From 33d8c5cc285296a345d562d9890cff0b6eac7fe6 Mon Sep 17 00:00:00 2001 From: couturie Date: Wed, 4 Nov 2015 10:05:53 -0500 Subject: [PATCH] new --- paper.tex | 12 +++++------- 1 file changed, 5 insertions(+), 7 deletions(-) diff --git a/paper.tex b/paper.tex index 384ff8b..f75c983 100644 --- a/paper.tex +++ b/paper.tex @@ -655,7 +655,6 @@ significant). -%%HIER END MY REVISIONS (SIDER) \section{Experimental study} \label{sec6} %\subsection{Definition of the used polynomials } @@ -724,14 +723,13 @@ on the GPU is faster than those implemented on the CPU. This is due to the GPU ability to compute the data-parallel functions faster than its CPU counterpart. However, the execution time for the -CPU (4 cores) implementation exceed 5,000 s for 250,000 degrees -polynomials, in counterpart the GPU implementation for the same -polynomials not reach 100 s, more than again, with an execution time -under to 2,500 s CPU (4 cores) implementation can resolve With the GPU -we can solve very high degrees polynomials very quickly up to degree +CPU (4 cores) implementation exceed 5,000s for 250,000 degrees +polynomials. In counterpart, the GPU implementation for the same +polynomials do not take more 100s. With the GPU +we can solve high degrees polynomials very quickly up to degree of 1,000,000. We can also notice that the GPU implementation are almost 47 faster then those implementation on the CPU (4 -cores). However the CPU(4 cores) implementation are almost 4 faster +cores). However the CPU (4 cores) implementation are almost 4 faster then his implementation on CPU (1 core). Furthermore, the number of iterations and the convergence precision are similar with the CPU and the GPU implementation. -- 2.39.5