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The classical Euclidean GCD Algorithm is known from ancient times. Given at input two integer numbers A_{o} and B_{o},A_{o}>B_{o}, it works at iterations called rounds implementing a single operation C_{n}= A_{n} mod B_{n} and submitting new pair (A_{n+1}, B_{n+1}) = (B_{n}, C_{n}). It is very easy implemented and programmed at any programming language. Its main disadvantage is a slow convergence. If we define a convergence coefficient as p=B/C then at most iterations of the Euclidean procedure it takes value less than 3. We can a little speed up the algorithm using a Lehmer’s idea to unite two or more iterations into one [1].

The extended version of the Euclidean algorithm is used to solve the Besout’s Equation, namely, given integers A,B find and , satisfying equation

Au+Bv=d, (1)

where d is the GCD of integers A and B.

Equation (1) allows us to find inverse elements by a given module, that is, to carry out the operation that has numerous applications in Number Theory and Cryptography. Namely, the module inversing is used to perform calculations in Galois Fields, generate keys for Cryptographic algorithms like RSA, DSS, carry out operations on Elliptic Curves over finite fields etc. An aacceleration of the GCD procedure can affect on a number of Cryptography algorithms.

We continue with a short description of other GCD algorithms. The binary GCD algorithm was first published by an Israeli physicist and programmer Josef Stein in 1967 [2] even it was known much earlier. His algorithm uses simpler arithmetic operations than the conventional Euclidean algorithm; it replaces division with arithmetic shifts, comparisons, and subtraction. It again consists of iterations at which given odd naturals A and B we count their difference C=|A-B| and reduce it dividing by 2 until C be odd. Then a new pair (B,C) is formed for the next iteration. The whole number of iterations is larger than in the Euclidean case but the binary algorithm outperforms the Euclidean in the operations at the algorithm step. In general, the Euclidean algorithm is preferable to the binary.

The next advantage in the area is due to Jonathan Sorenson [3], who invented the k-ary GCD algorithm that generalizes the Binary GCD algorithm. Independently, the k-ary algorithm was studied by K. Weber [4] and T. Jebelean [5].

Parameter k in this algorithm is chosen to be a comparatively small integer (usually, a power of 2 k=2s). Given at input integers A and B, co-prime to k, A>B, the algorithm searches for integers u and v such that

Au+Bv ≡ 0mod k (2)

counts integer C= |(Au+Bv)/k|, and divides C by GCD(C,k) to make it co-prime to k. By

Sorenson’s Theorem [3] integers u and v can be found satisfying |u|,|v|≤ √k so coefficient p=A/C xceeds √k/2. The main advantage of the k-ary algorithm is a lesser number of iterations against the Euclidean one. The larger k decreases the number of iterations but implies a longer calculation for searching s u and v. When k exceeds some optimal value, the algorithm’s speed begins to fall. The direct implementation of the k-ary algorithm loses the Euclidean one but if we calculate in advance intermediate parameters like inverses by module k and store them in RAM memory of a computer we can overcome the Euclidean algorithm up to 3-5 times at integers of length 2000 or more bits (the most popular size of integers used in Cryptography).

A disadvantage of the k-ary algorithm is that the final GCD obtained by the algorithm can differ from the origin GCD. Namely, it can contain extra factors accumulated during the computation. To remove them, an additional calculation with the Euclidean GCD algorithm is performed.

In 2016 S. Ishmukhametov introduced a new approximating GCD algorithm [6] that was a modification of Sorenson’s k-ary GCD algorithm. The main difference is in the choice of parameters u and v in equivalence (2). The new algorithms searches for a pair (u,v) satisfying two restrictions:

O__
__

|Au+Bv| takes a least possible value.

The search of required u and v is implemented using the Farey Series [6]. Taking M=k we can reach the reduction coefficient P=B/C exceeding k.

Let be the fraction part of a real

$\left|\frac{A/B-q}{k}\right|$

where q= AB-1 mod k. Farey’s Series are used to find an approximation fraction m/n with limited denominator n≤M for α with minimal discrepancy |α-m/n|. Then required (x,y) are defined as

(x,y)=(n,f(m,n,α)),

where f(m,n,α) is an integer expression of arguments written in brackets.

Experimental calculations show that at input of size 500 bits and larger this algorithm is up to 5 times faster than the Euclidean Algorithm and fast versions of the k-ary GCD Algorithm. Below we give an example of GCD calculation by the Approximating Algorithm at k=64 (M=k).

The calculation finishes in 4 steps, much faster than in case of Euclidean and Sorenson’s k-ary algorithms.

The extended version of the approximating GCD Algorithm was introduced in [7] by S.Ishmukahmetov, B.Mubarakov and Kamal Maad but a large amount of work was done by AlKhalidi Arkan Mohammed Ali who developed the theoretical idea of the algorithm, implemented it in the programming language C and performed experimental calculations [8,9]. Like as in the extended Euclidean Algorithm the algorithm consists of two stages. At the first stage it computes during the direct run the GCD d of input integers A and B. This stage can be performed by the Sorenson’s GCsD algorithm, or using the Approximating algorithm. Then, during the inverse computation, some equations are formed to be solved using the Chinese Remainder Theorem.

The common procedure is performed up to 5 times faster than in the extended Euclidean Algorithm at integers 500 bits and larger. So this algorithm is a perspective replacement to other GCD algorithms using in the current Cryptography applications.

The purpose of this paper was to advertise the new approximating k-ary GCD algorithm. The algorithm works in a lesser number of iterations but with an additional Farey procedure implementing at stages of the algorithm. The direct implementation of the algorithm loses the Euclidean procedure due to a large amount of work at a stage of the algorithm. But using preliminary computed parameters of the computation we were able to overcome Euclidean’s and Sorenson’s algorithms up to 5 times at integers of size more than 500 bits.

- Knuth D (1998) The Art of Computer Programming. 2. Link: https://bit.ly/3itivu2
- Stein J (1967) Computational problems associated with Racah algebra. Journal of Computational Physics 1: 397-405. Link: https://bit.ly/2D9bcrr
- Sorenson J (1994) Two fast GCD Algorithms. J Alg 16: 110-144. Link: https://bit.ly/31It9r1
- Weber K (1995) The accelerated integer GCD algorithm. ACM Trans Math Software 21: 1-12 . Link: https://bit.ly/2Z07GrY
- Jebelean T (1993) A Generalization of the Binary GCD Algorithm. Proc of Intern Symp on Symb and Algebr Comp (ISSAC’93) 111-116. Link: https://bit.ly/2VK2fv4
- Ishmukhametov ST (2016) An approximating k-ary GCD Algorithm. Lobachevskii Journal of Mathematics 37: 723-729. Link: https://bit.ly/2ZBEMNJ
- Ishmukhametov ST, Mubarakov BG, Al-Anni KM (2017) Calculation of Bezout’s Coefficients for the k-Ary Algorithm of Finding GCD, Russian Mathematics Allerton Press Inc 61: 26-33. Link: https://bit.ly/2O065vD
- Al-Khalidi Arkan M (2020) Effective Computations of Inverse by Module Elements with Approximating K-Ary GCD Algorithm by Ishmukhametov. IOP Journal of Physics 1350: 1-7. Link: https://bit.ly/2ZE3YTV
- Al-Khalidi Arkan M, Ishmukhametov ST (2020) Effective programming of the GCD procedure for natural numbers, Russian Mathematics 3-8.

© 2020 Ishmukhametov ST, et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

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