## Monday, September 21, 2015

### Repeated Squaring Method for Modular Exponentiation

Previously on Modular Exponentiation we learned about Divide and Conquer approach to finding the value of $B^P \:\%\: M$. In that article, which is recursive. I also mentioned about an iterative algorithm that finds the same value in same complexity, only faster due to the absence of recursion overhead. We will be looking into that faster algorithm on this post today.

Make sure you know about Bit Manipulation before proceeding.

## Problem

Given three positive integers $B, P$ and $M$, find the value of $B^P \:\%\: M$.

For example, $B=2$, $P=5$ and $M=7$, then $B^P \:\%\: M = 2^5 \: \% \: 7 = 32 \: \% \: 7 = 4$.

## Repeated Squaring Method

Repeated Squaring Method (RSM) takes the advantage of the fact that $A^x \times A^y = A^{x+y}$.

Now, we know that any number can be written as the sum of powers of $2$. Just convert the number to Binary Number System. Now for each position $i$ for which binary number has $1$ in it, add $2^i$ to the sum.

For example, $(19)_{10} = (10011)_2 = ( 2^4 + 2^1 + 2^0)_{10} = (16 + 2 + 1 )_{10}$

Therefore, in equation $B^P$, we can decompose $P$ to the sum of powers of $2$.

So let's say, $P = 19$, then $B^{19} = B^{2^4 + 2^1 + 2^0} = B^{16+2+1} = B^{16} \times B^2 \times B^1$.

This is the main concept for repeated squaring method. We decompose the value $P$ to binary, and then for each position $i$ (we start from 0 and loop till the highest position at binary form of $P$) for which binary of $P$ has $1$ in $i_{th}$ position, we multiply $B^{2^i}$ to result.

## Code

Here is the code for RSM. The Explanation is below the code.
int bigmod ( int b, int p, int m ) {
int res = 1 % m, x = b % m;
while ( p ) {
if ( p & 1 ) res = ( res * x ) % m;
x = ( x * x ) % m;
p >>= 1;
}
return res;
}

### Explanation

At line $1$, we have the parameters. We simply send the value of $B$, $P$ and $M$ to this function, and it will return the required result.

At line $2$, we initiate some variables. $res$ is the variable that will hold our result. It contains the value $1$ initially. We will multiply $b^{2^i}$ with result to find $b^p$. $x$ is temporary variable that initially contains the value $b^{2^0} = b^1 = b$.

Now, from line $3$ the loop starts. This loop runs until $p$ becomes $0$. Huh? Why is that? Keep reading.

At line $4$ we first check whether the first bit of $p$ is on or not. If it is on, then it means that we have to multiply $b^{2^i}$ to our result. $x$ contains that value, so we multiply $x$ to $res$.

Now line $5$ and $6$ are crucial to the algorithm. Right now, $x$ contains the value of $b^{2^0}$ and we are just checking the $0_{th}$ position of $p$ at each step. We need to update our variables such that they keep working for positions other than $0$.

First, we update the value of $x$. $x$ contains the value of $b^{2^i}$. On next iteration, we will be working with position $i+1$. So we need to update $x$ to hold $b^{2^{i+1}}$.

$b^{2^{i+1}} = b^{2^i \times 2^1} = b ^ {2^i \times 2} = b^{2^i + 2^i} = b^{2^i} \times b^{2^i} = x \times x$.

Hence, new value of $x$ is $x \times x$. We make this update at line $5$.

Now, at each step we are checking the $0_{th}$ position of $p$. But next we need to check the $1_{st}$ position of $p$ in binary. Instead of checking $1_{st}$ position of $p$, what we can do is shift $p$ $1$ time towards right. Now, checking $0_{th}$ position of $p$ is same as checking $1_{st}$ position. We do this update at line $6$.

These two lines ensures that our algorithm works on each iteration. When $p$ becomes $0$, it means there is no more bit to check, so the loop ends.

### Complexity

Since there cannot be more than $log_{2}(P)$ bits in $P$, the loop at line $3$ runs at most $log_{2}(P)$ times. So the complexity is $log_{2}(P)$.

## Conclusion

RSM is significantly faster than D&C approach due to lack of recursion overhead. Hence, I always use this method when I have to find Modular Exponentiation.

The code may seem a little confusing, so feel free to ask questions.

When I first got my hands on this code, I had no idea how it worked. I found it in a forum with a title, "Faster Approach to Modular Exponentiation". Since then I have been using this code.

## Resources

1. forthrigth48 - Modular Exponentiation
2. forthright48 - Bit Manipulation
3. algorithmist - Repeated Squaring
4. Wiki - Exponentiation by Squaring