function is the destination array, the second is the source array and the third
is the number of elements to copy (exprimed in bytes).
-Now the GPU contains the data needed to perform the addition. In sequential such
-addition is achieved out with a loop on all the elements. With a GPU, it is
-possible to perform the addition of all elements of the arrays in parallel (if
-the number of blocks and threads per blocks is sufficient). In
+Now that the GPU contains the data needed to perform the addition. In sequential
+such addition is achieved out with a loop on all the elements. With a GPU, it
+is possible to perform the addition of all elements of the arrays in parallel
+(if the number of blocks and threads per blocks is sufficient). In
Listing\ref{ch2:lst:ex1} at the beginning, a simple kernel,
called \texttt{addition} is defined to compute in parallel the summation of the
-two arrays. With CUDA, a kernel starts with the keyword \texttt{\_\_global\_\_}
-which indicates that this kernel can be call from the C code. The first
-instruction in this kernel is used to computed the \texttt{tid} which
-representes the thread index. This thread index is computed according to the
-values of the block index (it is a variable of CUDA
-called \texttt{blockIdx\index{CUDA~keywords!blockIdx}}). Blocks of threads can
+two arrays. With CUDA, a kernel starts with the keyword \texttt{\_\_global\_\_} \index{CUDA~keywords!\_\_shared\_\_}
+which indicates that this kernel can be called from the C code. The first
+instruction in this kernel is used to compute the variable \texttt{tid} which
+represents the thread index. This thread index\index{thread index} is computed
+according to the values of the block index (it is a variable of CUDA
+called \texttt{blockIdx}\index{CUDA~keywords!blockIdx}). Blocks of threads can
be decomposed into 1 dimension, 2 dimensions or 3 dimensions. According to the
dimension of data manipulated, the appropriate dimension can be useful. In our
example, only one dimension is used. Then using notation \texttt{.x} we can
