C#线程安全快速(最佳)计数器


147

用C#获得具有最佳性能的线程安全计数器的方法是什么?

这很简单:

public static long GetNextValue()
{
    long result;
    lock (LOCK)
    {
        result = COUNTER++;
    }
    return result;
}

但是有更快的替代方法吗?

Answers:



108

正如其他人所推荐的那样,它们的Interlocked.Increment性能将优于lock()。只需看一下IL和Assembly,您将看到它Increment变成了“总线锁定”语句,并且其变量直接增加(x86)或“增加”到(x64)。

该“总线锁定”语句锁定总线,以防止在调用CPU进行操作时另一个CPU访问该总线。现在,看一下C#lock()语句的IL。在这里,您将看到调用以Monitor开始或结束一个部分。

换句话说,.Net lock()语句的作用远远超过.Net Interlocked.Increment

因此,如果您要做的只是增加一个变量,Interlock.Increment它将更快。查看所有“互锁”方法,以查看可用的各种原子操作并找到适合您需求的操作。使用lock()时,你想去做多个相互关联的递增/递减,或者连续访问更复杂的事情,是不是整数更复杂的资源。


3
-1表示实现细节。的确,锁定比原子操作慢得多,但这与IL无关。如果不是因为它们的语义,这些函数调用将比原子操作快得多,这不是IL固有的要求。
小狗



1

如前所述,使用 Interlocked.Increment

来自MS的代码示例:

下面的示例确定要生成具有中点值的1,000个随机数,需要多少个从0到1,000的随机数。为了跟踪中点值的数量,将变量MidpointCount设置为等于0,并在每次随机数生成器返回中点值时递增,直到其达到10,000。由于三个线程生成随机数,因此调用Increment(Int32)方法以确保多个线程不会同时更新midpointCount。注意,锁还用于保护随机数生成器,并且CountdownEvent对象用于确保Main方法在三个线程之前不会完成执行。

using System;
using System.Threading;

public class Example
{
   const int LOWERBOUND = 0;
   const int UPPERBOUND = 1001;

   static Object lockObj = new Object();
   static Random rnd = new Random();
   static CountdownEvent cte;

   static int totalCount = 0;
   static int totalMidpoint = 0;
   static int midpointCount = 0;

   public static void Main()
   {
      cte = new CountdownEvent(1);
      // Start three threads. 
      for (int ctr = 0; ctr <= 2; ctr++) {
         cte.AddCount();
         Thread th = new Thread(GenerateNumbers);
         th.Name = "Thread" + ctr.ToString();
         th.Start();
      }
      cte.Signal();
      cte.Wait();
      Console.WriteLine();
      Console.WriteLine("Total midpoint values:  {0,10:N0} ({1:P3})",
                        totalMidpoint, totalMidpoint/((double)totalCount));
      Console.WriteLine("Total number of values: {0,10:N0}", 
                        totalCount);                  
   }

   private static void GenerateNumbers()
   {
      int midpoint = (UPPERBOUND - LOWERBOUND) / 2;
      int value = 0;
      int total = 0;
      int midpt = 0;

      do {
         lock (lockObj) {
            value = rnd.Next(LOWERBOUND, UPPERBOUND);
         }
         if (value == midpoint) { 
            Interlocked.Increment(ref midpointCount);
            midpt++;
         }
         total++;    
      } while (midpointCount < 10000);

      Interlocked.Add(ref totalCount, total);
      Interlocked.Add(ref totalMidpoint, midpt);

      string s = String.Format("Thread {0}:\n", Thread.CurrentThread.Name) +
                 String.Format("   Random Numbers: {0:N0}\n", total) + 
                 String.Format("   Midpoint values: {0:N0} ({1:P3})", midpt, 
                               ((double) midpt)/total);
      Console.WriteLine(s);
      cte.Signal();
   }
}
// The example displays output like the following:
//       Thread Thread2:
//          Random Numbers: 2,776,674
//          Midpoint values: 2,773 (0.100 %)
//       Thread Thread1:
//          Random Numbers: 4,876,100
//          Midpoint values: 4,873 (0.100 %)
//       Thread Thread0:
//          Random Numbers: 2,312,310
//          Midpoint values: 2,354 (0.102 %)
//       
//       Total midpoint values:      10,000 (0.100 %)
//       Total number of values:  9,965,084

下面的示例与上一个示例相似,不同之处在于它使用Task类而不是线程过程来生成50,000个随机中点整数。在此示例中,lambda表达式替换了GenerateNumbers线程过程,并且对Task.WaitAll方法的调用消除了对CountdownEvent对象的需求。

using System;
using System.Collections.Generic;
using System.Threading;
using System.Threading.Tasks;

public class Example
{
   const int LOWERBOUND = 0;
   const int UPPERBOUND = 1001;

   static Object lockObj = new Object();
   static Random rnd = new Random();

   static int totalCount = 0;
   static int totalMidpoint = 0;
   static int midpointCount = 0;

   public static void Main()
   {
      List<Task> tasks = new List<Task>();
      // Start three tasks. 
      for (int ctr = 0; ctr <= 2; ctr++) 
         tasks.Add(Task.Run( () => { int midpoint = (UPPERBOUND - LOWERBOUND) / 2;
                                     int value = 0;
                                     int total = 0;
                                     int midpt = 0;

                                     do {
                                        lock (lockObj) {
                                           value = rnd.Next(LOWERBOUND, UPPERBOUND);
                                        }
                                        if (value == midpoint) { 
                                           Interlocked.Increment(ref midpointCount);
                                           midpt++;
                                        }
                                        total++;    
                                     } while (midpointCount < 50000);

                                     Interlocked.Add(ref totalCount, total);
                                     Interlocked.Add(ref totalMidpoint, midpt);

                                     string s = String.Format("Task {0}:\n", Task.CurrentId) +
                                                String.Format("   Random Numbers: {0:N0}\n", total) + 
                                                String.Format("   Midpoint values: {0:N0} ({1:P3})", midpt, 
                                                              ((double) midpt)/total);
                                     Console.WriteLine(s); } ));

      Task.WaitAll(tasks.ToArray());
      Console.WriteLine();
      Console.WriteLine("Total midpoint values:  {0,10:N0} ({1:P3})",
                        totalMidpoint, totalMidpoint/((double)totalCount));
      Console.WriteLine("Total number of values: {0,10:N0}", 
                        totalCount);                  
   }
}
// The example displays output like the following:
//       Task 3:
//          Random Numbers: 10,855,250
//          Midpoint values: 10,823 (0.100 %)
//       Task 1:
//          Random Numbers: 15,243,703
//          Midpoint values: 15,110 (0.099 %)
//       Task 2:
//          Random Numbers: 24,107,425
//          Midpoint values: 24,067 (0.100 %)
//       
//       Total midpoint values:      50,000 (0.100 %)
//       Total number of values: 50,206,378

https://docs.microsoft.com/zh-cn/dotnet/api/system.threading.interlocked.increment?view=netcore-3.0

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