在一些简短的测试中，我发现两者的结合在我所谓的合理密集数学中会更好:

类型:<双[]>列表

时间:00:00:05.1861300

类型：列表<列表<double>>

时间:00:00:05.7941351

类型:double[行*列]

时间:00:00:06.0547118

运行代码:

int rows = 10000;
int columns = 10000;

IMatrix Matrix = new IMatrix(rows, columns);

Stopwatch stopwatch = new Stopwatch();
stopwatch.Start();


for (int r = 0; r < Matrix.Rows; r++)
    for (int c = 0; c < Matrix.Columns; c++)
        Matrix[r, c] = Math.E;

for (int r = 0; r < Matrix.Rows; r++)
    for (int c = 0; c < Matrix.Columns; c++)
        Matrix[r, c] *= -Math.Log(Math.E);


stopwatch.Stop();
TimeSpan ts = stopwatch.Elapsed;

Console.WriteLine(ts.ToString());

我真希望我们有一些顶尖的硬件加速矩阵类，就像。net团队用system . numbers . vectors类做的那样!

c#可能是最好的ML语言，只要在这方面多做一些工作!

简短的回答:

在。net List中<T>和Array<T>具有相同的速度/性能，因为在。net List中是Array的包装器。

再说一遍:List在里面是数组!在。net List中<T>是其他语言中的<T>数组列表。

详细说明在哪些情况下需要使用什么:

Array need to use: So often as possible. It's fast and takes smallest RAM range for same amount information. If you know exact count of cells needed If data saved in array < 85000 b (85000/32 = 2656 elements for integer data) If needed high Random Access speed List need to use: If needed to add cells to the end of list (often) If needed to add cells in the beginning/middle of the list (NOT OFTEN) If data saved in array < 85000 b (85000/32 = 2656 elements for integer data) If needed high Random Access speed LinkedList need to use: If needed to add cells in the beginning/middle/end of the list (often) If needed only sequential access (forward/backward) If you need to save LARGE items, but items count is low. Better do not use for large amount of items, as it's use additional memory for links. If you not sure that you need LinkedList -- YOU DON'T NEED IT. Just do not use it.

更多的细节:

更多细节:

https://stackoverflow.com/a/29263914/4423545

测量结果很好，但是根据您在内部循环中所做的具体操作，您将得到显著不同的结果。衡量你自己的情况。如果您正在使用多线程，那么这本身就不是一个简单的活动。

由于List<>在内部使用数组，因此基本性能应该是相同的。为什么这个列表可能会稍微慢一些，有两个原因:

要在列表中查找元素，调用list方法，该方法在底层数组中进行查找。所以你需要一个额外的方法调用。另一方面，编译器可能会识别出这一点，并优化“不必要的”调用。 如果编译器知道数组的大小，它可能会做一些特殊的优化，而对于一个未知长度的列表，它就不能这样做。如果列表中只有几个元素，这可能会带来一些性能改进。

要检查它是否对您有任何影响，最好将发布的计时函数调整为您计划使用的大小列表，并查看您的特殊情况的结果如何。

我担心在其他答案中发布的基准测试仍然会为编译器留下优化，消除或合并循环的空间，所以我写了一个:

使用不可预测的输入(随机) 运行计算结果并将结果打印到控制台 每次重复修改输入数据

结果是，直接数组的性能比访问封装在IList中的数组要好250%:

10亿次数组访问:4000毫秒 10亿次列表访问:10000毫秒 1亿个数组访问:350毫秒 1亿次列表访问:1000毫秒

代码如下:

static void Main(string[] args) {
  const int TestPointCount = 1000000;
  const int RepetitionCount = 1000;

  Stopwatch arrayTimer = new Stopwatch();
  Stopwatch listTimer = new Stopwatch();

  Point2[] points = new Point2[TestPointCount];
  var random = new Random();
  for (int index = 0; index < TestPointCount; ++index) {
    points[index].X = random.NextDouble();
    points[index].Y = random.NextDouble();
  }

  for (int repetition = 0; repetition <= RepetitionCount; ++repetition) {
    if (repetition > 0) { // first repetition is for cache warmup
      arrayTimer.Start();
    }
    doWorkOnArray(points);
    if (repetition > 0) { // first repetition is for cache warmup
      arrayTimer.Stop();
    }

    if (repetition > 0) { // first repetition is for cache warmup
      listTimer.Start();
    }
    doWorkOnList(points);
    if (repetition > 0) { // first repetition is for cache warmup
      listTimer.Stop();
    }
  }

  Console.WriteLine("Ignore this: " + points[0].X + points[0].Y);
  Console.WriteLine(
    string.Format(
      "{0} accesses on array took {1} ms",
      RepetitionCount * TestPointCount, arrayTimer.ElapsedMilliseconds
    )
  );
  Console.WriteLine(
    string.Format(
      "{0} accesses on list took {1} ms",
      RepetitionCount * TestPointCount, listTimer.ElapsedMilliseconds
    )
  );

}

private static void doWorkOnArray(Point2[] points) {
  var random = new Random();

  int pointCount = points.Length;

  Point2 accumulated = Point2.Zero;
  for (int index = 0; index < pointCount; ++index) {
    accumulated.X += points[index].X;
    accumulated.Y += points[index].Y;
  }

  accumulated /= pointCount;

  // make use of the result somewhere so the optimizer can't eliminate the loop
  // also modify the input collection so the optimizer can merge the repetition loop
  points[random.Next(0, pointCount)] = accumulated;
}

private static void doWorkOnList(IList<Point2> points) {
  var random = new Random();

  int pointCount = points.Count;

  Point2 accumulated = Point2.Zero;
  for (int index = 0; index < pointCount; ++index) {
    accumulated.X += points[index].X;
    accumulated.Y += points[index].Y;
  }

  accumulated /= pointCount;

  // make use of the result somewhere so the optimizer can't eliminate the loop
  // also modify the input collection so the optimizer can merge the repetition loop
  points[random.Next(0, pointCount)] = accumulated;
}

不要试图通过增加元素数量来增加容量。

性能

List For Add: 1ms
Array For Add: 2397ms

    Stopwatch watch;
        #region --> List For Add <--

        List<int> intList = new List<int>();
        watch = Stopwatch.StartNew();
        for (int rpt = 0; rpt < 60000; rpt++)
        {
            intList.Add(rand.Next());
        }
        watch.Stop();
        Console.WriteLine("List For Add: {0}ms", watch.ElapsedMilliseconds);
        #endregion

        #region --> Array For Add <--

        int[] intArray = new int[0];
        watch = Stopwatch.StartNew();
        int sira = 0;
        for (int rpt = 0; rpt < 60000; rpt++)
        {
            sira += 1;
            Array.Resize(ref intArray, intArray.Length + 1);
            intArray[rpt] = rand.Next();

        }
        watch.Stop();
        Console.WriteLine("Array For Add: {0}ms", watch.ElapsedMilliseconds);

        #endregion