单多处理性能问题

在Mono上运行计算密集型多进程代码时，我遇到了严重的性能问题。下面的简单片段使用蒙特卡罗方法估计pi的值，说明了这个问题。

该程序生成的线程数等于当前机器上的逻辑核数，并在每个线程上执行相同的计算。当使用.NET Framework 4.5在装有Windows 7的英特尔酷睿i7笔记本电脑上运行时，整个过程在4.2中运行s、 线程各自的执行时间之间的相对标准偏差为2%。

然而，当使用Mono 2.10.9在同一台机器（和操作系统）上运行时，总执行时间会飙升至18s。各个线程的性能差异很大，最快完成时间仅为5.6s，而最慢的需要18s.平均值为14s、 相对标准偏差为28%。

原因似乎不是线程调度。将每个线程固定到不同的核心（通过调用BeginThreadAffinity和SetThreadAffinityMask）对线程的持续时间或差异没有任何显著影响。

类似地，在每个线程上多次运行计算（并单独计时）也会给出看似临时的持续时间。因此，这个问题似乎也不是由每个处理器的预热时间引起的。

我发现有区别的是将所有8个线程都固定在同一个处理器上。在这种情况下，总执行量为25s、 这只比在单个线程上执行8倍的工作慢1%。此外，相对标准偏差也降至1%以下。因此，问题不在于Mono的多线程本身，而在于它的多处理。

有人有解决方案来解决这个性能问题吗？

static long limit = 1L << 26;
static long[] results;
static TimeSpan[] timesTaken;
internal static void Main(string[] args)
{
    int processorCount = Environment.ProcessorCount;
    Console.WriteLine("Thread count: " + processorCount);
    Console.WriteLine("Number of points per thread: " + limit.ToString("N0"));
    Thread[] threads = new Thread[processorCount];            
    results = new long[processorCount];
    timesTaken = new TimeSpan[processorCount];
    for (int i = 0; i < processorCount; ++i)
        threads[i] = new Thread(ComputeMonteCarloPi);
    Stopwatch stopwatch = Stopwatch.StartNew();
    for (int i = 0; i < processorCount; ++i)
        threads[i].Start(i);
    for (int i = 0; i < processorCount; ++i)
        threads[i].Join();
    stopwatch.Stop();
    double average = results.Average();
    double ratio = average / limit;
    double pi = ratio * 4;
    Console.WriteLine("Pi: " + pi);
    Console.WriteLine("Overall duration:   " + FormatTime(stopwatch.Elapsed));
    Console.WriteLine();
    for (int i = 0; i < processorCount; ++i)
        Console.WriteLine("Thread " + i.ToString().PadLeft(2, '0') + " duration: " + FormatTime(timesTaken[i]));
    Console.ReadKey();
}
static void ComputeMonteCarloPi(object o)
{
    int processorID = (int)o;
    Random random = new Random(0);
    Stopwatch stopwatch = Stopwatch.StartNew();
    long hits = SamplePoints(random);
    stopwatch.Stop();
    timesTaken[processorID] = stopwatch.Elapsed;
    results[processorID] = hits;
}
private static long SamplePoints(Random random)
{
    long hits = 0;
    for (long i = 0; i < limit; ++i)
    {
        double x = random.NextDouble() - 0.5;
        double y = random.NextDouble() - 0.5;
        if (x * x + y * y <= 0.25)
            hits++;
    }
    return hits;
}
static string FormatTime(TimeSpan time, int padLeft = 7)
{
    return time.TotalMilliseconds.ToString("N0").PadLeft(padLeft);
}

NET上的输出：

Thread count: 8
Number of points per thread: 67,108,864
Pi: 3.14145541191101
Overall duration:     4,234
Thread 00 duration:   4,199
Thread 01 duration:   3,987
Thread 02 duration:   4,002
Thread 03 duration:   4,032
Thread 04 duration:   3,956
Thread 05 duration:   3,980
Thread 06 duration:   4,036
Thread 07 duration:   4,160

单声道输出：

Thread count: 8
Number of points per thread: 67,108,864
Pi: 3.14139330387115
Overall duration:    17,890
Thread 00 duration:  10,023
Thread 01 duration:  13,203
Thread 02 duration:  14,776
Thread 03 duration:  15,564
Thread 04 duration:  17,888
Thread 05 duration:  16,776
Thread 06 duration:  16,050
Thread 07 duration:   5,561

单声道输出，所有线程固定在同一处理器上：

Thread count: 8
Number of points per thread: 67,108,864
Pi: 3.14139330387115
Overall duration:    25,260
Thread 00 duration:  24,704
Thread 01 duration:  25,191
Thread 02 duration:  24,689
Thread 03 duration:  24,697
Thread 04 duration:  24,716
Thread 05 duration:  24,725
Thread 06 duration:  24,707
Thread 07 duration:  24,720

单声道输出，单线程：

Thread count: 1
Number of points per thread: 536,870,912
Pi: 3.14153660088778
Overall duration:    25,090