | 550 1500 800 1600
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支持(来源: http ://caniuse.com/typedarrays):
IE 10+ | FF 4+ | Chrome 7+ | Safari 5.1+ | Opera 11.6+
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