Sdcb.Arithmetic
Sdcb.Arithmetic
is a modern .NET
library that can PInvoke to gmp
and mpfr
, that enable both high performance and best .NET convenience.
Known classes in Sdcb.Arithmetic
:
Class | Native name | Library |
---|---|---|
GmpInteger | mpz_t | Sdcb.Arithmetic.Gmp |
GmpFloat | mpf_t | Sdcb.Arithmetic.Gmp |
GmpRational | mpq_t | Sdcb.Arithmetic.Gmp |
GmpRandom | gmp_randstate_t | Sdcb.Arithmetic.Gmp |
MpfrFloat | mpfr_t | Sdcb.Arithmetic.Mpfr |
NuGet Packages
libgmp
mpfr
Question - Why not linux-64 can't run in my linux?
The linux-x64
package is compiled using vcpkg
in Ubuntu 22.04, so it may not run in other linux distributions.
If you want to run in other linux distributions, you can compile it yourself, or install it using apt
or yum
or other package manager.
This is the all native dynamic library name in case you wondering(defined in GmpNativeLoader.cs
and MpfrNativeLoader.cs
):
OS | gmp dynamic lib | mpfr dynamic lib |
---|---|---|
Windows | gmp-10.dll | mpfr-6.dll |
Linux | libgmp.so.10 | libmpfr.so.6 |
MacOS | libgmp.10.dylib | libmpfr.6.dylib |
Others | gmp.10 | mpfr.6 |
Examples
Sdcb.Arithmetic.Gmp
:
Calculate 1,000,000 length of π using // Install NuGet package: Sdcb.Arithmetic.Gmp
// Install NuGet package: Sdcb.Arithmetic.Gmp.runtime.win-x64(for windows)
using Sdcb.Arithmetic.Gmp;
Console.WriteLine(CalcPI().ToString("N1000000"));
GmpFloat CalcPI(int inputDigits = 1_000_000)
{
const double DIGITS_PER_TERM = 14.1816474627254776555; // = log(53360^3) / log(10)
int DIGITS = (int)Math.Max(inputDigits, Math.Ceiling(DIGITS_PER_TERM));
uint PREC = (uint)(DIGITS * Math.Log2(10));
int N = (int)(DIGITS / DIGITS_PER_TERM);
const int A = 13591409;
const int B = 545140134;
const int C = 640320;
const int D = 426880;
const int E = 10005;
const double E3_24 = (double)C * C * C / 24;
using PQT pqt = ComputePQT(0, N);
GmpFloat pi = new(precision: PREC);
// pi = D * sqrt((mpf_class)E) * PQT.Q;
pi.Assign(GmpFloat.From(D, PREC) * GmpFloat.Sqrt((GmpFloat)E, PREC) * (GmpFloat)pqt.Q);
// pi /= (A * PQT.Q + PQT.T);
GmpFloat.DivideInplace(pi, pi, GmpFloat.From(A * pqt.Q + pqt.T, PREC));
return pi;
PQT ComputePQT(int n1, int n2)
{
int m;
if (n1 + 1 == n2)
{
PQT res = new()
{
P = GmpInteger.From(2 * n2 - 1)
};
GmpInteger.MultiplyInplace(res.P, res.P, 6 * n2 - 1);
GmpInteger.MultiplyInplace(res.P, res.P, 6 * n2 - 5);
GmpInteger q = GmpInteger.From(E3_24);
GmpInteger.MultiplyInplace(q, q, n2);
GmpInteger.MultiplyInplace(q, q, n2);
GmpInteger.MultiplyInplace(q, q, n2);
res.Q = q;
GmpInteger t = GmpInteger.From(B);
GmpInteger.MultiplyInplace(t, t, n2);
GmpInteger.AddInplace(t, t, A);
GmpInteger.MultiplyInplace(t, t, res.P);
// res.T = (A + B * n2) * res.P;
if ((n2 & 1) == 1) GmpInteger.NegateInplace(t, t);
res.T = t;
return res;
}
else
{
m = (n1 + n2) / 2;
PQT res1 = ComputePQT(n1, m);
using PQT res2 = ComputePQT(m, n2);
GmpInteger p = res1.P * res2.P;
GmpInteger q = res1.Q * res2.Q;
// t = res1.T * res2.Q + res1.P * res2.T
GmpInteger.MultiplyInplace(res1.T, res1.T, res2.Q);
GmpInteger.MultiplyInplace(res1.P, res1.P, res2.T);
GmpInteger.AddInplace(res1.T, res1.T, res1.P);
res1.P.Dispose();
res1.Q.Dispose();
return new PQT
{
P = p,
Q = q,
T = res1.T,
};
}
}
}
public ref struct PQT
{
public GmpInteger P;
public GmpInteger Q;
public GmpInteger T;
public readonly void Dispose()
{
P?.Dispose();
Q?.Dispose();
T?.Dispose();
}
}
Technical notes
Why choosing struct in class design instead of raw memory IntPtr design?
-
(1)
Struct in class
design:class GmpInteger { public readonly Mpz_t Raw; public unsafe void DoWork() { fixed (Mpz_t* ptr = &Raw) { GmpLib.__dowork((IntPtr)ptr); } } } struct Mpz_t { public int A, B; public IntPtr Limbs; }
-
(2)
Raw memory IntPtr
design:class GmpInteger : IDisposable { public readonly IntPtr Raw; public unsafe GmpInteger() { Raw = Marshal.AllocHGlobal(sizeof(Mpz_t)); } public void DoWork() { GmpLib.__dowork(Raw); } public void Dispose() { Marshal.FreeHGlobal(Raw); } }
Here is some benchmark I tested for both
DoWork
senario andinitialize-dispose
senario:Details:
- init & dispose combines following actions:
- allocating struct memory
- calling
mpz_init
- calling
mpz_free
- free the memory
- Measure the operations-per-seconds, higher ops is better
- dowork contains following actions:
- create a
GmpFloat
to1.5
with precision=1000(v = 1, a = 1.5) - Calling
MultiplyInplace
(v *= a)10*1024*1024
times - Measure the duration, lower is better
- create a
Here is the tested results in my laptop:
case/senario init & dispose dowork Struct in class 82,055,792 ops 1237ms Raw memory IntPtr 15,543,619 ops 1134ms As you can see, raw memory IntPtr design will benifits ~8.33% faster in
dowork
senario above, but struct in class design will be 5.2x faster ininit & dispose
senario.Finally I choosed the struct in class design, here is some existing Raw memory IntPtr design work if you also wants to check or test:
- branch: https://github.com/sdcb/Sdcb.Arithmetic/tree/feature/gmp-raw-ptr
- nuget-package: https://www.nuget.org/packages/Sdcb.Arithmetic.Gmp/1.0.10-preview.12
Struct in class performance results environment:
- commit: https://github.com/sdcb/Sdcb.Arithmetic/tree/976d4271c487a554be936cf56ed55f2b1314042e
- nuget-package: https://www.nuget.org/packages/Sdcb.Arithmetic.Gmp/1.0.10-preview.11
In the future,
Raw memory IntPtr
design can be pick-up if a handy, good performance memory allocator was found. - init & dispose combines following actions: