Awesome
IntX
IntX
is a C++11 port of IntX arbitrary precision Integer library with speed, about O(N * log N)
multiplication/division algorithms implementation. It provides all the basic arithmetic operations on Integers, comparing, bitwise shifting etc. It also allows parsing numbers in different bases and converting them to string, also in any base. The advantage of this library is its fast multiplication, division and from base/to base conversion algorithms. all the fast versions of the algorithms are based on fast multiplication of big Integers using Fast Hartley Transform which runs for O(N * log N * log log N)
time instead of classic O(N^2)
.
Code Example
Here is a sample of code which uses IntX
to calculate 42 in power 1048576 (which is 2^20 (1 shl 20)):
#include <iostream>
#include <Windows.h>
#include "Settings\IntXGlobalSettings.h"
#include "IntX.h"
void Calc()
{
uint32_t valA, valB;
double Delta;
valA = GetTickCount();
IntX::Pow(42, 1048576);
valB = GetTickCount();
Delta = (valB - valA) / 1000;
cout << Delta << endl;
}
int main()
{
Calc();
system("PAUSE");
TIntX::getGlobalSettings()->setMultiplyMode(MultiplyMode::mmClassic);
Calc();
return 0;
} // end main
First 'Calc()' call uses fast multiplication implementation (which is default),
second, classic one. On my machine (Windows 10, Intel Core i5 2.20 GHz,
8 GB RAM), Compiled with 64 bits, first call took 0 seconds while the second one
took 13 seconds.Resulting number has 1,702,101 digits.
Some other functions implemented internally by me are
IntegerSquareRoot (Integer SquareRoot)
Square
GCD (Greatest Common Divisor (HCF))
LCM (Least Common Multiple)
AbsoluteValue (Get Absolute Value of a Negative TIntX)
Bézouts Identity
InvMod (Modular Inverse)
Factorial
IntegerLogN (base, number) (Gets IntegerLog of a number using a specified base)
Ln (The natural logarithm)
Log10 (The base-10 logarithm)
LogN (Logarithm of a number for a specified base)
Random (Now Uses PcgRandom Instead of Mersemme Twister)
Modular Exponentiation (ModPow)
IsProbablyPrime (based on Miller Rabin Primality Test)
As you can see, IntX
implements all the standard arithmetic operators using operator overloading
so its usage is transparent for developers, like if you're working with usual Integers.
FHT and Calculations Precision
Internally IntX
library operates with floating-point numbers when multiplication using FHT (Fast Hartley Transform) is performed so at some point it stops working correctly and loses precision. Luckily, this unpleasant side-effects effects starts to appear when Integer size is about 2^28 bytes i.e. for really huge Integers. Anyway, to catch such errors some code was added, FHT multiplication result validity check into code -- it takes N last digits of each big Integer, multiplies them using classic approach and then compares last N digits of classic result with last N digits of FHT result (so it's kind of a simplified CRC check). If any inconsistency is found, then an
FhtMultiplicationException
is thrown; this check can be disabled using global settings.
Internal Representation and ToString() Performance
For a really huge Integer numbers (like 42 in power 1048576 above) ToString()
call can take quite some time to execute. This is because, internally IntX
big
Integers are stored as 2^32
-base number in UInt32
array and to generate decimal
string output it should be converted from 2^32
base to decimal base. Such digits
storage approach was chosen intentionally -- it makes ToString()
slower but uses
memory efficiently and makes primitive operations on digits faster than power of
10-base storage (which would make ToString()
work faster) and
usually computations are used more often than ToString()
.
Tested Enviroments:
Visual Studio 2015.
###License
This "Software" is Licensed Under MIT License (MIT)
.
Conclusion
Special Thanks to first of all, (Andriy Kozachuk) for creating the Original CSharp
version and Xor-el for various support offered.