X-Git-Url: https://bilbo.iut-bm.univ-fcomte.fr/and/gitweb/mpi-energy.git/blobdiff_plain/068765674898390f6a849e6426474b76e4ebf291..c3da7359fcccb593da2f53d83b99fd595bfae86c:/paper.tex diff --git a/paper.tex b/paper.tex index bfa1bc1..1ce2f60 100644 --- a/paper.tex +++ b/paper.tex @@ -14,8 +14,9 @@ % \usepackage{secdot} %\usepackage[font={footnotesize,bt}]{caption} %\usepackage[font=scriptsize,labelfont=bf]{caption} +\usepackage{xspace} \usepackage[textsize=footnotesize]{todonotes} -\newcommand{\AG}[2][inline]{\todo[color=green!50,#1]{\sffamily\textbf{AG:} #2}} +\newcommand{\AG}[2][inline]{\todo[color=green!50,#1]{\sffamily\textbf{AG:} #2}\xspace} \begin{document} @@ -109,7 +110,9 @@ presented and classified in two parts : offline and online methods. The DVFS offline methods are static and are not executed during the runtime of the program. Some approaches used heuristics to select the best DVFS state during the compilation phases as an example in Azevedo et al.~\cite{40}. He used -intra-task algorithm to choose the DVFS setting when there are dependency points +intra-task algorithm +\AG{what is an ``intra-task algorithm''?} +to choose the DVFS setting when there are dependency points between tasks. While in~\cite{29}, Xie et al. used breadth-first search algorithm to do that. Their goal is saving energy with time limits. Another approaches gathers and stores the runtime information for each DVFS state, then @@ -166,11 +169,13 @@ we consider execution of the synchronous tasks on distributed homogeneous platform. These tasks can exchange the data via synchronous memory passing. \begin{figure*}[t] \centering - \subfloat[Synch. Imbalanced Communications]{\includegraphics[scale=0.67]{synch_tasks}\label{fig:h1}} - \subfloat[Synch. Imbalanced Computations]{\includegraphics[scale=0.67]{compt}\label{fig:h2}} + \subfloat[Sync. Imbalanced Communications]{\includegraphics[scale=0.67]{synch_tasks}\label{fig:h1}} + \subfloat[Sync. Imbalanced Computations]{\includegraphics[scale=0.67]{compt}\label{fig:h2}} \caption{Parallel Tasks on Homogeneous Platform} \label{fig:homo} \end{figure*} +\AG{On fig.~\ref{fig:h1}, how can there be a synchronization point without communications just before ?\\ +Use ``Sync.'' to abbreviate ``Synchronization''} Therefore, the execution time of a task consists of the computation time and the communication time. Moreover, the synchronous communications between tasks can lead to idle time while tasks wait at the synchronous point for others tasks to @@ -208,7 +213,7 @@ where V is the supply voltage, N is the number of transistors, $K_{design}$ is a design dependent parameter and $I_{leak}$ is a technology-dependent parameter. Energy consumed by an individual processor $E_{ind}$ is the summation of the dynamic and the static power multiply by the execution time for example -see~\cite{36,15} . +see~\cite{36,15}. \begin{equation} \label{eq:eind} E_{ind} = ( P_{dyn} + P_{static} ) \cdot T @@ -217,7 +222,7 @@ The dynamic voltage and frequency scaling (DVFS) is a process that allowed in modern processors to reduce the dynamic power by scaling down the voltage and frequency. Its main objective is to reduce the overall energy consumption~\cite{37}. The operational frequency \emph f depends linearly on the -supply voltage $V$, i.e., $V = \beta . f$ with some constant $\beta$. This +supply voltage $V$, i.e., $V = \beta \cdot f$ with some constant $\beta$. This equation is used to study the change of the dynamic voltage with respect to various frequency values in~\cite{3}. The reduction process of the frequency are expressed by scaling factor \emph S. The scale \emph S is the ratio between the @@ -226,8 +231,10 @@ maximum and the new frequency as in EQ~(\ref{eq:s}). \label{eq:s} S = \frac{F_{max}}{F_{new}} \end{equation} -The value of the scale \emph S is grater than 1 when changing the frequency to -any new frequency value(\emph {P-state}) in governor. It is equal to 1 when the +The value of the scale $S$ is greater than 1 when changing the frequency to +any new frequency value (\emph {P-state}) in governor. +\AG{Explain what's a governor} +It is equal to 1 when the frequency are set to the maximum frequency. The energy consumption model for parallel homogeneous platform is depending on the scaling factor \emph S. This factor reduces quadratically the dynamic power. Also, this factor increases the @@ -347,7 +354,7 @@ figure~(\ref{fig:pred}). This section demonstrates our approach for choosing the optimal scaling factor. This factor gives maximum energy reduction taking into account the -execution time for both computation and communication times . The relation +execution time for both computation and communication times. The relation between the energy and the performance are nonlinear and complex, because the relation of the energy with scaling factor is nonlinear and with the performance it is linear see~\cite{17}. The relation between the energy and the performance @@ -482,7 +489,7 @@ in the MPI program. \For {$J:=1$ to $Some-Iterations \; $} \State -Computations Section. \State -Communications Section. - \If {$(J==1)$} + \If {$(J==1)$} \State -Gather all times of computation and\par \State communication from each node. \State -Call EPSA with these times. @@ -774,6 +781,12 @@ than the first. Computations have been performed on the supercomputer facilities of the Mésocentre de calcul de Franche-Comté. +% trigger a \newpage just before the given reference +% number - used to balance the columns on the last page +% adjust value as needed - may need to be readjusted if +% the document is modified later +%\IEEEtriggeratref{15} + \bibliographystyle{IEEEtran} \bibliography{IEEEabrv,my_reference} \end{document} @@ -782,8 +795,8 @@ Mésocentre de calcul de Franche-Comté. %%% mode: latex %%% TeX-master: t %%% fill-column: 80 -%%%ispell-local-dictionary: "american" +%%% ispell-local-dictionary: "american" %%% End: % LocalWords: Badri Charr FIXME Tianhe DVFS HPC NAS NPB SMPI Rauber's Rauber -% LocalWords: CMOS EQ EPSA +% LocalWords: CMOS EQ EPSA Franche Comté Tflop