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\appendix |
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\chapter{\label{chapt:oopse}Object-Oriented Parallel Simulation Engine} |
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Designing object-oriented software is hard, and designing reusable |
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object-oriented scientific software is even harder. Absence of |
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applying modern software development practices is the bottleneck of |
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Scientific Computing community\cite{Wilson2006}. For instance, in |
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the last 20 years , there are quite a few MD packages that were |
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developed to solve common MD problems and perform robust simulations |
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. However, many of the codes are legacy programs that are either |
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poorly organized or extremely complex. Usually, these packages were |
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contributed by scientists without official computer science |
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training. The development of most MD applications are lack of strong |
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coordination to enforce design and programming guidelines. Moreover, |
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most MD programs also suffer from missing design and implement |
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documents which is crucial to the maintenance and extensibility. |
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Along the way of studying structural and dynamic processes in |
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condensed phase systems like biological membranes and nanoparticles, |
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we developed and maintained an Object-Oriented Parallel Simulation |
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Engine ({\sc OOPSE}). This new molecular dynamics package has some |
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unique features |
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Absence of applying modern software development practices is the |
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bottleneck of Scientific Computing community\cite{Wilson2006}. In |
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the last 20 years , there are quite a few MD |
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packages\cite{Brooks1983, Vincent1995, Kale1999} that were developed |
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to solve common MD problems and perform robust simulations . |
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Unfortunately, most of them are commercial programs that are either |
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poorly written or extremely complicate. Consequently, it prevents |
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the researchers to reuse or extend those packages to do cutting-edge |
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research effectively. Along the way of studying structural and |
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dynamic processes in condensed phase systems like biological |
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membranes and nanoparticles, we developed an open source |
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Object-Oriented Parallel Simulation Engine ({\sc OOPSE}). This new |
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molecular dynamics package has some unique features |
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\begin{enumerate} |
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\item {\sc OOPSE} performs Molecular Dynamics (MD) simulations on non-standard |
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atom types (transition metals, point dipoles, sticky potentials, |
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program of the package, \texttt{oopse} and it corresponding parallel |
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version \texttt{oopse\_MPI}, as well as other useful utilities, such |
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as \texttt{StatProps} (see Sec.~\ref{appendixSection:StaticProps}), |
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\texttt{DynamicProps} (see |
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Sec.~\ref{appendixSection:appendixSection:DynamicProps}), |
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\texttt{Dump2XYZ} (see |
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Sec.~\ref{appendixSection:appendixSection:Dump2XYZ}), \texttt{Hydro} |
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(see Sec.~\ref{appendixSection:appendixSection:hydrodynamics}) |
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\texttt{DynamicProps} (see Sec.~\ref{appendixSection:DynamicProps}), |
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\texttt{Dump2XYZ} (see Sec.~\ref{appendixSection:Dump2XYZ}), |
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\texttt{Hydro} (see Sec.~\ref{appendixSection:hydrodynamics}) |
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\textit{etc}. |
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\begin{figure} |
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reusable. They provide a ready-made solution that can be adapted to |
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different problems as necessary. Pattern are expressive. they |
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provide a common vocabulary of solutions that can express large |
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solutions succinctly. |
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Patterns are usually described using a format that includes the |
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following information: |
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\begin{enumerate} |
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\item The \emph{name} that is commonly used for the pattern. Good pattern names form a vocabulary for |
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discussing conceptual abstractions. a pattern may have more than one commonly used or recognizable name |
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in the literature. In this case it is common practice to document these nicknames or synonyms under |
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the heading of \emph{Aliases} or \emph{Also Known As}. |
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\item The \emph{motivation} or \emph{context} that this pattern applies |
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to. Sometimes, it will include some prerequisites that should be satisfied before deciding to use a pattern |
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\item The \emph{solution} to the problem that the pattern |
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addresses. It describes how to construct the necessary work products. The description may include |
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pictures, diagrams and prose which identify the pattern's structure, its participants, and their |
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collaborations, to show how the problem is solved. |
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\item The \emph{consequences} of using the given solution to solve a |
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problem, both positive and negative. |
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\end{enumerate} |
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As one of the latest advanced techniques emerged from |
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object-oriented community, design patterns were applied in some of |
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the modern scientific software applications, such as JMol, {\sc |
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OOPSE}\cite{Meineke2005} and PROTOMOL\cite{Matthey2005} |
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solutions succinctly. As one of the latest advanced techniques |
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emerged from object-oriented community, design patterns were applied |
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in some of the modern scientific software applications, such as |
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JMol, {\sc OOPSE}\cite{Meineke2005} and PROTOMOL\cite{Matthey2004} |
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\textit{etc}. The following sections enumerates some of the patterns |
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used in {\sc OOPSE}. |
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|
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variable, the logging utility which reports error and warning |
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messages to the console in {\sc OOPSE} is a good candidate for |
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applying the Singleton pattern to avoid the global namespace |
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pollution.Although the singleton pattern can be implemented in |
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pollution. Although the singleton pattern can be implemented in |
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various ways to account for different aspects of the software |
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designs, such as lifespan control \textit{etc}, we only use the |
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static data approach in {\sc OOPSE}. IntegratorFactory class is |
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declared as |
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|
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static data approach in {\sc OOPSE}. The declaration and |
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implementation of IntegratorFactory class are given by declared in |
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List.~\ref{appendixScheme:singletonDeclaration} and |
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List.~\ref{appendixScheme:singletonImplementation} respectively. |
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Since constructor is declared as protected, a client can not |
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instantiate IntegratorFactory directly. Moreover, since the member |
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function getInstance serves as the only entry of access to |
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IntegratorFactory, this approach fulfills the basic requirement, a |
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single instance. Another consequence of this approach is the |
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automatic destruction since static data are destroyed upon program |
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termination. |
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\begin{lstlisting}[float,caption={[A classic Singleton design pattern implementation(I)] The declaration of of simple Singleton pattern.},label={appendixScheme:singletonDeclaration}] |
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class IntegratorFactory { |
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\end{lstlisting} |
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The corresponding implementation is |
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\begin{lstlisting}[float,caption={[A classic implementation of Singleton design pattern (II)] The implementation of simple Singleton pattern.},label={appendixScheme:singletonImplementation}] |
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IntegratorFactory::instance_ = NULL; |
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\end{lstlisting} |
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Since constructor is declared as protected, a client can not |
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instantiate IntegratorFactory directly. Moreover, since the member |
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function getInstance serves as the only entry of access to |
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IntegratorFactory, this approach fulfills the basic requirement, a |
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single instance. Another consequence of this approach is the |
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automatic destruction since static data are destroyed upon program |
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termination. |
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\subsection{\label{appendixSection:factoryMethod}Factory Method} |
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createIntegrator member function) creates products based on the |
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identifier (see List.~\ref{appendixScheme:factoryDeclaration}). If |
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the identifier has been already registered, the factory method will |
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invoke the corresponding creator (see List.~\ref{integratorCreator}) |
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which utilizes the modern C++ template technique to avoid excess |
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subclassing. |
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invoke the corresponding creator (see |
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List.~\ref{appendixScheme:integratorCreator}) which utilizes the |
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modern C++ template technique to avoid excess subclassing. |
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|
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\begin{lstlisting}[float,caption={[The implementation of Parameterized Factory pattern (I)]Source code of IntegratorFactory class.},label={appendixScheme:factoryDeclaration}] |
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and other atoms of type $B$, $g_{AB}(r)$. {\tt StaticProps} can |
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also be used to compute the density distributions of other molecules |
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in a reference frame {\it fixed to the body-fixed reference frame} |
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of a selected atom or rigid body. |
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of a selected atom or rigid body. Due to the fact that the selected |
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StuntDoubles from two selections may be overlapped, {\tt |
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StaticProps} performs the calculation in three stages which are |
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illustrated in Fig.~\ref{oopseFig:staticPropsProcess}. |
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|
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\begin{figure} |
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\centering |
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\includegraphics[width=\linewidth]{staticPropsProcess.eps} |
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\caption[A representation of the three-stage correlations in |
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\texttt{StaticProps}]{This diagram illustrates three-stage |
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processing used by \texttt{StaticProps}. $S_1$ and $S_2$ are the |
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numbers of selected stuntdobules from {\tt -{}-sele1} and {\tt |
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-{}-sele2} respectively, while $C$ is the number of stuntdobules |
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appearing at both sets. The first stage($S_1-C$ and $S_2$) and |
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second stages ($S_1$ and $S_2-C$) are completely non-overlapping. On |
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the contrary, the third stage($C$ and $C$) are completely |
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overlapping} \label{oopseFig:staticPropsProcess} |
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\end{figure} |
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There are five seperate radial distribution functions availiable in |
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OOPSE. Since every radial distrbution function invlove the |
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\end{description} |
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The vectors (and angles) associated with these angular pair |
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distribution functions are most easily seen in the figure below: |
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distribution functions are most easily seen in |
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Fig.~\ref{oopseFig:gofr} |
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\begin{figure} |
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\centering |
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their body-fixed frames.} \label{oopseFig:gofr} |
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\end{figure} |
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|
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Due to the fact that the selected StuntDoubles from two selections |
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may be overlapped, {\tt StaticProps} performs the calculation in |
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three stages which are illustrated in |
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Fig.~\ref{oopseFig:staticPropsProcess}. |
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|
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\begin{figure} |
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\centering |
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\includegraphics[width=\linewidth]{staticPropsProcess.eps} |
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\caption[A representation of the three-stage correlations in |
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\texttt{StaticProps}]{This diagram illustrates three-stage |
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processing used by \texttt{StaticProps}. $S_1$ and $S_2$ are the |
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numbers of selected stuntdobules from {\tt -{}-sele1} and {\tt |
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-{}-sele2} respectively, while $C$ is the number of stuntdobules |
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appearing at both sets. The first stage($S_1-C$ and $S_2$) and |
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second stages ($S_1$ and $S_2-C$) are completely non-overlapping. On |
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the contrary, the third stage($C$ and $C$) are completely |
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overlapping} \label{oopseFig:staticPropsProcess} |
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\end{figure} |
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The options available for {\tt StaticProps} are as follows: |
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\begin{longtable}[c]{|EFG|} |
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\caption{StaticProps Command-line Options} |
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select different types of atoms is already present in the code. |
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For large simulations, the trajectory files can sometimes reach |
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sizes in excess of several gigabytes. In order to effectively |
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analyze that amount of data. In order to prevent a situation where |
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the program runs out of memory due to large trajectories, |
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\texttt{dynamicProps} will estimate the size of free memory at |
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first, and determine the number of frames in each block, which |
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allows the operating system to load two blocks of data |
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sizes in excess of several gigabytes. In order to prevent a |
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situation where the program runs out of memory due to large |
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trajectories, \texttt{dynamicProps} will estimate the size of free |
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memory at first, and determine the number of frames in each block, |
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which allows the operating system to load two blocks of data |
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simultaneously without swapping. Upon reading two blocks of the |
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trajectory, \texttt{dynamicProps} will calculate the time |
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correlation within the first block and the cross correlations |
