From 165e7b481ee54e4e3f0be7828ca7b071aaa93888 Mon Sep 17 00:00:00 2001 From: couturie Date: Mon, 2 Nov 2015 14:13:41 -0500 Subject: [PATCH] new --- paper.tex | 8 +++++--- 1 file changed, 5 insertions(+), 3 deletions(-) diff --git a/paper.tex b/paper.tex index e4873d7..cf8c180 100644 --- a/paper.tex +++ b/paper.tex @@ -423,13 +423,15 @@ In~\cite{Kahinall14} we already proposed the first implementation of a root finding method on GPUs, that of the Durand-Kerner method. The main result showed that a parallel CUDA implementation is 10 times as fast as the sequential implementation on a single CPU for high degree -polynomials of 48000. In this paper we present a parallel implementation of Ehlisch-Aberth method on -GPUs, which details are discussed in the sequel. +polynomials of 48000. +%In this paper we present a parallel implementation of Ehrlich-Aberth +%method on GPUs for sparse and full polynomials with high degree (up +%to $1,000,000$). \section {A CUDA parallel Ehrlich-Aberth method} In the following, we describe the parallel implementation of Ehrlich-Aberth method on GPU -for solving high degree polynomials. First, the hardware and software of the GPUs are presented. Then, a CUDA parallel Ehrlich-Aberth method are presented. +for solving high degree polynomials (up to $1,000,000$). First, the hardware and software of the GPUs are presented. Then, the CUDA parallel Ehrlich-Aberth method is presented. \subsection{Background on the GPU architecture} A GPU is viewed as an accelerator for the data-parallel and -- 2.39.5