From: Kahina Date: Fri, 23 Oct 2015 13:04:27 +0000 (+0200) Subject: MAJ de fihure 4 et quelqueS remarques faites par SIDER X-Git-Url: https://bilbo.iut-bm.univ-fcomte.fr/and/gitweb/kahina_paper1.git/commitdiff_plain/224b2f7a7a806831c78bd580084d6261e2674ae2 MAJ de fihure 4 et quelqueS remarques faites par SIDER --- diff --git a/paper.tex b/paper.tex index 5bef5e8..02f98de 100644 --- a/paper.tex +++ b/paper.tex @@ -54,7 +54,7 @@ \begin{frontmatter} -\title{Rapid solution of very high degree polynomials root finding using GPU} +\title{Parallel polynomial root finding using GPU} %% Group authors per affiliation: \author{Elsevier\fnref{myfootnote}} @@ -79,12 +79,14 @@ \address[mysecondaryaddress]{FEMTO-ST Institute, University of Franche-Compté } \begin{abstract} -Polynomials are mathematical algebraic structures that play a great role in science and engineering. But the process of solving them for high and large degrees is computationally demanding and still not solved. In this paper, we present the results of a parallel implementation of the Ehrlish-Aberth algorithm for the problem root finding for -high degree polynomials on GPU architectures (Graphics Processing Unit). The main result of this work is to be able to solve high and very large degree polynomials (up to 100000) very efficiently. We also compare the results with a sequential implementation and the Durand-Kerner method on full and sparse polynomials. +in this article we present a parallel implementation +of the Aberth algorithm for the problem root finding for +high degree polynomials on GPU architecture (Graphics +Processing Unit). \end{abstract} \begin{keyword} -root finding of polynomials, high degree, iterative methods, Ehrlish-Aberth, Durant-Kerner, GPU, CUDA, CPU , Parallelization +root finding of polynomials, high degree, iterative methods, Durant-Kerner, GPU, CUDA, CPU , Parallelization \end{keyword} \end{frontmatter} @@ -92,19 +94,14 @@ root finding of polynomials, high degree, iterative methods, Ehrlish-Aberth, Dur \linenumbers \section{The problem of finding roots of a polynomial} -Polynomials are mathematical algebraic structures used in science and engineering to capture physical phenomenons and to express any outcome in the form of a function of some unknown variables. Formally speaking, a polynomial $p(x)$ of degree \textit{n} having $n$ coefficients in the complex plane \textit{C} is : +Polynomials are algebraic structures used in mathematics that capture physical phenomenons and that express the outcome in the form of a function of some unknown variable. Formally speaking, a polynomial $p(x)$ of degree \textit{n} having $n$ coefficients in the complex plane \textit{C} and zeros $\alpha_{i},\textit{i=1,...,n}$ %%\begin{center} \begin{equation} - {\Large p(x)=\sum_{i=0}^{n}{a_{i}x^{i}}}. + {\Large p(x)=\sum_{i=0}^{n}{a_{i}x^{i}}=a_{n}\prod_{i=1}^{n}(x-\alpha_{i}), a_{0} a_{n}\neq 0}. \end{equation} %%\end{center} -The root finding problem consists in finding the values of all the $n$ values of the variable $x$ for which \textit{p(x)} is nullified. Such values are called zeroes of $p$. If zeros are $\alpha_{i},\textit{i=1,...,n}$ the $p(x)$ can be written as : -\begin{equation} - {\Large p(x)=a_{n}\prod_{i=1}^{n}(x-\alpha_{i}), a_{0} a_{n}\neq 0}. -\end{equation} - -The problem of finding a root is equivalent to that of solving a fixed-point problem. To see this, consider the fixed-point problem of finding the $n$-dimensional +The root finding problem consists in finding the values of all the $n$ values of the variable $x$ for which \textit{p(x)} is nullified. Such values are called zeroes of $p$. The problem of finding a root is equivalent to that of solving a fixed-point problem. To see this, consider the fixed-point problem of finding the $n$-dimensional vector $x$ such that \begin{center} $x=g(x)$