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elvis
2023-08-26 21:14:54 +02:00
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@ -307,11 +307,11 @@ The class \texttt{Stencil} holds both the parallel implementation using the Fast
The class \texttt{Reader} reads a binary file composed of 4 bytes representing the number of rows, 4 bytes representing the number of columns and then the raw matrix data. Each element is a \texttt{char} in all the test cases. The result is stored in the class \texttt{Task} which will be passed to the next node. If instead the operator \texttt{()} is called, only the data will be returned as a pointer. The class \texttt{Reader} reads a binary file composed of 4 bytes representing the number of rows, 4 bytes representing the number of columns and then the raw matrix data. Each element is a \texttt{char} in all the test cases. The result is stored in the class \texttt{Task} which will be passed to the next node. If instead the operator \texttt{()} is called, only the data will be returned as a pointer.
The \texttt{Task} class can support matrixes of different element type rather than \texttt{char}. The \texttt{Task} class can support matrices of different element type rather than \texttt{char}.
The \texttt{Writer} instead writes to disk the task to the same folder, overwriting existing files if present. The \texttt{Writer} instead writes to disk the task to the same folder, overwriting existing files if present.
The \texttt{Stencil} class divides the matrix in rougly equal parts and distributes them to other workers. The \texttt{Stencil} class divides the matrix in roughly equal parts and distributes them to other workers.
%% - - - - - - - - - - - - - - - - - - %% %% - - - - - - - - - - - - - - - - - - %%
\subsection{Native C++ Threads} \subsection{Native C++ Threads}
@ -457,7 +457,7 @@ the fastflow has a peek of speedup and scalability when using 4 workers in the s
\end{center} \end{center}
The file \texttt{random400x2500} % chktex 29 The file \texttt{random400x2500} % chktex 29
performs best with 16 workers in the Fastflow implementation and slightly better at 64 workers compared to 32 workers in terms of speedup and scalability but has a significand drop in efficiency from $0.361$ to $0.184$. The relationship between number of workers and speedup is close to linear up to 8 workers. performs best with 16 workers in the Fastflow implementation and slightly better at 64 workers compared to 32 workers in terms of speedup and scalability but has a significant drop in efficiency from $0.361$ to $0.184$. The relationship between number of workers and speedup is close to linear up to 8 workers.
\begin{center} \begin{center}
\begin{tikzpicture} \begin{tikzpicture}
@ -483,11 +483,11 @@ The file \texttt{equation} more closely follows a linear relationship between sp
\end{tikzpicture} \end{tikzpicture}
\end{center} \end{center}
As the size of the input increases the speedup and the scalability both follow linear trends up with a higher ammount of threds. As the size of the input increases the speedup and the scalability both follow linear trends up with a higher amount of threads.
The scalability for both test files \texttt{equation} and \texttt{equation2} never go below $0.37$, but is slightly better for the implementation with native C++ threads. The scalability for both test files \texttt{equation} and \texttt{equation2} never go below $0.37$, but is slightly better for the implementation with native C++ threads.
The difference in the three quantities between the test with file \texttt{equation} and the test with file \texttt{euqation1} is much smaller for the Fastflow version. In the native thread version instead there is a small improvement expecially with a higher number of workers. The difference in the three quantities between the test with file \texttt{equation} and the test with file \texttt{equation1} is much smaller for the Fastflow version. In the native thread version instead there is a small improvement especially with a higher number of workers.
\end{document} \end{document}