TP-openmp/BE_OpenMP_2019/tree_branch/subject.tex

\documentclass{article}

\usepackage{algorithm}
\usepackage{algorithmic}
\usepackage{graphicx}
\usepackage{marvosym}
\usepackage{dingbat}
\usepackage{tikz}

\title{Longest branch of a tree}
\date{}

\usetikzlibrary{arrows}

\tikzset{
  treenode/.style = {align=center, inner sep=0pt, text centered, font=\sffamily},
  wn/.style = {treenode, circle, black, font=\ttfamily, draw=white, fill=white, text width=1.5em},
  txt/.style = {black, anchor=west, font=\ttfamily, draw=white, fill=white},
  edge from parent/.style={thick,draw=black, latex-}
}

\begin{document}
\maketitle

\section{Longest tree branch}

This exercise is about parallelizing a Depth First Search (DFS) traversal of
a random tree. We assume that each node has a weight which corresponds
to the time it takes to process it. Our DFS traversal finds the
longest branch in the tree, i.e., the branch such that the sum of the
weigths of its nodes is maximum. 

The tree is nodes of type \texttt{node\_t} which contain the following members

\begin{itemize}
\item \texttt{weight}: the weight of the node;
\item \texttt{branch\_weight}: the weight of the branch that connects
  the node to the root of the tree; this is set to zero at the
  beginning and is updated during the DFS traversal;
\item \texttt{id}: the node number;
\item \texttt{nc}: the number of children of the node.
\item \texttt{*children}: an array of pointers to the children of the node.
\end{itemize}

The traversal is done recursively using the following code

\begin{verbatim}
void longest_branch_seq_rec(node_t *root, unsigned int *weight, unsigned int *leaf){
  int i;
  process(root);
  root->branch_weight += root->weight;
  
  if(root->nc>0) {
    for(i=0; i<root->nc; i++){
      root->children[i].branch_weight = root->branch_weight;
      longest_branch_seq_rec(root->children+i, weight, leaf);
    }
  } else {
    if(root->branch_weight > *weight){
      *weight = root->branch_weight;
      *leaf   = root->id;
    }
  }
}
\end{verbatim}

The \texttt{weight} and \texttt{leaf} arguments of this function are
meant to return the weight of the longest branch and the corresponding
leaf.  When we visit a node, first we process it using the
\texttt{process} routine and we update the weight of the branch that
connects it to the root (i.e., we add its weight to the branch weight
of its father).  Then, if it has children, we recursively call this
code on each one of them, if not then it means that we have reached a
leaf of the tree; in this case if the weight of the current branch is
grater than the current maximum contained in the \texttt{weight}
variable, we update \texttt{weight} and \texttt{leaf}.

For example, on the tree below, this method would return the leaf
number $3$ and the associated weight of $137$.

\begin{center}
  \includegraphics[width=0.4\textwidth]{tree.pdf}
\end{center}


\section{Package content}
In the \texttt{tree\_branch} directory you will find the
following files:
\begin{itemize}
\item \texttt{main.c}: this file contains the main program which first
  initializes the tree for a provided number of maximum levels. The main
  program then calls a sequential routine \texttt{longest\_branch\_seq}
  containing the above code, then calls the
  \texttt{longest\_branch\_par} routine which is supposed to contain a
  parallel version of the traversal code.
\item \texttt{longest\_branch\_seq.c}: contains a routine implementing a
  sequential traversal with the code presented above.
\item \texttt{longest\_branch\_par.c} contains a routine implementing a
  parallel tree traversal. \textbf{Only this file has to be modified
    for this exercise}.
\item \texttt{aux.c, aux.h}: these two files contain auxiliary
  routines and \textbf{must not be modified}.
\end{itemize}



The code can be compiled with the \texttt{make} command: just type
\texttt{make} inside the \texttt{tree\_branch} directory; this
will generate a \texttt{main} program that can be run like this:

\begin{verbatim}
$ ./main l s
\end{verbatim}

where \texttt{l} is the number of levels in the tree. The argument $s$
is the seed for the random number generation (which is used to build
the tree), and can be used to create trees of different shapes for a
fixed number of levels.

\section{Assignment}
\begin{itemize}
\item {\huge \Keyboard} At the beginning, the
  \texttt{longest\_branch\_par} routine contains an exact copy of the
  \texttt{longest\_branch\_seq} one. Modify these routine in order to
  parallelize it.  Make sure that the result computed by the three
  routines (sequential and parallel ones) is consistently (that is, at
  every execution of the parallel code) the same; a message printed at
  the end of the execution will tell you whether this is the
  case. Note that there may be multiple branches of the same length;
  in this case any of them will be considered a correct result. Also,
  modify the code in order to count the number of nodes updated by
  each of the working threads.
\item \smallpencil Report the execution times for the implemented
  parallel version with 1, 2 and 4 threads and for different tree
  sizes. Analyze and comment on your results: is the achieved speedup
  reasonable or not? Report your answer in the \texttt{responses.txt}
  file.
\end{itemize}


\paragraph{Advice}
\begin{itemize}
\item As usual, when developing and debugging choose trees of small
  size. When evaluating performance it's better to choose a larges
  tree size.
\end{itemize}



















\end{document}




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