如何：加速小型迴圈主體
當 Parallel.For 迴圈有小型的主體時，其執行速度可能會比同等的循序迴圈更慢，例如 C# 中的 for 迴圈和 Visual Basic 中的 For 迴圈。 效能較慢的起因是分割資料時相關的負擔，以及在每次迴圈反覆運算上叫用委派的成本。 為了解決這類情況，Partitioner 類別提供 Partitioner.Create 方法，可讓您提供循序迴圈給委派主體，讓每個資料分割只叫用一次委派，而不會每個反覆項目叫用一次。 如需詳細資訊，請參閱 PLINQ 和 TPL 的自訂 Partitioner。
範例
using System;
using System.Collections.Concurrent;
using System.Linq;
using System.Threading;
using System.Threading.Tasks;
class Program
{
static void Main()
{
// Source must be array or IList.
var source = Enumerable.Range(0, 100000).ToArray();
// Partition the entire source array.
var rangePartitioner = Partitioner.Create(0, source.Length);
double[] results = new double[source.Length];
// Loop over the partitions in parallel.
Parallel.ForEach(rangePartitioner, (range, loopState) =>
{
// Loop over each range element without a delegate invocation.
for (int i = range.Item1; i < range.Item2; i++)
{
results[i] = source[i] * Math.PI;
}
});
Console.WriteLine("Operation complete. Print results? y/n");
char input = Console.ReadKey().KeyChar;
if (input == 'y' || input == 'Y')
{
foreach(double d in results)
{
Console.Write("{0} ", d);
}
}
}
}
Imports System.Threading.Tasks
Imports System.Collections.Concurrent
Module PartitionDemo
Sub Main()
' Source must be array or IList.
Dim source = Enumerable.Range(0, 100000).ToArray()
' Partition the entire source array.
' Let the partitioner size the ranges.
Dim rangePartitioner = Partitioner.Create(0, source.Length)
Dim results(source.Length - 1) As Double
' Loop over the partitions in parallel. The Sub is invoked
' once per partition.
Parallel.ForEach(rangePartitioner, Sub(range, loopState)
' Loop over each range element without a delegate invocation.
For i As Integer = range.Item1 To range.Item2 - 1
results(i) = source(i) * Math.PI
Next
End Sub)
Console.WriteLine("Operation complete. Print results? y/n")
Dim input As Char = Console.ReadKey().KeyChar
If input = "y"c Or input = "Y"c Then
For Each d As Double In results
Console.Write("{0} ", d)
Next
End If
End Sub
End Module
在此範例中示範的方法適用於迴圈執行最少量工作的情況。 當工作變得更運算密集時，藉由使用 For 或 ForEach 迴圈與預設 Partitioner，您可能會取得相同或更高的效能。
