Possible Duplicate:
Are doubles faster than floats in c#?
I wrote simple benchmark to check how much performance i can get changing double
datatype to float
in my application. Here is my code:
// my form:
// one textbox: textbox1 (MultiLine property set to true)
// one button: button1 with event button1_Click
private void button1_Click(object sender, EventArgs e)
{
int num = 10000000;
float[] floats1 = new float[num];
float[] floats2 = new float[num];
float[] floatsr = new float[num]; // array for results
double[] doubles1 = new double[num];
double[] doubles2 = new double[num];
double[] doublesr = new double[num]; // array for results
Stopwatch stw = new Stopwatch();
log("Preparing data");
Random rnd = new Random();
stw.Start();
for (int i = 0; i < num; i++)
{
floats1[i] = NextFloat(rnd);
floats2[i] = NextFloat(rnd);
doubles1[i] = rnd.NextDouble();
doubles2[i] = rnd.NextDouble();
}
stw.Stop();
log(stw.Elapsed.TotalMilliseconds.ToString()+"ms");
stw.Reset();
log("");
stw.Start();
for (int i = 0; i <# i++)
{
floatsr[i] = floats1[i] * floats2[i];
}
stw.Stop();
log("Multiplying floats: " + stw.Elapsed.TotalMilliseconds.ToString() + "ms");
stw.Reset();
stw.Start();
for (int i = 0; i < num; i++)
{
doublesr[i] = doubles1[i] * doubles2[i];
}
stw.Stop();
log("Multiplying doubles: " + stw.Elapsed.TotalMilliseconds.ToString() + "ms");
stw.Reset();
stw.Start();
for (int i = 0; i < num; i++)
{
floatsr[i] = floats1[i] / floats2[i];
}
stw.Stop();
log("Dividing floats: " + stw.Elapsed.TotalMilliseconds.ToString() + "ms");
stw.Reset();
stw.Start();
for (int i = 0; i < num; i++)
{
doublesr[i] = doubles1[i] / doubles2[i];
}
stw.Stop();
log("Dividing doubles: " + stw.Elapsed.TotalMilliseconds.ToString() + "ms");
stw.Reset();
}
private void log(string text)
{
textBox1.Text = textBox1.Text + text + Environment.NewLine;
}
// I found that function somewhere on stackoverflow
static float NextFloat(Random random)
{
double mantissa = (random.NextDouble() * 2.0) - 1.0;
double exponent = Math.Pow(2.0, random.Next(-126, 128));
return (float)(mantissa * exponent);
}
I got results like this (release, no debug, Intel Mobile Core Duo T2500 2.0GHz 2MB CPU):
Preparing data 5275,6862ms
Multiplying floats: 442,7865ms
Multiplying doubles: 169,4028ms
Dividing floats: 550,7052ms
Dividing doubles: 164,1607ms
I was suprised, that operations on double
are almost 3 times faster than operations on float
. I searched for "double float" here, and i found this:
Is using double faster than float?
Best answer is focused on CPU architecture, but I cant agree with that.
I suspect that something else is causing low performance on floats, because my CPU with Intel SSE should be able to multiply or divide 4 floats at once (packed floating point instructions), or 2 doubles at once. So floats should be faster.
Maybe compiler (or clr in .net) is optimizing memory usage somehow?
Is there any way to optimize it and make float faster?
Please don't report duplicate, i saw other questions and they not satisfying me.
My results after changing method for generating floats now look fine (suggested by Servy):
Preparing data 1367,0678ms
Multiplying floats: 109,8742ms
Multiplying doubles: 149,9555ms
Dividing floats: 167,0079ms
Dividing doubles: 168,6821ms
It has to do with how you generated the random numbers. Multiplying and dividing floating point numbers are not all the same; the actual values of those numbers matter. In the case of floats, you're populating a value over a fairly large range. If you create your floats such that they are between 0 and 1, just like the doubles, then it comes out more like you'd expect. Just change
NextFloat
to be this:I just ran a few tests, and with that change the floats were 33% faster at multiplication.
Of course, this is just the easiest way to make the comparison "fair". To get a better understanding of how floats really compare to doubles you'd want to generate random floats and doubles each between the full range of the respective types, or better yet, both holding values representing the type of data your program will be using.
GPU operations on floats are still faster, in some cases by far, because they have 32-bit float hardware.
Your x86 (or x86_64) architecture CPU doesn't have 32-bit support in the math coprocessor. Or even 64-bit support. The x87 floating-point unit uses 80-bit arithmetic.
Now, modern x86 CPUs do have SIMD instructions (MMX, SSE, AVX) with hardware support for 32-bit and 64-bit floating-point operations, with much higher performance -- if you can do everything in the SIMD unit. Moving data between SIMD and the FPU will kill performance.
And .NET doesn't use MMX or SSE or AVX, as of the current version. You might try Mono, which provides intrinsic methods that JIT-compile to SIMD instructions. Or you might use native code for the most performance-sensitive parts, since modern C++ compilers not only allow SIMD usage, but can auto-vectorize ordinary-looking code into SIMD instructions.