Solving Quadratic Equations with XL on Parallel Architectures


Introduction

Multivariate quadratic systems can be solved using the XL algorithm: The system is extended by multiplying each equation with all monomials up to a certain degree \(D\); then the resulting system is linearized by treating all monomials as individual variables. The resulting large and sparse linear system \(B\) is solved; if \(D\) was chosen large enough, the kernel space becomes small enough so that we find a solution for the original quadratic system.

We are using Coppersmith's block variant of the Wiedemann algorithm (block Wiedemann: BW) for solving the sparse linear system. In the first step of BW, a sequence of matrices \(\{a^{(i)}\}, a_i=x B^{i+1} z\) for some matrices \(x\) and \(z\) is computed. In the second step, the block Berlekamp-Massey algorithm is used in order to compute the minimal polynomial \(\lambda\) of the sequence. Finally, the polynomial is evaluated at \(B\) giving a solution \(s\) such that \(Bs = 0\).

We describe this project and the implementation in detail in our paper "Solving Quadratic Equations with XL on Parallel Architectures" and in Chapter 4 of my thesis.

We used this code to solve Type III systems of the Fukuoka MQ Challenge. Here is more information on solving the challenges.

Source Code

To download the latest version of the software do the following:

The field and the size of the system must be defined at compile time, there are defines (Q, M and N) in the Makefile; currently, there are implementations for \(\mathbb{F}_2,\) \(\mathbb{F}_{16},\) and \(\mathbb{F}_{31}\); the code is in the gf/ directory. After compiling, you can run the program using:

./xl --all

The code generates a random system, prints the expected solution, and then uses XL to do the computation. A Fukuoka challenge can be loaded using

./xl --challenge FILE --all

By default, the code compiles with OpenMP; there are several implementations for MPI which you can choose in the Makefile:

Tweaking BW3

The code implements an unpublished idea to improve the runtime of the last step of BW which is not in the paper: Usually, when solving a large linear system, one is interested in a solution for all variables. However, for XL, we actually need only a solution for the original system (before it was extended and linearized). Therefore, we do not need to repeat the computations of the first BW step — but can just compute the solution from the sequence that was computed in the first step (using a tweak on how the sequence is computed). That reduces the cost of the last step to a marginal amount (e.g., 3 minutes out of 50 days in the Type III n=35 case).

Contact

Ruben Niederhagen, Tung Chou