X-Git-Url: https://bilbo.iut-bm.univ-fcomte.fr/and/gitweb/kahina_paper1.git/blobdiff_plain/e74bf528b696246b88bb8a5542efc542fd09788a..1fc948028049feeeacad3808eedfb3b2acb32775:/paper.tex diff --git a/paper.tex b/paper.tex index 76b626e..20686d2 100644 --- a/paper.tex +++ b/paper.tex @@ -308,7 +308,7 @@ but we prefer the latter one because we can use it to improve the Ehrlich-Aberth method and find the roots of very high degrees polynomials. More details are given in Section ~\ref{sec2}. \subsection{Convergence Condition} -The convergence condition determines the termination of the algorithm. It consists in stopping from running the iterative function when the roots are sufficiently stable. We consider that the method converges sufficiently when: +The convergence condition determines the termination of the algorithm. It consists in stopping the iterative function when the roots are sufficiently stable. We consider that the method converges sufficiently when: \begin{equation} \label{eq:Aberth-Conv-Cond} @@ -319,7 +319,8 @@ The convergence condition determines the termination of the algorithm. It consis \section{Improving the Ehrlich-Aberth Method for high degree polynomials with exp.log formulation} \label{sec2} -The Ehrlich-Aberth method implementation suffers of overflow problems. This +With high degree polynomial, the Ehrlich-Aberth method implementation, +as well as the Durand-Kerner implement, suffers from overflow problems. This situation occurs, for instance, in the case where a polynomial having positive coefficients and a large degree is computed at a point $\xi$ where $|\xi| > 1$, where $|x|$ stands for the modolus of a complex $x$. Indeed, the limited number in the @@ -347,7 +348,7 @@ Using the logarithm (eq.~\ref{deflncomplex}) and the exponential (eq.~\ref{defex manipulate lower absolute values and the roots for large polynomial's degrees can be looked for successfully~\cite{Karimall98}. Applying this solution for the Ehrlich-Aberth method we obtain the -iteration function with logarithm: +iteration function with exponential and logarithm: %%$$ \exp \bigl( \ln(p(z)_{k})-ln(\ln(p(z)_{k}^{'}))- \ln(1- \exp(\ln(p(z)_{k})-ln(\ln(p(z)_{k}^{'})+\ln\sum_{i\neq j}^{n}\frac{1}{z_{k}-z_{j}})$$ \begin{equation} \label{Log_H2} @@ -393,7 +394,7 @@ There are many schemes for the simultaneous approximation of all roots of a give polynomial. Several works on different methods and issues of root finding have been reported in~\cite{Azad07, Gemignani07, Kalantari08, Skachek08, Zhancall08, Zhuall08}. However, Durand-Kerner and Ehrlich-Aberth methods are the most practical choices among them~\cite{Bini04}. These two methods have been extensively -studied for parallelization due to their intrinsics, i.e. the +studied for parallelization due to their intrinsics parallelism, i.e. the computations involved in both methods has some inherent parallelism that can be suitably exploited by SIMD machines. Moreover, they have fast rate of convergence (quadratic for the @@ -412,8 +413,11 @@ Optoelectronic Transpose Interconnection System (OTIS).The algorithms are mapped on an OTIS-2D torus using N processors. This solution needs N processors to compute N roots, which is not practical for solving polynomials with large degrees. -Until very recently, the literature doen not mention implementations able to compute the roots of -large degree polynomials (higher then 1000) and within small or at least tractable times. Finding polynomial roots rapidly and accurately is the main objective of our work. +%Until very recently, the literature did not mention implementations +%able to compute the roots of large degree polynomials (higher then +%1000) and within small or at least tractable times. + +Finding polynomial roots rapidly and accurately is the main objective of our work. With the advent of CUDA (Compute Unified Device Architecture), finding the roots of polynomials receives a new attention because of the new possibilities to solve higher degree polynomials in less time. In~\cite{Kahinall14} we already proposed the first implementation