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[kahina_paper2.git] / paper.tex

diff --git a/paper.tex b/paper.tex
index 8203ed0ec7a6a605d6f076d48d51756fc13dbe1c..61f4778be34c625910d972a702a39ec8a72e0c81 100644 (file)
--- a/paper.tex
+++ b/paper.tex
@@ -21,7 +21,7 @@
 
 \title{Two parallel implementations of Ehrlich-Aberth algorithm for root-finding of polynomials on multiple GPUs with OpenMP and MPI}
 
 
 \title{Two parallel implementations of Ehrlich-Aberth algorithm for root-finding of polynomials on multiple GPUs with OpenMP and MPI}
 

-\author{\IEEEauthorblockN{Kahina Guidouche, Abderrahmane Sider }
+\author{\IEEEauthorblockN{Kahina Ghidouche, Abderrahmane Sider }

   \IEEEauthorblockA{Laboratoire LIMED\\
     Faculté des sciences exactes\\
     Université de Bejaia, 06000, Algeria\\
   \IEEEauthorblockA{Laboratoire LIMED\\
     Faculté des sciences exactes\\
     Université de Bejaia, 06000, Algeria\\


@@ -203,7 +203,7 @@ Using the logarithm  and the exponential operators, we can replace any multiplic
 The code is organized as kernels which are parts of code that are run
 on GPU devices. Algorithm~\ref{alg1-cuda} describes the CUDA
 implementation of the Ehrlich-Aberth on a GPU.  This algorithms starts
 The code is organized as kernels which are parts of code that are run
 on GPU devices. Algorithm~\ref{alg1-cuda} describes the CUDA
 implementation of the Ehrlich-Aberth on a GPU.  This algorithms starts

-by initializinf the polynomial and its derivative (line 1). The
+by initializing the polynomial and its derivative (line 1). The

 initialization of the roots is performed (line 2). Data are transfered
 from the CPU to the GPU (after allocation of the required memory on
 the GPU) (line 3). Then at each iteration, if the error is greater
 initialization of the roots is performed (line 2). Data are transfered
 from the CPU to the GPU (after allocation of the required memory on
 the GPU) (line 3). Then at each iteration, if the error is greater