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# Line 3 | Line 3 | the last 20 years , there are quite a few MD packages
3  
4   Absence of applying modern software development practices is the
5   bottleneck of Scientific Computing community\cite{Wilson2006}. In
6 < the last 20 years , there are quite a few MD packages that were
7 < developed to solve common MD problems and perform robust simulations
8 < . However, many of the codes are legacy programs that are either
9 < poorly organized or extremely complex. Usually, these packages were
10 < contributed by scientists without official computer science
11 < training. The development of most MD applications are lack of strong
12 < coordination to enforce design and programming guidelines. Moreover,
13 < most MD programs also suffer from missing design and implement
14 < documents which is crucial to the maintenance and extensibility.
15 < Along the way of studying structural and dynamic processes in
16 < condensed phase systems like biological membranes and nanoparticles,
17 < we developed and maintained an Object-Oriented Parallel Simulation
18 < Engine ({\sc OOPSE}). This new molecular dynamics package has some
19 < unique features
6 > the last 20 years , there are quite a few MD
7 > packages\cite{Brooks1983, Vincent1995, Kale1999} that were developed
8 > to solve common MD problems and perform robust simulations .
9 > Unfortunately, most of them are commercial programs that are either
10 > poorly written or extremely complicate. Consequently, it prevents
11 > the researchers to reuse or extend those packages to do cutting-edge
12 > research effectively. Along the way of studying structural and
13 > dynamic processes in condensed phase systems like biological
14 > membranes and nanoparticles, we developed an open source
15 > Object-Oriented Parallel Simulation Engine ({\sc OOPSE}). This new
16 > molecular dynamics package has some unique features
17   \begin{enumerate}
18    \item {\sc OOPSE} performs Molecular Dynamics (MD) simulations on non-standard
19   atom types (transition metals, point dipoles, sticky potentials,
# Line 87 | Line 84 | solutions succinctly.
84   reusable. They provide a ready-made solution that can be adapted to
85   different problems as necessary. Pattern are expressive. they
86   provide a common vocabulary of solutions that can express large
87 < solutions succinctly.
88 <
89 < Patterns are usually described using a format that includes the
90 < following information:
94 < \begin{enumerate}
95 <  \item The \emph{name} that is commonly used for the pattern. Good pattern names form a vocabulary for
96 <  discussing conceptual abstractions. a pattern may have more than one commonly used or recognizable name
97 <  in the literature. In this case it is common practice to document these nicknames or synonyms under
98 <  the heading of \emph{Aliases} or \emph{Also Known As}.
99 <  \item The \emph{motivation} or \emph{context} that this pattern applies
100 <  to. Sometimes, it will include some prerequisites that should be satisfied before deciding to use a pattern
101 <  \item The \emph{solution} to the problem that the pattern
102 <  addresses. It describes how to construct the necessary work products. The description may include
103 <  pictures, diagrams and prose which identify the pattern's structure, its participants, and their
104 <  collaborations, to show how the problem is solved.
105 <  \item The \emph{consequences} of using the given solution to solve a
106 <  problem, both positive and negative.
107 < \end{enumerate}
108 <
109 < As one of the latest advanced techniques emerged from
110 < object-oriented community, design patterns were applied in some of
111 < the modern scientific software applications, such as JMol, {\sc
112 < OOPSE}\cite{Meineke2005} and PROTOMOL\cite{Matthey2005}
87 > solutions succinctly. As one of the latest advanced techniques
88 > emerged from object-oriented community, design patterns were applied
89 > in some of the modern scientific software applications, such as
90 > JMol, {\sc OOPSE}\cite{Meineke2005} and PROTOMOL\cite{Matthey2004}
91   \textit{etc}. The following sections enumerates some of the patterns
92   used in {\sc OOPSE}.
93  
# Line 121 | Line 99 | pollution.Although the singleton pattern can be implem
99   variable, the logging utility which reports error and warning
100   messages to the console in {\sc OOPSE} is a good candidate for
101   applying the Singleton pattern to avoid the global namespace
102 < pollution.Although the singleton pattern can be implemented in
102 > pollution. Although the singleton pattern can be implemented in
103   various ways  to account for different aspects of the software
104   designs, such as lifespan control \textit{etc}, we only use the
105 < static data approach in {\sc OOPSE}. IntegratorFactory class is
106 < declared as
107 <
105 > static data approach in {\sc OOPSE}. The declaration and
106 > implementation of IntegratorFactory class are given by declared in
107 > List.~\ref{appendixScheme:singletonDeclaration} and
108 > Scheme.~\ref{appendixScheme:singletonImplementation} respectively.
109 > Since constructor is declared as protected, a client can not
110 > instantiate IntegratorFactory directly. Moreover, since the member
111 > function getInstance serves as the only entry of access to
112 > IntegratorFactory, this approach fulfills the basic requirement, a
113 > single instance. Another consequence of this approach is the
114 > automatic destruction since static data are destroyed upon program
115 > termination.
116   \begin{lstlisting}[float,caption={[A classic Singleton design pattern implementation(I)] The declaration of of simple Singleton pattern.},label={appendixScheme:singletonDeclaration}]
117  
118   class IntegratorFactory {
# Line 141 | Line 127 | The corresponding implementation is
127  
128   \end{lstlisting}
129  
144 – The corresponding implementation is
145 –
130   \begin{lstlisting}[float,caption={[A classic implementation of Singleton design pattern (II)] The implementation of simple Singleton pattern.},label={appendixScheme:singletonImplementation}]
131  
132   IntegratorFactory::instance_ = NULL;
# Line 156 | Line 140 | Since constructor is declared as protected, a client c
140  
141   \end{lstlisting}
142  
159 – Since constructor is declared as protected, a client can not
160 – instantiate IntegratorFactory directly. Moreover, since the member
161 – function getInstance serves as the only entry of access to
162 – IntegratorFactory, this approach fulfills the basic requirement, a
163 – single instance. Another consequence of this approach is the
164 – automatic destruction since static data are destroyed upon program
165 – termination.
143  
144   \subsection{\label{appendixSection:factoryMethod}Factory Method}
145  
# Line 172 | Line 149 | identifier (see List.~\ref{appendixScheme:factoryDecla
149   implemented by delegating the creation operation to the subclasses.
150   Parameterized Factory pattern where factory method (
151   createIntegrator member function) creates products based on the
152 < identifier (see List.~\ref{appendixScheme:factoryDeclaration}). If
152 > identifier (see Scheme.~\ref{appendixScheme:factoryDeclaration}). If
153   the identifier has been already registered, the factory method will
154 < invoke the corresponding creator (see List.~\ref{integratorCreator})
155 < which utilizes the modern C++ template technique to avoid excess
156 < subclassing.
154 > invoke the corresponding creator (see
155 > Scheme.~\ref{appendixScheme:integratorCreator}) which utilizes the
156 > modern C++ template technique to avoid excess subclassing.
157  
158   \begin{lstlisting}[float,caption={[The implementation of Parameterized Factory pattern (I)]Source code of IntegratorFactory class.},label={appendixScheme:factoryDeclaration}]
159  
# Line 238 | Line 215 | in List.~\ref{appendixScheme:element}). Since the hier
215   Dump2XYZ}. In order to convert an OOPSE dump file, a series of
216   distinct operations are performed on different StuntDoubles (See the
217   class hierarchy in Fig.~\ref{oopseFig:hierarchy} and the declaration
218 < in List.~\ref{appendixScheme:element}). Since the hierarchies
218 > in Scheme.~\ref{appendixScheme:element}). Since the hierarchies
219   remains stable, it is easy to define a visit operation (see
220 < List.~\ref{appendixScheme:visitor}) for each class of StuntDouble.
220 > Scheme.~\ref{appendixScheme:visitor}) for each class of StuntDouble.
221   Note that using Composite pattern\cite{Gamma1994}, CompositVisitor
222   manages a priority visitor list and handles the execution of every
223   visitor in the priority list on different StuntDoubles.
# Line 300 | Line 277 | class SSDAtomVisitor:public BaseAtomVisitor{ public:
277    virtual void visit(RigidBody* rb);
278   };
279  
303 – class SSDAtomVisitor:public BaseAtomVisitor{ public:
304 –  virtual void visit(Atom* atom);
305 –  virtual void visit(DirectionalAtom* datom);
306 –  virtual void visit(RigidBody* rb);
307 – };
308 –
280   class CompositeVisitor: public BaseVisitor {
281   public:
282  
# Line 314 | Line 285 | class CompositeVisitor: public BaseVisitor { (public)
285    virtual void visit(Atom* atom) {
286      VisitorListIterator i;
287      BaseVisitor* curVisitor;
288 <    for(i = visitorList.begin();i != visitorList.end();++i) {
288 >    for(i = visitorScheme.begin();i != visitorScheme.end();++i) {
289        atom->accept(*i);
290      }
291    }
# Line 322 | Line 293 | class CompositeVisitor: public BaseVisitor { (public)
293    virtual void visit(DirectionalAtom* datom) {
294      VisitorListIterator i;
295      BaseVisitor* curVisitor;
296 <    for(i = visitorList.begin();i != visitorList.end();++i) {
296 >    for(i = visitorScheme.begin();i != visitorScheme.end();++i) {
297        atom->accept(*i);
298      }
299    }
# Line 332 | Line 303 | class CompositeVisitor: public BaseVisitor { (public)
303      std::vector<Atom*> myAtoms;
304      std::vector<Atom*>::iterator ai;
305      myAtoms = rb->getAtoms();
306 <    for(i = visitorList.begin();i != visitorList.end();++i) {{
306 >    for(i = visitorScheme.begin();i != visitorScheme.end();++i) {{
307        rb->accept(*i);
308        for(ai = myAtoms.begin(); ai != myAtoms.end(); ++ai){
309          (*ai)->accept(*i);
# Line 344 | Line 315 | class CompositeVisitor: public BaseVisitor { (public)
315    protected:
316      VistorListType visitorList;
317   };
347 –
318   \end{lstlisting}
319  
320   \section{\label{appendixSection:concepts}Concepts}
# Line 515 | Line 485 | of a selected atom or rigid body.
485   and other atoms of type $B$, $g_{AB}(r)$.  {\tt StaticProps} can
486   also be used to compute the density distributions of other molecules
487   in a reference frame {\it fixed to the body-fixed reference frame}
488 < of a selected atom or rigid body.
488 > of a selected atom or rigid body. Due to the fact that the selected
489 > StuntDoubles from two selections may be overlapped, {\tt
490 > StaticProps} performs the calculation in three stages which are
491 > illustrated in Fig.~\ref{oopseFig:staticPropsProcess}.
492  
493 + \begin{figure}
494 + \centering
495 + \includegraphics[width=\linewidth]{staticPropsProcess.eps}
496 + \caption[A representation of the three-stage correlations in
497 + \texttt{StaticProps}]{This diagram illustrates three-stage
498 + processing used by \texttt{StaticProps}. $S_1$ and $S_2$ are the
499 + numbers of selected stuntdobules from {\tt -{}-sele1} and {\tt
500 + -{}-sele2} respectively, while $C$ is the number of stuntdobules
501 + appearing at both sets. The first stage($S_1-C$ and $S_2$) and
502 + second stages ($S_1$ and $S_2-C$) are completely non-overlapping. On
503 + the contrary, the third stage($C$ and $C$) are completely
504 + overlapping} \label{oopseFig:staticPropsProcess}
505 + \end{figure}
506 +
507   There are five seperate radial distribution functions availiable in
508   OOPSE. Since every radial distrbution function invlove the
509   calculation between pairs of bodies, {\tt -{}-sele1} and {\tt
# Line 560 | Line 547 | distribution functions are most easily seen in the fig
547   \end{description}
548  
549   The vectors (and angles) associated with these angular pair
550 < distribution functions are most easily seen in the figure below:
550 > distribution functions are most easily seen in
551 > Fig.~\ref{oopseFig:gofr}
552  
553   \begin{figure}
554   \centering
# Line 571 | Line 559 | Due to the fact that the selected StuntDoubles from tw
559   their body-fixed frames.} \label{oopseFig:gofr}
560   \end{figure}
561  
574 – Due to the fact that the selected StuntDoubles from two selections
575 – may be overlapped, {\tt StaticProps} performs the calculation in
576 – three stages which are illustrated in
577 – Fig.~\ref{oopseFig:staticPropsProcess}.
578 –
579 – \begin{figure}
580 – \centering
581 – \includegraphics[width=\linewidth]{staticPropsProcess.eps}
582 – \caption[A representation of the three-stage correlations in
583 – \texttt{StaticProps}]{This diagram illustrates three-stage
584 – processing used by \texttt{StaticProps}. $S_1$ and $S_2$ are the
585 – numbers of selected stuntdobules from {\tt -{}-sele1} and {\tt
586 – -{}-sele2} respectively, while $C$ is the number of stuntdobules
587 – appearing at both sets. The first stage($S_1-C$ and $S_2$) and
588 – second stages ($S_1$ and $S_2-C$) are completely non-overlapping. On
589 – the contrary, the third stage($C$ and $C$) are completely
590 – overlapping} \label{oopseFig:staticPropsProcess}
591 – \end{figure}
592 –
562   The options available for {\tt StaticProps} are as follows:
563   \begin{longtable}[c]{|EFG|}
564   \caption{StaticProps Command-line Options}
# Line 652 | Line 621 | sizes in excess of several gigabytes. In order to effe
621   select different types of atoms is already present in the code.
622  
623   For large simulations, the trajectory files can sometimes reach
624 < sizes in excess of several gigabytes. In order to effectively
625 < analyze that amount of data. In order to prevent a situation where
626 < the program runs out of memory due to large trajectories,
627 < \texttt{dynamicProps} will estimate the size of free memory at
628 < first, and determine the number of frames in each block, which
660 < allows the operating system to load two blocks of data
624 > sizes in excess of several gigabytes. In order to prevent a
625 > situation where the program runs out of memory due to large
626 > trajectories, \texttt{dynamicProps} will estimate the size of free
627 > memory at first, and determine the number of frames in each block,
628 > which allows the operating system to load two blocks of data
629   simultaneously without swapping. Upon reading two blocks of the
630   trajectory, \texttt{dynamicProps} will calculate the time
631   correlation within the first block and the cross correlations

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