From: afanfakh Date: Mon, 5 Oct 2015 09:06:14 +0000 (+0200) Subject: adding the comparison section X-Git-Url: https://bilbo.iut-bm.univ-fcomte.fr/and/gitweb/mpi-energy2.git/commitdiff_plain/fe79318beef87d419e3952d9a1140372bd71bf4e?hp=b4f045bac56831537abd93cb4ee5bc570e53fe3b adding the comparison section --- diff --git a/mpi-energy2-extension/Heter_paper.tex b/mpi-energy2-extension/Heter_paper.tex index b2c2c21..a7aa66d 100644 --- a/mpi-energy2-extension/Heter_paper.tex +++ b/mpi-energy2-extension/Heter_paper.tex @@ -1096,6 +1096,74 @@ in these benchmarks. \subsection{The comparison of the proposed frequencies selecting algorithm } \label{sec.compare_EDP} +The tradeoff between the energy consumption and the performance of the parallel +application had significant importance in the domain of the research. +Many researchers, \cite{EDP_for_multi_processors,Energy_aware_application_scheduling,Exploring_Energy_Performance_TradeOffs}, +are optimized the tradeoff between the energy and performance using the energy and delay product, $EDP=energy \times delay$. +This model is used by Spiliopoulos et al. algorithm \cite{Spiliopoulos_Green.governors.Adaptive.DVFS}, +the objective is to selects the suitable frequencies that minimized EDP product for the multicores +architecture when DVFS is used. Moreover, their algorithm is applied online which synchronously optimized the energy consumption +and the execution time. Both energy consumption and execution time of a processor are predicted by the their algorithm. +In this section the proposed frequency selection algorithm, called Maxdist is compared with Spiliopoulos et al. algorithm, called EDP. +To make both of the algorithms follow the same direction and fairly comparing them, the same energy model, equation \ref{eq:energy} and +the execution time model, equation \ref{eq:perf}, are used in the prediction process to select the best vector of the frequencies. +In contrast, the proposed algorithm starts the search space from the lower bound computed as in equation the \ref{eq:Fint}. Also, the algorithm +stops the search process when reaching to the lower bound as mentioned before. While, the EDP algorithm is developed to start from the +same upper bound until it reach to the minimum available frequencies. Finally, resulting the algorithm is an exhaustive search algorithm that +test all possible frequencies, starting from the initial frequencies, and selecting those minimized the EDP products. + +Both algorithms were applied to NAS benchmarks class D over 16 nodes selected from grid'5000 clusters. +The participating computing nodes are distributed between two sites to had two different scenarios. +These scenarios are two sites and one site scenarios that explained previously. +The experimental results of the energy saving, performance degradation and tradeoff distance are +presented in the figures \ref{fig:edp-eng}, \ref{fig:edp-perf} and \ref{fig:edp-dist} respectively. + +In one site scenario the proposed frequencies selection algorithm outperform the EDP algorithm +in term of energy and performance for all of the benchmarks. While, the compassion results from the two sites scenario +showed that the proposed algorithm outperform EDP algorithm for all benchmarks except MG benchmark. +In case of MG benchmark the are small communications and bigger frequencies selected in EDP algorithm +decreased the performance degradation more than the frequencies selected by Maxdist algorithm. +While the energy saving percentage are higher for Maxdist algorithm. + +Generally, the proposed algorithm gives better results for all benchmarks because it +optimized the distance between the energy saving and the performance degradation. +Whereas, in EDP algorithm gives negative tradeoff for some benchmarks in the two sites scenarios. +These negative tradeoffs mean the performance degradation percentage is higher than energy saving percentage. +The higher positive value for tradeoff distance is mean the best energy and performance tradeoff is achieved synchronously, when +the energy saving percentage is much higher than the performance degradation percentage +The time complexity of the proposed algorithm is $O(N \cdot M \cdot F)$, where $N$ is the number of the clusters, +$M$ is the number of nodes and $F$ is the maximum number of available frequencies. The algorithm is selected +the best frequencies in small execution time, on average is equal to 0.01 $ms$ when it works over 32 nodes. +While the EDP algorithm was slower than Maxdist algorithm by ten times, where their execution time on average +takes 0.1 $ms$ to selects the suitable frequencies over 32 nodes. +The time complexity of this algorithm is $O(N^2 \cdot M^2 \cdot F)$. + + + + + + + +\begin{figure} + \centering + \includegraphics[scale=0.5]{fig/edp_eng} + \caption{Comparing of the energy saving for the proposed method with EDP method} + \label{fig:edp-eng} +\end{figure} + +\begin{figure} + \centering + \includegraphics[scale=0.5]{fig/edp_per} + \caption{Comparing of the performance degradation for the proposed method with EDP method} + \label{fig:edp-perf} +\end{figure} + +\begin{figure} + \centering + \includegraphics[scale=0.5]{fig/edp_dist} + \caption{Comparing of the tradeoff distance for the proposed method with EDP method} + \label{fig:edp-dist} +\end{figure} \section{Conclusion} diff --git a/mpi-energy2-extension/my_reference.bib b/mpi-energy2-extension/my_reference.bib index 81d1c9f..c960950 100644 --- a/mpi-energy2-extension/my_reference.bib +++ b/mpi-energy2-extension/my_reference.bib @@ -834,3 +834,50 @@ pages={1451-1476} year={2013}, publisher={Springer Science \& Business Media} } + +@article{EDP_for_multi_processors, +year={2015}, +journal={Human-centric Computing and Information Sciences}, +eid={28}, +volume={5}, +number={1}, +doi={10.1186/s13673-015-0046-x}, +title={An energy-delay product study on chip multi-processors for variable stage pipelining}, +url={http://dx.doi.org/10.1186/s13673-015-0046-x}, +publisher={Springer Berlin Heidelberg}, +keywords={Chip multi-processors (CMP); Variable stage pipelining (VSP); Power-performance; Optimal pipeline}, +author={Saravanan, Vijayalakshmi and Anpalagan, Alagan and Woungang, Isaac} +} + + +@INPROCEEDINGS{Energy_aware_application_scheduling, +author={Jian Chen and John, L.K.}, +booktitle={Workload Characterization, 2008. IISWC 2008. IEEE International Symposium on}, +title={Energy-aware application scheduling on a heterogeneous multi-core system}, +year={2008}, +pages={5-13}, +keywords={fuzzy logic;power aware computing;processor scheduling;resource allocation;branch transition rate;energy-aware application scheduling mechanism;fuzzy logic;heterogeneous multicore processor;instruction dependency distance;power efficient computing;program execution;random scheduling approach;resource requirement;suitability-guided program scheduling mechanism;workload balancing;Algorithm design and analysis;Application software;Energy consumption;Fuzzy logic;Hardware;Multicore processing;Power engineering and energy;Power engineering computing;Processor scheduling;Scheduling algorithm}, +doi={10.1109/IISWC.2008.4636086}, +month={Sept} +} + +@INPROCEEDINGS{elusive_metric_for_low_power, + author = {Hsien-hsin S. Lee and Joshua B. Fryman and A. Utku Diril and Yuvraj S. Dhillon}, + title = {The elusive metric for low-power architecture research}, + booktitle = {In Proceedings of the Workshop on Complexity-Effective Design}, + year = {2003} +} + +@incollection{Exploring_Energy_Performance_TradeOffs, +year={2006}, +isbn={978-3-540-68039-0}, +booktitle={High Performance Computing - HiPC 2006}, +volume={4297}, +editor={Robert, Yves and Parashar, Manish and Badrinath, Ramamurthy and Prasanna, ViktorK.}, +doi={10.1007/11945918_48}, +title={Exploring Energy-Performance Trade-Offs for Heterogeneous Interconnect Clustered VLIW Processors}, +url={http://dx.doi.org/10.1007/11945918_48}, +publisher={Springer Berlin Heidelberg}, +author={Nagpal, Rahul and Srikant, Y.N.}, +pages={497-508} +}