并行排序算法.doc

并行排序算法先简单说一下给的A，B，C 三种算法(见上面引用的那篇博客)，A算法将耗时的平方和开平方计算放到比较函数中，导致Array.Sort 时，每次亮亮比较都要执行平方和开平方计算，其平均算法复杂度为 O(nlog2n) 。 而B 将平方和开平方计算提取出来，算法复杂度降低到 O(n) ，这也就是为什么B比A效率要高很多的缘故。C 和 B 相比，将平方函数替换成了 x*x ，由于少了远程函数调用和Pow函数本身的开销，效率有提高了不少。我在C的基础上编写了D算法，D算法采用并行计算技术，在我的双核笔记本电脑上数据量比较大的情况下，其排序效率较C要提高30%左右。下面重点介绍这个并行排序算法。算法思路其实很简单，就是将要排序的数组按照处理器数量等分成若干段，然后用和处理器数量等同的线程并行对各个小段进行排序，排序结束和，再在单一线程中对这若干个已经排序的小段进行归并排序，最后输出完整的排序结果。考试大考虑到和.Net 2.0 兼容，没有用微软提供的并行库，而是用多线程来实现。下面是测试结果：n A B C D32768 0.7345 0.04122 0.0216 0.025465535 1.5464 0.08863 0.05139 0.05149131072 3.2706 0.1858 0.118 0.108262144 6.8423 0.4056 0.29586 0.21849524288 15.0342 0.9689 0.7318 0.49061048576 31.6312 1.9978 1.4646 1.0742097152 66.9134 4.1763 3.0828 2.3095从测试结果上看，当要排序的数组长度较短时，并行排序的效率甚至还没有不进行并行排序高，这主要是多线程的开销造成的。当数组长度增大到25万以上时，并行排序的优势开始体现出来，随着数组长度的增长，排序时间最后基本稳定在但线程排序时间的 74% 左右，其中并行排序的消耗大概在50%左右，归并排序的消耗在 14%左右。由此也可以推断，如果在4CPU的机器上，其排序时间最多可以减少到单线程的 14 + 25 = 39%。8 CPU 为 14 + 12.5 = 26.5%。目前这个算法在归并算法上可能还有提高的余地，如果哪位高手能够进一步提高这个算法，不妨贴出来一起交流交流。下面分别给出并行排序和归并排序的代码：并行排序类 ParallelSortParalletsort 类是一个通用的泛型，调用起来非常简单，下面给一个简单的int型数组的排序示例：class IntComparer : IComparer IComparer Members #region IComparer Memberspublic int Compare( int x, int y)return x.CompareTo(y);#endregionpublic void SortInt( int array)Sort.ParallelSort parallelSort = new Sort.ParallelSort ();parallelSort.Sort(array, new IntComparer();只要实现一个T类型两两比较的接口，然后调用ParallelSort 的 Sort 方法就可以了，是不是很简单?下面是 ParallelSort类的代码using System;using System.Collections.Generic;using System.Linq;using System.Text;using System.Threading;namespace Sort/*/ / ParallelSort/public class ParallelSort enum StatusIdle = 0 ,Running = 1 ,Finish = 2 ,class ParallelEntitypublic Status Status;public T Array;public IComparer Comparer;public ParallelEntity(Status status, T array, IComparer comparer)Status = status;Array = array;Comparer = comparer;private void ThreadProc(Object stateInfo)ParallelEntity pe = stateInfo as ParallelEntity;lock (pe)pe.Status = ParallelSort .Status.Running;Array.Sort(pe.Array, pe.Comparer);pe.Status = ParallelSort .Status.Finish;public void Sort(T array, IComparer comparer)/ Calculate process countint processorCount = Environment.ProcessorCount;/ If array.Length too short, do not use Parallel sortif (processorCount = 1 | array.Length processorCount)Array.Sort(array, comparer);return ;/ Split arrayParallelEntity partArray = new ParallelEntityprocessorCount;int remain = array.Length;int partLen = array.Length / processorCount;/ Copy data to splited arrayfor ( int i = 0 ; i processorCount; i + )if (i = processorCount - 1 )partArrayi = new ParallelEntity(Status.Idle, new Tremain, comparer);elsepartArrayi = new ParallelEntity(Status.Idle, new TpartLen, comparer);remain -= partLen;Array.Copy(array, i * partLen, partArrayi.Array, 0 , partArrayi.Array.Length);/ Parallel sortfor ( int i = 0 ; i processorCount - 1 ; i + )ThreadPool.QueueUserWorkItem( new WaitCallback(ThreadProc), partArrayi);ThreadProc(partArrayprocessorCount - 1 );/ Wait all threads finishfor ( int i = 0 ; i processorCount; i + )while ( true )lock (partArrayi)if (partArrayi.Status = ParallelSort .Status.Finish)break ;Thread.Sleep( 0 );/ Merge sortMergeSort mergeSort = new MergeSort ();List source = new List (processorCount);foreach (ParallelEntity pe in partArray)source.Add(pe.Array);mergeSort.Sort(array, source, comparer);多路归并排序类 MergeSortusing System;using System.Collections.Generic;using System.Linq;using System.Text;namespace Sort/*/ / MergeSort/public class MergeSort public void Sort(T destArray, List source, IComparer comparer)/ Merge Sortint mergePoint = new int source.Count;for ( int i = 0 ; i source.Count; i + )mergePointi = 0 ;int index = 0 ;while (index destArray.Length)int min = - 1 ;for ( int i = 0 ; i = sourcei.Length)continue ;if (min 0 )min = i;elseif (comparer.Compare(sourceimergePointi, sourceminmergePointmin) 0 )min = i;if (min 0 )continue ;destArrayindex + = sourceminmergePointmin;mergePointmin + ;主函数及测试代码 在蛙蛙池塘 代码基础上修改using System;using System.Collections.Generic;using System.Diagnostics;namespace Vector4Testpublic class Vectorpublic double W;public double X;public double Y;public double Z;public double T;internal class VectorComparer : IComparer public int Compare(Vector c1, Vector c2)if (c1 = null | c2 = null )throw new ArgumentNullException( Both objects must not be null );double x = Math.Sqrt(Math.Pow(c1.X, 2 )+ Math.Pow(c1.Y, 2 )+ Math.Pow(c1.Z, 2 )+ Math.Pow(c1.W, 2 );double y = Math.Sqrt(Math.Pow(c2.X, 2 )+ Math.Pow(c2.Y, 2 )+ Math.Pow(c2.Z, 2 )+ Math.Pow(c2.W, 2 );if (x y)return 1 ;else if (x y)return - 1 ;elsereturn 0 ;internal class VectorComparer2 : IComparer public int Compare(Vector c1, Vector c2)if (c1 = null | c2 = null )throw new ArgumentNullException( Both objects must not be null );if (c1.T c2.T)return 1 ;else if (c1.T c2.T)return - 1 ;elsereturn 0 ;internal class Programprivate static void Print(Vector vectors)/ foreach (Vector v in vectors)/ / Console.WriteLine(v.T);/ private static void Main( string args)Vector vectors = GetVectors();Console.WriteLine( string .Format( n = 0 , vectors.Length);Stopwatch watch1 = new Stopwatch();watch1.Start();A(vectors);watch1.Stop();Console.WriteLine( A sort time: + watch1.Elapsed);Print(vectors);vectors = GetVectors();watch1.Reset();watch1.Start();B(vectors);watch1.Stop();Console.WriteLine( B sort time: + watch1.Elapsed);Print(vectors);vectors = GetVectors();watch1.Reset();watch1.Start();C(vectors);watch1.Stop();Console.WriteLine( C sort time: + watch1.Elapsed);Print(vectors);vectors = GetVectors();watch1.Reset();watch1.Start();D(vectors);watch1.Stop();Console.WriteLine( D sort time: + watch1.Elapsed);Print(vectors);Console.ReadKey();private static Vector GetVectors()int n = 1 21 ;Vector vectors = new Vectorn;Random random = new Random();for ( int i = 0 ; i n; i + )vectorsi = new Vector();vectorsi.X = random.NextDouble();vectorsi.Y = random.NextDouble();vectorsi.Z = random.NextDouble();vectorsi.W = random.NextDouble();return vectors;private static void A(Vector vectors)Array.Sort(vectors, new VectorComparer();private static void B(Vector vectors)int n = vectors.Length;for ( int i =