为什么Parallel.For只为这个特定函数提供了这么少的收益?

时间:2014-11-25 19:43:39

标签: c# concurrency parallel-processing task-parallel-library unsafe

我无法理解为什么我的http://www.codeproject.com/Tips/447938/High-performance-Csharp-byte-array-to-hex-string-t函数的“并发”实现只有大约20%的性能提升。

为方便起见,这里是该网站的代码:

static readonly int[] toHexTable = new int[] {
    3145776, 3211312, 3276848, 3342384, 3407920, 3473456, 3538992, 3604528, 3670064, 3735600,
    4259888, 4325424, 4390960, 4456496, 4522032, 4587568, 3145777, 3211313, 3276849, 3342385,
    3407921, 3473457, 3538993, 3604529, 3670065, 3735601, 4259889, 4325425, 4390961, 4456497,
    4522033, 4587569, 3145778, 3211314, 3276850, 3342386, 3407922, 3473458, 3538994, 3604530,
    3670066, 3735602, 4259890, 4325426, 4390962, 4456498, 4522034, 4587570, 3145779, 3211315,
    3276851, 3342387, 3407923, 3473459, 3538995, 3604531, 3670067, 3735603, 4259891, 4325427,
    4390963, 4456499, 4522035, 4587571, 3145780, 3211316, 3276852, 3342388, 3407924, 3473460,
    3538996, 3604532, 3670068, 3735604, 4259892, 4325428, 4390964, 4456500, 4522036, 4587572,
    3145781, 3211317, 3276853, 3342389, 3407925, 3473461, 3538997, 3604533, 3670069, 3735605,
    4259893, 4325429, 4390965, 4456501, 4522037, 4587573, 3145782, 3211318, 3276854, 3342390,
    3407926, 3473462, 3538998, 3604534, 3670070, 3735606, 4259894, 4325430, 4390966, 4456502,
    4522038, 4587574, 3145783, 3211319, 3276855, 3342391, 3407927, 3473463, 3538999, 3604535,
    3670071, 3735607, 4259895, 4325431, 4390967, 4456503, 4522039, 4587575, 3145784, 3211320,
    3276856, 3342392, 3407928, 3473464, 3539000, 3604536, 3670072, 3735608, 4259896, 4325432,
    4390968, 4456504, 4522040, 4587576, 3145785, 3211321, 3276857, 3342393, 3407929, 3473465,
    3539001, 3604537, 3670073, 3735609, 4259897, 4325433, 4390969, 4456505, 4522041, 4587577,
    3145793, 3211329, 3276865, 3342401, 3407937, 3473473, 3539009, 3604545, 3670081, 3735617,
    4259905, 4325441, 4390977, 4456513, 4522049, 4587585, 3145794, 3211330, 3276866, 3342402,
    3407938, 3473474, 3539010, 3604546, 3670082, 3735618, 4259906, 4325442, 4390978, 4456514,
    4522050, 4587586, 3145795, 3211331, 3276867, 3342403, 3407939, 3473475, 3539011, 3604547,
    3670083, 3735619, 4259907, 4325443, 4390979, 4456515, 4522051, 4587587, 3145796, 3211332,
    3276868, 3342404, 3407940, 3473476, 3539012, 3604548, 3670084, 3735620, 4259908, 4325444,
    4390980, 4456516, 4522052, 4587588, 3145797, 3211333, 3276869, 3342405, 3407941, 3473477,
    3539013, 3604549, 3670085, 3735621, 4259909, 4325445, 4390981, 4456517, 4522053, 4587589,
    3145798, 3211334, 3276870, 3342406, 3407942, 3473478, 3539014, 3604550, 3670086, 3735622,
    4259910, 4325446, 4390982, 4456518, 4522054, 4587590
};

public static unsafe string ToHex1(byte[] source)
{
    fixed (int* hexRef = toHexTable)
    fixed (byte* sourceRef = source)
    {
        byte* s = sourceRef;
        int resultLen = (source.Length << 1);

        var result = new string(' ', resultLen);
        fixed (char* resultRef = result)
        {
            int* pair = (int*)resultRef;

            while (*pair != 0)
                *pair++ = hexRef[*s++];
            return result;
        }
    }
}

以下是我的“改进”:

public static unsafe string ToHex1p(byte[] source)
{
    var chunks = Environment.ProcessorCount;
    var n = (int)Math.Ceiling(source.Length / (double)chunks);

    int resultLen = (source.Length << 1);

    var result = new string(' ', resultLen);

    Parallel.For(0, chunks, k =>
    {
        var l = Math.Min(source.Length, (k + 1) * n);
        fixed (char* resultRef = result) fixed (byte* sourceRef = source)
        {
            int from = n * k;
            int to = (int)resultRef + (l << 2);

            int* pair = (int*)resultRef + from;
            byte* s = sourceRef + from;
            while ((int)pair != to)
                *pair++ = toHexTable[*s++];
        }
    });

    return result;
}


修改1 这就是我计算时间的方法:

var n = 0xff;
var s = new System.Diagnostics.Stopwatch();
var d = Enumerable.Repeat<byte>(0xce, (int)Math.Pow(2, 23)).ToArray();

s.Start();
for (var i = 0; i < n; ++i)
{
    Binary.ToHex1(d);
}
Console.WriteLine(s.ElapsedMilliseconds / (double)n);

s.Restart();
for (var i = 0; i < n; ++i)
{
    Binary.ToHex1p(d);
}
Console.WriteLine(s.ElapsedMilliseconds / (double)n);

1 个答案:

答案 0 :(得分:0)

我在第一个答案的评注中读到(顺便提一下,这个问题比评论和评论更全面),这些测试的执行时间最多只有25毫秒。

关于这一点有很多话要说,但首先是&#34;浪费好程序员的时间!&#34;

这是一个过度优化的明显案例。在我第一眼浏览代码时,我想&#34;为什么世界上有人想要并行这个?&#34;你正在进行按位操作,这非常迅速。首先,没有足够的性能损失来证明并行性。

现在,您的测试差异。 TPL是一个复杂的库,并行性比单线程更复杂一个数量级。因此,当您运行测试时会有许多因素发挥作用,其中几个(但并非全部)在各种注释中都有提及。每个因素都会以不可预测的方式影响结果,您可以将每个因素视为添加一些变化。最后,您的测试结果没有足够的力量来区分这两者,这是过度优化的另一个迹象。

作为程序员,我们需要记住,作为一般规则,我们的时间非常昂贵,特别是与计算机时间相比时。在编程时很少有机会实现真正的,增值的性能提升,并且通常以非常昂贵的处理或需要从远程服务器请求的情况为中心等等。肯定有时候需要它,但这不是它们。