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Maxim Saplin
Maxim Saplin

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C# `float` vs `double`: Performance Considerations

In C# there're 3 floating-point numeric types:

  • Single precision 32-bit/4-byte float
  • Double precision 64-bit/8-byte double
  • 128-bit/16-byte decimal

As long as you don't need extended precision, will 32-bit floats perform better? Intuition suggests that smaller types will be faster.

I tested this hypothesis with Mandelbrot calculation. I.e. I have implemented the same algorithm twice, the only difference being different variable types:

...

public struct Complex
{
  public double Real { get; set; }
  public double Imaginary { get; set; } 
  ...
}

...

public struct ComplexF
{
  public float Real { get; set; }
  public float Imaginary { get; set; }
  ...
}

...

// Part of calculation
private static int[] MandelbrotF()
{
  var output = new int[Height * Width];
  for (int h = 0, idx = 0; h < Height; h++, idx += Width)
  {
    float cy = MinYf + h * ScaleYf;
    for (int w = 0; w < Width; w++)
    {
      float cx = MinXf + w * ScaleXf;
      output[idx + w] = Mandelbrot_0F(new ComplexF(cx, cy));
    }
  }
  return output;
}
..
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Turns out, float is slower. Tested it many times on different machines and it was always behind double.

dotnet run -c Release

Platform Precision Avg Time (ms) StdDev (%) Sum
Apple M1 Pro double 392.70 0.14 78513425
Apple M1 Pro float 395.49 0.38 78520223
Intel® Core™ i5-8257U CPU @ 1.40GHz double 355.99 13.13 78513425
Intel® Core™ i5-8257U CPU @ 1.40GHz float 372.59 1.13 78520223
AMD 5900x double 185.80 0.97 78513425
AMD 5900x float 207.49 0.75 78520223

dotnet build -c Release

Platform Precision Avg Time (ms) StdDev (%) Sum
Apple M1 Pro double 392.42 0.11 78513425
Apple M1 Pro float 395.35 0.13 78520223
Intel® Core™ i5-8257U CPU @ 1.40GHz double 327.30 3.82 78513425
Intel® Core™ i5-8257U CPU @ 1.40GHz float 370.90 1.48 78520223
  • Tested with .NET 7.0.307
  • Sum column shows how different types produced different results (summarising resulting array elements)

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