adding some changes

diff --git a/mpi-energy2-extension/Heter_paper.tex b/mpi-energy2-extension/Heter_paper.tex
index 8c6061c8aea45247fd3f4bdff1afaf6521d580e6..5dc876cb679388874b8f85e4411257064779fcda 100644 (file)
--- a/mpi-energy2-extension/Heter_paper.tex
+++ b/mpi-energy2-extension/Heter_paper.tex
@@ -213,7 +213,7 @@ scaling (DVFS) is one of them. It can be used to reduce the power consumption of
   The proposed algorithm is evaluated on a real grid, the grid'5000 platform, while
   running the NAS parallel benchmarks.  The experiments show that it reduces the
   energy consumption on average by \np[\%]{30} while  the performance  is only degraded
   The proposed algorithm is evaluated on a real grid, the grid'5000 platform, while
   running the NAS parallel benchmarks.  The experiments show that it reduces the
   energy consumption on average by \np[\%]{30} while  the performance  is only degraded

-  on average by \np[\%]{3}. Finally, the algorithm is 
+  on average by \np[\%]{3.2}. Finally, the algorithm is 

   compared to an existing method. The comparison results show that it outperforms the
   latter in terms of energy consumption reduction and performance.
 \end{abstract}
   compared to an existing method. The comparison results show that it outperforms the
   latter in terms of energy consumption reduction and performance.
 \end{abstract}


@@ -661,9 +661,9 @@ equation, as follows:
 \begin{figure}
   \centering
   \subfloat[Homogeneous cluster]{%
 \begin{figure}
   \centering
   \subfloat[Homogeneous cluster]{%

-    \includegraphics[width=.33\textwidth]{fig/homo}\label{fig:r1}} \hspace{2cm}%
+    \includegraphics[width=.4\textwidth]{fig/homo}\label{fig:r1}} \hspace{2cm}%

   \subfloat[Heterogeneous grid]{%
   \subfloat[Heterogeneous grid]{%

-    \includegraphics[width=.33\textwidth]{fig/heter}\label{fig:r2}}
+    \includegraphics[width=.4\textwidth]{fig/heter}\label{fig:r2}}

   \label{fig:rel}
   \caption{The energy and performance relation}
 \end{figure}
   \label{fig:rel}
   \caption{The energy and performance relation}
 \end{figure}


@@ -998,16 +998,7 @@ Table \ref{tab:sc} shows the number of nodes used from each cluster for each sce
 \end{table}
 
 
 \end{table}
 
 

-\begin{figure}
-  \centering
-  \subfloat[The energy consumption by the nodes wile executing the NAS benchmarks over different scenarios    
-           ]{%
-    \includegraphics[width=.4\textwidth]{fig/eng_con_scenarios.eps}\label{fig:eng_sen}} \hspace{1cm}%
-  \subfloat[The execution times of the NAS benchmarks over different scenarios]{%
-    \includegraphics[width=.4\textwidth]{fig/time_scenarios.eps}\label{fig:time_sen}}
-  \label{fig:exp-time-energy}
-  \caption{The  energy consumption and execution time of NAS  Benchmarks over different scenarios}
-\end{figure}
+

 
 The NAS parallel benchmarks are executed over these two platforms
  with different number of nodes, as in Table \ref{tab:sc}. 
 
 The NAS parallel benchmarks are executed over these two platforms
  with different number of nodes, as in Table \ref{tab:sc}. 


@@ -1033,18 +1024,6 @@ However, the  execution times and the energy consumptions of EP and MG benchmark
  in both scenarios. Even when the number of nodes is doubled. On the other hand, the communications of the rest of the benchmarks increases when using long distance communications between two sites or increasing the number of computing nodes.
 
 
  in both scenarios. Even when the number of nodes is doubled. On the other hand, the communications of the rest of the benchmarks increases when using long distance communications between two sites or increasing the number of computing nodes.
 
 

-\begin{figure}
-  \centering
-  \subfloat[The energy reduction while executing the NAS benchmarks over different scenarios ]{%
-    \includegraphics[width=.33\textwidth]{fig/eng_s.eps}\label{fig:eng_s}} \hspace{0.08cm}%
-  \subfloat[The performance degradation of the NAS benchmarks over different scenarios]{%
-    \includegraphics[width=.33\textwidth]{fig/per_d.eps}\label{fig:per_d}}\hspace{0.08cm}%
-    \subfloat[The tradeoff distance between the energy reduction and the performance of the NAS benchmarks  
-      over different scenarios]{%
-    \includegraphics[width=.33\textwidth]{fig/dist.eps}\label{fig:dist}}
-  \label{fig:exp-res}
-  \caption{The experimental results of different scenarios}
-\end{figure}

 
 The energy saving percentage is computed as the ratio between the reduced 
 energy consumption, equation (\ref{eq:energy}), and the original energy consumption,
 
 The energy saving percentage is computed as the ratio between the reduced 
 energy consumption, equation (\ref{eq:energy}), and the original energy consumption,


@@ -1058,8 +1037,31 @@ is exponentially related to the CPU's frequency value. On the other side, the in
 increase the communication times and thus produces less energy saving depending on the 
 benchmarks being executed. The results of the benchmarks CG, MG, BT and FT show more 
 energy saving percentage in one site scenario when executed over 16 nodes comparing to 32 nodes. While, LU and SP consume more energy with 16 nodes than 32 in one site  because their computations to communications ratio is not affected by the increase of the number of local communications. 
 increase the communication times and thus produces less energy saving depending on the 
 benchmarks being executed. The results of the benchmarks CG, MG, BT and FT show more 
 energy saving percentage in one site scenario when executed over 16 nodes comparing to 32 nodes. While, LU and SP consume more energy with 16 nodes than 32 in one site  because their computations to communications ratio is not affected by the increase of the number of local communications. 

+\begin{figure}
+  \centering
+  \subfloat[The energy consumption by the nodes wile executing the NAS benchmarks over different scenarios    
+           ]{%
+    \includegraphics[width=.4\textwidth]{fig/eng_con_scenarios.eps}\label{fig:eng_sen}} \hspace{1cm}%
+  \subfloat[The execution times of the NAS benchmarks over different scenarios]{%
+    \includegraphics[width=.4\textwidth]{fig/time_scenarios.eps}\label{fig:time_sen}}
+  \label{fig:exp-time-energy}
+  \caption{The  energy consumption and execution time of NAS  Benchmarks over different scenarios}
+\end{figure}

 
 
 
 

+\begin{figure}
+  \centering
+  \subfloat[The energy reduction while executing the NAS benchmarks over different scenarios ]{%
+    \includegraphics[width=.4\textwidth]{fig/eng_s.eps}\label{fig:eng_s}} \hspace{2cm}%
+  \subfloat[The performance degradation of the NAS benchmarks over different scenarios]{%
+    \includegraphics[width=.4\textwidth]{fig/per_d.eps}\label{fig:per_d}}\hspace{2cm}%
+    \subfloat[The tradeoff distance between the energy reduction and the performance of the NAS benchmarks  
+      over different scenarios]{%
+    \includegraphics[width=.4\textwidth]{fig/dist.eps}\label{fig:dist}}
+  \label{fig:exp-res}
+  \caption{The experimental results of different scenarios}
+\end{figure}
+

 The energy saving percentage is reduced for all the benchmarks because of the long distance communications in the two sites 
 scenario, except for the   EP benchmark which has  no communications. Therefore, the energy saving percentage of this benchmark is 
 dependent on the maximum difference between the computing powers of the heterogeneous computing nodes, for example 
 The energy saving percentage is reduced for all the benchmarks because of the long distance communications in the two sites 
 scenario, except for the   EP benchmark which has  no communications. Therefore, the energy saving percentage of this benchmark is 
 dependent on the maximum difference between the computing powers of the heterogeneous computing nodes, for example 


@@ -1076,9 +1078,9 @@ The best energy saving percentage was obtained in the one site scenario with 16
 
 Figure \ref{fig:per_d} presents the performance degradation percentages for all benchmarks over the two scenarios.
 The performance degradation percentage for the benchmarks running on two sites  with
 
 Figure \ref{fig:per_d} presents the performance degradation percentages for all benchmarks over the two scenarios.
 The performance degradation percentage for the benchmarks running on two sites  with

-16 or 32  nodes is on average equal to 8\% or 4\% respectively. 
+16 or 32  nodes is on average equal to 8.3\% or 4.7\% respectively. 

 For this scenario, the proposed scaling algorithm selects smaller frequencies for the executions with 32 nodes  without significantly degrading their performance because the communication times are higher with 32 nodes which results in smaller  computations to communications ratio.  On the other hand, the performance degradation percentage  for the benchmarks running  on one site  with
 For this scenario, the proposed scaling algorithm selects smaller frequencies for the executions with 32 nodes  without significantly degrading their performance because the communication times are higher with 32 nodes which results in smaller  computations to communications ratio.  On the other hand, the performance degradation percentage  for the benchmarks running  on one site  with

-16 or 32  nodes is on average equal to 3\% or 10\% respectively. In opposition to the two sites scenario, when the number of computing nodes is increased in the one site scenario, the performance degradation percentage is increased. Therefore, doubling the number of computing 
+16 or 32  nodes is on average equal to 3.2\% or 10.6\% respectively. In opposition to the two sites scenario, when the number of computing nodes is increased in the one site scenario, the performance degradation percentage is increased. Therefore, doubling the number of computing 

 nodes when the communications occur in high speed network does not decrease the computations to 
 communication ratio. 
 
 nodes when the communications occur in high speed network does not decrease the computations to 
 communication ratio. 
 


@@ -1090,7 +1092,7 @@ when the communication times increase and vice versa.
 
 Figure \ref{fig:dist} presents the  distance percentage between the energy saving  and the performance degradation for each benchmark  over both  scenarios. The tradeoff distance percentage can be 
 computed as in equation \ref{eq:max}. The one site scenario with 16 nodes gives the best energy and performance 
 
 Figure \ref{fig:dist} presents the  distance percentage between the energy saving  and the performance degradation for each benchmark  over both  scenarios. The tradeoff distance percentage can be 
 computed as in equation \ref{eq:max}. The one site scenario with 16 nodes gives the best energy and performance 

-tradeoff, on average it is equal to  26\%. The one site scenario using both 16 and 32 nodes had better energy and performance 
+tradeoff, on average it is equal to  26.8\%. The one site scenario using both 16 and 32 nodes had better energy and performance 

 tradeoff comparing to the two sites scenario  because the former has high speed local communications 
 which increase the computations to communications ratio  and the latter uses long distance communications which decrease this ratio. 
 
 tradeoff comparing to the two sites scenario  because the former has high speed local communications 
 which increase the computations to communications ratio  and the latter uses long distance communications which decrease this ratio. 
 


@@ -1179,12 +1181,12 @@ These  tradeoff distance percentages are used to verify which scenario is the be
 \begin{figure}
   \centering
     \subfloat[The energy saving of running NAS benchmarks over one core and multicores scenarios]{%
 \begin{figure}
   \centering
     \subfloat[The energy saving of running NAS benchmarks over one core and multicores scenarios]{%

-    \includegraphics[width=.33\textwidth]{fig/eng_s_mc.eps}\label{fig:eng-s-mc}} \hspace{0.08cm}%
+    \includegraphics[width=.4\textwidth]{fig/eng_s_mc.eps}\label{fig:eng-s-mc}} \hspace{2cm}%

     \subfloat[The performance degradation of running NAS benchmarks over one core and multicores scenarios
       ]{%
     \subfloat[The performance degradation of running NAS benchmarks over one core and multicores scenarios
       ]{%

-    \includegraphics[width=.33\textwidth]{fig/per_d_mc.eps}\label{fig:per-d-mc}}\hspace{0.08cm}%
+    \includegraphics[width=.4\textwidth]{fig/per_d_mc.eps}\label{fig:per-d-mc}}\hspace{2cm}%

     \subfloat[The tradeoff distance of running NAS benchmarks over one core and multicores scenarios]{%
     \subfloat[The tradeoff distance of running NAS benchmarks over one core and multicores scenarios]{%

-    \includegraphics[width=.33\textwidth]{fig/dist_mc.eps}\label{fig:dist-mc}}
+    \includegraphics[width=.4\textwidth]{fig/dist_mc.eps}\label{fig:dist-mc}}

   \label{fig:exp-res}
   \caption{The experimental results of one core and multi-cores scenarios}
 \end{figure}
   \label{fig:exp-res}
   \caption{The experimental results of one core and multi-cores scenarios}
 \end{figure}


@@ -1205,11 +1207,12 @@ In these experiments, the class D of the NAS parallel benchmarks are executed ov
 \begin{figure}
   \centering
   \subfloat[The energy saving percentages for the nodes executing the NAS benchmarks over the three power scenarios]{%
 \begin{figure}
   \centering
   \subfloat[The energy saving percentages for the nodes executing the NAS benchmarks over the three power scenarios]{%

-    \includegraphics[width=.33\textwidth]{fig/eng_pow.eps}\label{fig:eng-pow}} \hspace{0.08cm}%
+    \includegraphics[width=.4\textwidth]{fig/eng_pow.eps}\label{fig:eng-pow}} \hspace{2cm}%

   \subfloat[The performance degradation percentages for the NAS benchmarks over the three power scenarios]{%
   \subfloat[The performance degradation percentages for the NAS benchmarks over the three power scenarios]{%

-    \includegraphics[width=.33\textwidth]{fig/per_pow.eps}\label{fig:per-pow}}\hspace{0.08cm}%
+    \includegraphics[width=.4\textwidth]{fig/per_pow.eps}\label{fig:per-pow}}\hspace{2cm}%

     \subfloat[The tradeoff distance between the energy reduction and the performance of the NAS benchmarks over the three power scenarios]{%
     \subfloat[The tradeoff distance between the energy reduction and the performance of the NAS benchmarks over the three power scenarios]{%

-    \includegraphics[width=.33\textwidth]{fig/dist_pow.eps}\label{fig:dist-pow}}
+      
+    \includegraphics[width=.4\textwidth]{fig/dist_pow.eps}\label{fig:dist-pow}}

   \label{fig:exp-pow}
   \caption{The experimental results of different static power scenarios}
 \end{figure}
   \label{fig:exp-pow}
   \caption{The experimental results of different static power scenarios}
 \end{figure}


@@ -1269,11 +1272,11 @@ presented in the figures \ref{fig:edp-eng}, \ref{fig:edp-perf} and \ref{fig:edp-
 \begin{figure}
   \centering
   \subfloat[The energy reduction induced by the Maxdist method and the EDP method]{%
 \begin{figure}
   \centering
   \subfloat[The energy reduction induced by the Maxdist method and the EDP method]{%

-    \includegraphics[width=.33\textwidth]{fig/edp_eng}\label{fig:edp-eng}} \hspace{0.08cm}%
+    \includegraphics[width=.4\textwidth]{fig/edp_eng}\label{fig:edp-eng}} \hspace{2cm}%

     \subfloat[The performance degradation induced by  the Maxdist method and the EDP method]{%
     \subfloat[The performance degradation induced by  the Maxdist method and the EDP method]{%

-    \includegraphics[width=.33\textwidth]{fig/edp_per}\label{fig:edp-perf}}\hspace{0.08cm}%
+    \includegraphics[width=.4\textwidth]{fig/edp_per}\label{fig:edp-perf}}\hspace{2cm}%

     \subfloat[The tradeoff distance between the energy consumption reduction and the performance for the Maxdist method and the  EDP method]{%
     \subfloat[The tradeoff distance between the energy consumption reduction and the performance for the Maxdist method and the  EDP method]{%

-    \includegraphics[width=.33\textwidth]{fig/edp_dist}\label{fig:edp-dist}}
+    \includegraphics[width=.4\textwidth]{fig/edp_dist}\label{fig:edp-dist}}

   \label{fig:edp-comparison}
   \caption{The comparison results}
 \end{figure}
   \label{fig:edp-comparison}
   \caption{The comparison results}
 \end{figure}


@@ -1302,7 +1305,7 @@ of the distributed iterative message passing application running over a grid arc
 To evaluate the proposed method on a real heterogeneous grid platform, it was applied on the  
  NAS parallel benchmarks   and the  class D instance was executed over the  grid'5000 testbed platform. 
  The experimental results showed that the algorithm reduces  on average 30\% of the energy consumption
 To evaluate the proposed method on a real heterogeneous grid platform, it was applied on the  
  NAS parallel benchmarks   and the  class D instance was executed over the  grid'5000 testbed platform. 
  The experimental results showed that the algorithm reduces  on average 30\% of the energy consumption

-for all the NAS benchmarks   while  only degrading by 3\% on average  the performance. 
+for all the NAS benchmarks   while  only degrading by 3.2\% on average  the performance. 

 The Maxdist algorithm was also evaluated in different scenarios that vary in the distribution of the computing nodes between different clusters' sites or \textcolor{blue}{between using one core and multi-cores per node} or in the values of the consumed static power. The algorithm selects different vector of frequencies according to the 
 computations and communication times ratios, and  the values of the static and measured dynamic powers of the CPUs. 
 Finally, the proposed algorithm was compared to another method that uses
 The Maxdist algorithm was also evaluated in different scenarios that vary in the distribution of the computing nodes between different clusters' sites or \textcolor{blue}{between using one core and multi-cores per node} or in the values of the consumed static power. The algorithm selects different vector of frequencies according to the 
 computations and communication times ratios, and  the values of the static and measured dynamic powers of the CPUs. 
 Finally, the proposed algorithm was compared to another method that uses

diff --git a/mpi-energy2-extension/fig/dist_mc.eps b/mpi-energy2-extension/fig/dist_mc.eps
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diff --git a/mpi-energy2-extension/fig/per_d_mc.eps b/mpi-energy2-extension/fig/per_d_mc.eps
index e64ad0efca70998948194726d606a9243d03d4ab..19d87f193c8474d5b49452308da0505eed60b32d 100644 (file)
--- a/mpi-energy2-extension/fig/per_d_mc.eps
+++ b/mpi-energy2-extension/fig/per_d_mc.eps
@@ -1,6 +1,6 @@
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   /Author (afanfakh)
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-  /CreationDate (Thu Oct 22 13:20:07 2015)
+  /CreationDate (Thu Oct 22 17:36:36 2015)

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@@ -795,11 +795,11 @@ LTb
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 1.000 UL
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-1980 3305 M
-[ [(Helvetica) 140.0 0.0 true true 0 (One site/  one core)]
+2362 3305 M
+[ [(Helvetica) 140.0 0.0 true true 0 (One core per node scenario)]

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 LT0
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-1980 3173 M
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+2362 3173 M
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diff --git a/mpi-energy2-extension/fig/time.eps b/mpi-energy2-extension/fig/time.eps
index 72eb22bc51d63ce886e23e0a7e9584bfbe276c97..99cea89434afbae413265705131e1a1601d4460b 100644 (file)
--- a/mpi-energy2-extension/fig/time.eps
+++ b/mpi-energy2-extension/fig/time.eps
@@ -1,6 +1,6 @@
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   /Author (afanfakh)
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-  /CreationDate (Thu Oct 22 13:29:00 2015)
+  /CreationDate (Thu Oct 22 17:45:34 2015)

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@@ -866,11 +866,11 @@ LTb
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+2546 3264 M
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@@ -886,18 +886,18 @@ LT0
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@@ -913,7 +913,7 @@ LT1
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diff --git a/mpi-energy2-extension/my_reference.bib b/mpi-energy2-extension/my_reference.bib
index 2c7e80fb57da529fa52a7f873e998417331d438c..26a185885a3ef977081e116a120395b346052537 100644 (file)
--- a/mpi-energy2-extension/my_reference.bib
+++ b/mpi-energy2-extension/my_reference.bib
@@ -7,7 +7,6 @@
  isbn = {0-7695-2700-0},
  location = {Tampa, Florida},
  articleno = {107},
  isbn = {0-7695-2700-0},
  location = {Tampa, Florida},
  articleno = {107},

- doi = {10.1145/1188455.1188567},

  acmid = {1188567},
  publisher = {ACM},
  address = {New York, NY, USA}
  acmid = {1188567},
  publisher = {ACM},
  address = {New York, NY, USA}


@@ -15,11 +14,11 @@
 
 @article{2,  
  author = {Peraza , J. and Tiwari , A. and Laurenzano , M. and Carrington L. and Snavely},  
 
 @article{2,  
  author = {Peraza , J. and Tiwari , A. and Laurenzano , M. and Carrington L. and Snavely},  

- title = {{PMaC}'s green queue: a framework for selecting energy optimal {DVFS} configurations in large scale {MPI} applications},  
- journal = {Concurrency Computat.: Pract. Exper.DOI: 10.1002/cpe},
+ title = {PMaC's green queue: a framework for selecting energy optimal DVFS configurations in large  scale   MPI applications},  
+ journal = {Concurrency and Computation: Practice and Experience},

  pages =  {1-20},   
  year = {2012} 
  pages =  {1-20},   
  year = {2012} 

-  
+ }

  }
  
 
  }
  
 


@@ -47,7 +46,6 @@
  location = {San Diego, CA, USA},
  pages = {275--280},
  numpages = {6},
  location = {San Diego, CA, USA},
  pages = {275--280},
  numpages = {6},

- doi = {10.1145/996566.996650},

  acmid = {996650},
  publisher = {ACM},
  address = {New York, NY, USA},
  acmid = {996650},
  publisher = {ACM},
  address = {New York, NY, USA},


@@ -90,19 +88,17 @@ title={Bounding energy consumption in large-scale {MPI} programs},
 year={2007},
 month=nov,
 pages={1-9},
 year={2007},
 month=nov,
 pages={1-9},

-keywords={Clustering algorithms;Delay effects;Dynamic voltage scaling;Energy consumption;Frequency;Government;Laboratories;Large-scale systems;Linear programming;Processor scheduling},
-doi={10.1145/1362622.1362688}
+keywords={Clustering algorithms;Delay effects;Dynamic voltage scaling;Energy consumption;Frequency;Government;Laboratories;Large-scale systems;Linear programming;Processor scheduling}

 }
 
 @phdthesis {Malkowski_energy.efficient.high.performance.computing,
 }
 
 @phdthesis {Malkowski_energy.efficient.high.performance.computing,

-    author    = "Malkowski, Konrad",
-    title     = "Co-adapting scientific applications and architectures toward energy-efficient high performance computing",
-    school    = "The Pennsylvania State University",
-    address  = "USA",
-    year      = "2009",
-    pages    = "227",
+    author    = {Malkowski, Konrad},
+    title     = {Co-adapting scientific applications and architectures toward energy-efficient high performance computing},
+    school    = {The Pennsylvania State University},
+    address  = {USA},
+    year      = {2009},
+    pages    = {227}

   
   

-   

 }
 
 @INPROCEEDINGS{10,
 }
 
 @INPROCEEDINGS{10,


@@ -112,8 +108,7 @@ title={Crown scheduling: Energy-efficient resource allocation, mapping and discr
 year={2013},
 month=sep,
 pages={215-222},
 year={2013},
 month=sep,
 pages={215-222},

-keywords={cores;microprocessor chips;optimisation;power consumption;resource allocation;scaling circuits;scheduling;ILP;crown scheduling;data flows;discrete voltage-frequency scaling;dynamic discrete frequency scaling;dynamic rescaling;energy-efficient resource allocation;energy-optimal code;integer linear programming;malleable streaming tasks;many-core processor;mapping;optimization;pipelined task graph;power consumption;processor cores;streaming task collections;Dynamic scheduling;Optimization;Processor scheduling;Radio spectrum management;Resource management;Schedules},
-doi={10.1109/PATMOS.2013.6662176}
+keywords={cores;microprocessor chips;optimisation;power consumption;resource allocation;scaling circuits;scheduling;ILP;crown scheduling;data flows;discrete voltage-frequency scaling;dynamic discrete frequency scaling;dynamic rescaling;energy-efficient resource allocation;energy-optimal code;integer linear programming;malleable streaming tasks;many-core processor;mapping;optimization;pipelined task graph;power consumption;processor cores;streaming task collections;Dynamic scheduling;Optimization;Processor scheduling;Radio spectrum management;Resource management;Schedules}

 }
 
 @INPROCEEDINGS{11,
 }
 
 @INPROCEEDINGS{11,


@@ -124,7 +119,6 @@ year={2006},
 month=sep,
 pages={1-10},
 keywords={directed graphs;parallel programming;power aware computing;AMD Turion;PC clusters;PowerWatch;Transmeta Crusoe;control library;directed acyclic task graph;dynamic voltage scaling;energy consumption;energy reduction;frequency scaling;high performance computing;microprocessors;parallel programs;power consumption;power monitoring tools;slack reclamation;Clustering algorithms;Concurrent computing;Dynamic voltage scaling;Energy consumption;Energy efficiency;Frequency synchronization;Gears;Libraries;Microprocessors;Monitoring},
 month=sep,
 pages={1-10},
 keywords={directed graphs;parallel programming;power aware computing;AMD Turion;PC clusters;PowerWatch;Transmeta Crusoe;control library;directed acyclic task graph;dynamic voltage scaling;energy consumption;energy reduction;frequency scaling;high performance computing;microprocessors;parallel programs;power consumption;power monitoring tools;slack reclamation;Clustering algorithms;Concurrent computing;Dynamic voltage scaling;Energy consumption;Energy efficiency;Frequency synchronization;Gears;Libraries;Microprocessors;Monitoring},

-doi={10.1109/CLUSTR.2006.311839},

 ISSN={1552-5244}
 }
 
 ISSN={1552-5244}
 }
 


@@ -140,7 +134,6 @@ ISSN={1552-5244}
  issn = {1094-3420},
  pages = {342--350},
  numpages = {9},
  issn = {1094-3420},
  pages = {342--350},
  numpages = {9},

- doi = {10.1177/1094342011414749},

  acmid = {2020813},
  publisher = {Sage Publications, Inc.},
  address = {Thousand Oaks, CA, USA},
  acmid = {2020813},
  publisher = {Sage Publications, Inc.},
  address = {Thousand Oaks, CA, USA},


@@ -148,7 +141,7 @@ ISSN={1552-5244}
 } 
 
 @ARTICLE{13,  
 } 
 
 @ARTICLE{13,  

- author = {Lizhe Wang a,b, Samee U. Khan c , Dan Chen a , Joanna Kołodziej d , Rajiv Ranjan e , Cheng-zhong Xu f ,Albert Zomaya},  
+ author = {Lizhe Wang a,b, Samee U. Khan c, Dan Chen a, Joanna Kołodziej d, Rajiv Ranjan e, Cheng-zhong Xu f,Albert Zomaya},  

  title = {Energy-aware parallel task scheduling in a cluster},  
  journal = {Future Generation Computer Systems},
  volume = {29},
  title = {Energy-aware parallel task scheduling in a cluster},  
  journal = {Future Generation Computer Systems},
  volume = {29},


@@ -165,8 +158,7 @@ title={Energy-Efficient Cluster Computing via Accurate Workload Characterization
 year={2009},
 month=may,
 pages={68-75},
 year={2009},
 month=may,
 pages={68-75},

-keywords={parallel processing;power aware computing;workstation clusters;cluster computer;eco-friendly daemon;energy consumption reduction;energy-efficient cluster computing;power consumption reduction;processor stall cycles;workload characterization;Application software;Clustering algorithms;Energy consumption;Energy efficiency;Frequency;Grid computing;Hardware;High performance computing;Runtime;Voltage},
-doi={10.1109/CCGRID.2009.88}
+keywords={parallel processing;power aware computing;workstation clusters;cluster computer;eco-friendly daemon;energy consumption reduction;energy-efficient cluster computing;power consumption reduction;processor stall cycles;workload characterization;Application software;Clustering algorithms;Energy consumption;Energy efficiency;Frequency;Grid computing;Hardware;High performance computing;Runtime;Voltage}

 }
 
 @article{Zhuo_Energy.efficient.Dynamic.Task.Scheduling,
 }
 
 @article{Zhuo_Energy.efficient.Dynamic.Task.Scheduling,


@@ -182,7 +174,6 @@ doi={10.1109/CCGRID.2009.88}
  pages = {17:1--17:25},
  articleno = {17},
  numpages = {25},
  pages = {17:1--17:25},
  articleno = {17},
  numpages = {25},

- doi = {10.1145/1331331.1331341},

  acmid = {1331341},
  publisher = {ACM},
  address = {New York, NY, USA},
  acmid = {1331341},
  publisher = {ACM},
  address = {New York, NY, USA},


@@ -197,7 +188,6 @@ doi={10.1109/CCGRID.2009.88}
  year = {2007},
  isbn = {0-7695-2933-X},
  pages = {19--},
  year = {2007},
  isbn = {0-7695-2933-X},
  pages = {19--},

- doi = {10.1109/ICPP.2007.39},

  acmid = {1306033},
  publisher = {IEEE Computer Society},
  address = {Washington, DC, USA}
  acmid = {1306033},
  publisher = {IEEE Computer Society},
  address = {Washington, DC, USA}


@@ -211,7 +201,6 @@ doi={10.1109/CCGRID.2009.88}
  year = {2005},
  isbn = {0-7695-2312-9},
  pages = {4a-4a},
  year = {2005},
  isbn = {0-7695-2312-9},
  pages = {4a-4a},

- doi = {10.1109/IPDPS.2005.214},

  acmid = {1054466},
  publisher = {IEEE Computer Society},
  address = {Washington, DC, USA}
  acmid = {1054466},
  publisher = {IEEE Computer Society},
  address = {Washington, DC, USA}


@@ -225,7 +214,6 @@ year={2010},
 month=apr,
 pages={1-12},
 keywords={message passing;parallel algorithms;power aware computing;HPC environment;dynamic concurrency throttling;dynamic voltage-and-frequency scaling;high performance computing;hybrid MPI-OpenMP computing;hybrid programming models;large-scale distributed systems;message passing interface;parallel programs;power-aware computing;power-aware performance prediction model;Concurrent computing;Discrete cosine transforms;Dynamic programming;Dynamic voltage scaling;Frequency;Heuristic algorithms;Large-scale systems;Multicore processing;Power system modeling;Predictive models;MPI;OpenMP;performance modeling;power-aware high -performance computing},
 month=apr,
 pages={1-12},
 keywords={message passing;parallel algorithms;power aware computing;HPC environment;dynamic concurrency throttling;dynamic voltage-and-frequency scaling;high performance computing;hybrid MPI-OpenMP computing;hybrid programming models;large-scale distributed systems;message passing interface;parallel programs;power-aware computing;power-aware performance prediction model;Concurrent computing;Discrete cosine transforms;Dynamic programming;Dynamic voltage scaling;Frequency;Heuristic algorithms;Large-scale systems;Multicore processing;Power system modeling;Predictive models;MPI;OpenMP;performance modeling;power-aware high -performance computing},

-doi={10.1109/IPDPS.2010.5470463},

 ISSN={1530-2075}
 }
 
 ISSN={1530-2075}
 }
 


@@ -238,10 +226,8 @@ ISSN={1530-2075}
                and energy management},
   booktitle = {ISQED},
   year      = {2012},
                and energy management},
   booktitle = {ISQED},
   year      = {2012},

-  pages     = {747-754},
-  ee        = {http://dx.doi.org/10.1109/ISQED.2012.6187575},
-  CCcrossref  = {DBLP:conf/isqed/2012},
-  CCbibsource = {DBLP, http://dblp.uni-trier.de}
+  pages     = {747-754}
+  

 }
 
 
 }
 
 


@@ -255,7 +241,6 @@ ISSN={1530-2075}
  location = {New York, New York, USA},
  pages = {230--238},
  numpages = {9},
  location = {New York, New York, USA},
  pages = {230--238},
  numpages = {9},

- doi = {10.1145/1122971.1123006},

  acmid = {1123006},
  publisher = {ACM},
  address = {New York, NY, USA},
  acmid = {1123006},
  publisher = {ACM},
  address = {New York, NY, USA},


@@ -275,7 +260,7 @@ ISSN={1530-2075}
   pages = {11-18},
   publisher = {SCS/ACM},
   timestamp = {2011-12-01T00:00:00.000+0100},
   pages = {11-18},
   publisher = {SCS/ACM},
   timestamp = {2011-12-01T00:00:00.000+0100},

-  title = {Modeling the energy consumption for concurrent executions of parallel tasks.},
+  title = {Modeling the energy consumption for concurrent executions of parallel tasks},

   year = {2011}
 }
 
   year = {2011}
 }
 


@@ -287,7 +272,6 @@ ISSN={1530-2075}
  year = {2005},
  isbn = {1-59593-061-2},
  pages = {34--},
  year = {2005},
  isbn = {1-59593-061-2},
  pages = {34--},

- doi = {10.1109/SC.2005.57},

  acmid = {1105799},
  publisher = {IEEE Computer Society},
  address = {Washington, DC, USA}
  acmid = {1105799},
  publisher = {IEEE Computer Society},
  address = {Washington, DC, USA}


@@ -302,7 +286,6 @@ ISSN={1530-2075}
  year = {2005},
  isbn = {0-7695-2312-9},
  pages = {34--},
  year = {2005},
  isbn = {0-7695-2312-9},
  pages = {34--},

- doi = {10.1109/IPDPS.2005.346},

  acmid = {1054376},
  publisher = {IEEE Computer Society},
  address = {Washington, DC, USA}
  acmid = {1054376},
  publisher = {IEEE Computer Society},
  address = {Washington, DC, USA}


@@ -316,7 +299,6 @@ ISSN={1530-2075}
   date = {2009-11-27},
   description = {dblp},
   editor = {Mueller, Peter and Cao, Jian-Nong and Wang, Cho-Li},
   date = {2009-11-27},
   description = {dblp},
   editor = {Mueller, Peter and Cao, Jian-Nong and Wang, Cho-Li},

-  ee = {http://dx.doi.org/10.1007/978-3-642-10485-5_8},

   interhash = {d191ac30e6c4bd27288ffdf9e6d0e815},
   intrahash = {4601b8a777bdf956bb48fa611b7556f5},
   isbn = {978-3-642-10484-8},
   interhash = {d191ac30e6c4bd27288ffdf9e6d0e815},
   intrahash = {4601b8a777bdf956bb48fa611b7556f5},
   isbn = {978-3-642-10484-8},


@@ -358,7 +340,6 @@ ISSN={1530-2075}
  issn = {0743-7315},
  pages = {1154--1164},
  numpages = {11},
  issn = {0743-7315},
  pages = {1154--1164},
  numpages = {11},

- doi = {10.1016/j.jpdc.2011.01.004},

  acmid = {1998949},
  publisher = {Academic Press, Inc.},
  address = {Orlando, FL, USA},
  acmid = {1998949},
  publisher = {Academic Press, Inc.},
  address = {Orlando, FL, USA},


@@ -377,7 +358,6 @@ ISSN={1530-2075}
  issn = {0278-0070},
  pages = {676--689},
  numpages = {14},
  issn = {0278-0070},
  pages = {676--689},
  numpages = {14},

- doi = {10.1109/TCAD.2009.2015740},

  acmid = {1656937},
  publisher = {IEEE Press},
  address = {Piscataway, NJ, USA},
  acmid = {1656937},
  publisher = {IEEE Press},
  address = {Piscataway, NJ, USA},


@@ -391,8 +371,7 @@ title={Thermal vs Energy Optimization for {DVFS}-Enabled Processors in Embedded
 year={2007},
 month=mar,
 pages={204-209},
 year={2007},
 month=mar,
 pages={204-209},

-keywords={circuit optimisation;embedded systems;integrated circuit design;low-power electronics;microprocessor chips;nonlinear programming;thermal management (packaging);DVFS-enabled processors;application peak temperature;cooling costs;dynamic voltage voltage;embedded systems;energy consumption;frequency scaling;nonlinear programming;power optimization;run-time thermal emergencies;system thermal profile;thermal optimization;thermal-constrained energy optimization;Cooling;Cost function;Design optimization;Dynamic voltage scaling;Embedded system;Energy consumption;Frequency;Power system planning;Runtime;Temperature},
-doi={10.1109/ISQED.2007.158}
+keywords={circuit optimisation;embedded systems;integrated circuit design;low-power electronics;microprocessor chips;nonlinear programming;thermal management (packaging);DVFS-enabled processors;application peak temperature;cooling costs;dynamic voltage voltage;embedded systems;energy consumption;frequency scaling;nonlinear programming;power optimization;run-time thermal emergencies;system thermal profile;thermal optimization;thermal-constrained energy optimization;Cooling;Cost function;Design optimization;Dynamic voltage scaling;Embedded system;Energy consumption;Frequency;Power system planning;Runtime;Temperature}

 }
 
 @INPROCEEDINGS{29,
 }
 
 @INPROCEEDINGS{29,


@@ -402,8 +381,7 @@ title={Bounds on power savings using runtime dynamic voltage scaling: an exact a
 year={2005},
 month=aug,
 pages={287-292},
 year={2005},
 month=aug,
 pages={287-292},

-keywords={approximation theory;energy conservation;low-power electronics;power consumption;power supply circuits;DVFS policy;discrete voltage/frequency voltage level;dynamic voltage scaling;dynamic voltage/frequency scaling;energy reduction technique;exponential algorithm;linear-time heuristic approximation;power reduction technique;switching cost;Approximation algorithms;Costs;Dynamic voltage scaling;Energy consumption;Frequency;Linear approximation;Power system modeling;Runtime;Semiconductor device modeling;Upper bound},
-doi={10.1109/LPE.2005.195529}
+keywords={approximation theory;energy conservation;low-power electronics;power consumption;power supply circuits;DVFS policy;discrete voltage/frequency voltage level;dynamic voltage scaling;dynamic voltage/frequency scaling;energy reduction technique;exponential algorithm;linear-time heuristic approximation;power reduction technique;switching cost;Approximation algorithms;Costs;Dynamic voltage scaling;Energy consumption;Frequency;Linear approximation;Power system modeling;Runtime;Semiconductor device modeling;Upper bound}

 }
 
 @INPROCEEDINGS{30,
 }
 
 @INPROCEEDINGS{30,


@@ -413,8 +391,7 @@ title={Towards Energy Aware Scheduling for Precedence Constrained Parallel Tasks
 year={2010},
 month=may,
 pages={368-377},
 year={2010},
 month=may,
 pages={368-377},

-keywords={environmental factors;parallel processing;power aware computing;scheduling;workstation clusters;dynamic voltage frequency scaling technique;energy aware scheduling heuristics;green service level agreement;high end computing;precedence constrained parallel tasks;Computational modeling;Concurrent computing;Costs;Dynamic voltage scaling;Energy consumption;Frequency;Grid computing;High performance computing;Power engineering computing;Processor scheduling;Cluster Computing;Green Computing;Task Scheduling},
-doi={10.1109/CCGRID.2010.19}
+keywords={environmental factors;parallel processing;power aware computing;scheduling;workstation clusters;dynamic voltage frequency scaling technique;energy aware scheduling heuristics;green service level agreement;high end computing;precedence constrained parallel tasks;Computational modeling;Concurrent computing;Costs;Dynamic voltage scaling;Energy consumption;Frequency;Grid computing;High performance computing;Power engineering computing;Processor scheduling;Cluster Computing;Green Computing;Task Scheduling}

 }
 
 @article{31,
 }
 
 @article{31,


@@ -426,7 +403,6 @@ number = {RapidPosts},
 issn = {1556-6056},
 year = {2013},
 pages = {1},
 issn = {1556-6056},
 year = {2013},
 pages = {1},

-doi = {http://doi.ieeecomputersociety.org/10.1109/L-CA.2013.1},

 publisher = {IEEE Computer Society},
 address = {Los Alamitos, CA, USA}
 }
 publisher = {IEEE Computer Society},
 address = {Los Alamitos, CA, USA}
 }


@@ -440,7 +416,6 @@ pages = "76 - 91",
 year = "2013",
 note = "S.I.Energy efficiency in grids and clouds ",
 issn = "1569-190X",
 year = "2013",
 note = "S.I.Energy efficiency in grids and clouds ",
 issn = "1569-190X",

-doi = "http://dx.doi.org/10.1016/j.simpat.2013.04.007",

 author = {Tom Guérout and Thierry Monteil and Georges Da Costa and Rodrigo Neves Calheiros and Rajkumar Buyya and Mihai Alexandru}
 
 }
 author = {Tom Guérout and Thierry Monteil and Georges Da Costa and Rodrigo Neves Calheiros and Rajkumar Buyya and Mihai Alexandru}
 
 }


@@ -452,8 +427,7 @@ title={Just In Time Dynamic Voltage Scaling: Exploiting Inter-Node Slack to Save
 year={2005},
 month=nov,
 pages={33-33},
 year={2005},
 month=nov,
 pages={33-33},

-keywords={Computer science;Dynamic voltage scaling;Energy consumption;Energy efficiency;Frequency;Gears;Jitter;Microprocessors;Performance loss;Permission},
-doi={10.1109/SC.2005.39}
+keywords={Computer science;Dynamic voltage scaling;Energy consumption;Energy efficiency;Frequency;Gears;Jitter;Microprocessors;Performance loss;Permission}

 }
 
 @inproceedings{34,
 }
 
 @inproceedings{34,


@@ -480,7 +454,6 @@ pages = " - ",
 year = "2013",
 note = "",
 issn = "1084-8045",
 year = "2013",
 note = "",
 issn = "1084-8045",

-doi = "http://dx.doi.org/10.1016/j.jnca.2013.10.009",

 author = {Wei Liu and Wei Du and Jing Chen and Wei Wang and GuoSun Zeng}
 
 }
 author = {Wei Liu and Wei Du and Jing Chen and Wei Wang and GuoSun Zeng}
 
 }


@@ -497,7 +470,6 @@ author = {Wei Liu and Wei Du and Jing Chen and Wei Wang and GuoSun Zeng}
  issn = {0018-9162},
  pages = {68--75},
  numpages = {8},
  issn = {0018-9162},
  pages = {68--75},
  numpages = {8},

- doi = {10.1109/MC.2003.1250885},

  acmid = {957974},
  publisher = {IEEE Computer Society Press},
  address = {Los Alamitos, CA, USA}
  acmid = {957974},
  publisher = {IEEE Computer Society Press},
  address = {Los Alamitos, CA, USA}


@@ -522,7 +494,6 @@ author = {Wei Liu and Wei Du and Jing Chen and Wei Wang and GuoSun Zeng}
  location = {Porto Alegre, Brazil},
  pages = {175--185},
  numpages = {11},
  location = {Porto Alegre, Brazil},
  pages = {175--185},
  numpages = {11},

- doi = {10.1145/2155620.2155641},

  acmid = {2155641},
  publisher = {ACM},
  address = {NY, USA}
  acmid = {2155641},
  publisher = {ACM},
  address = {NY, USA}


@@ -535,8 +506,8 @@ title={Dynamic voltage frequency scaling for multi-tasking systems using online
 year={2007},
 month=aug,
 pages={207-212},
 year={2007},
 month=aug,
 pages={207-212},

-keywords={Linux;computer aided instruction;multiprogramming;power aware computing;program compilers;system monitoring;Intel PXA27x;Linux 2.6.9;dynamic voltage frequency scaling;multitasking systems;online learning;processors runtime statistics;Batteries;Computer applications;Delay;Dynamic voltage scaling;Embedded system;Energy consumption;Frequency estimation;Linux;Power engineering computing;Statistics;dynamic voltage frequency scaling;online learning},
-doi={10.1145/1283780.1283825}
+keywords={Linux;computer aided instruction;multiprogramming;power aware computing;program compilers;system monitoring;Intel PXA27x;Linux 2.6.9;dynamic voltage frequency scaling;multitasking systems;online learning;processors runtime statistics;Batteries;Computer applications;Delay;Dynamic voltage scaling;Embedded system;Energy consumption;Frequency estimation;Linux;Power engineering computing;Statistics;dynamic voltage frequency scaling;online learning}
+

 }
 
 @inproceedings{40,
 }
 
 @inproceedings{40,


@@ -562,7 +533,6 @@ doi={10.1145/1283780.1283825}
  location = {Vancouver, B.C., CANADA},
  pages = {155--165},
  numpages = {11},
  location = {Vancouver, B.C., CANADA},
  pages = {155--165},
  numpages = {11},

- doi = {10.1109/MICRO.2012.23},

  acmid = {2457493},
  publisher = {IEEE Computer Society},
  address = {Washington, DC, USA}
  acmid = {2457493},
  publisher = {IEEE Computer Society},
  address = {Washington, DC, USA}


@@ -578,7 +548,6 @@ volume={28},
 number={5},
 pages={676-689},
 keywords={power aware computing;DPM policies;Intel PXA27x core;device leakage characteristics;dynamic power management;dynamic voltage-frequency scaling problems;hard disk drive;online learning;system-level power management;workload characterization;Dynamic voltage frequency scaling;energy-performance trade-off;online learning;power management},
 number={5},
 pages={676-689},
 keywords={power aware computing;DPM policies;Intel PXA27x core;device leakage characteristics;dynamic power management;dynamic voltage-frequency scaling problems;hard disk drive;online learning;system-level power management;workload characterization;Dynamic voltage frequency scaling;energy-performance trade-off;online learning;power management},

-doi={10.1109/TCAD.2009.2015740},

 ISSN={0278-0070}
 }
 
 ISSN={0278-0070}
 }
 


@@ -629,7 +598,6 @@ ISSN={0278-0070}
   isbn =         {978-0-7695-3114-4},
   pages =        {126--131},
   numpages =     {6},
   isbn =         {978-0-7695-3114-4},
   pages =        {126--131},
   numpages =     {6},

-  doi =          {10.1109/UKSIM.2008.28},

   acmid =        {1398183},
   publisher =    {IEEE Computer Society},
   address =      {Washington, DC, USA}
   acmid =        {1398183},
   publisher =    {IEEE Computer Society},
   address =      {Washington, DC, USA}


@@ -647,7 +615,6 @@ ISSN={0278-0070}
   pages = {2899--2917},
   year = 2014,
   month = oct,
   pages = {2899--2917},
   year = 2014,
   month = oct,

-  doi = {10.1016/j.jpdc.2014.06.008},

   pdf = {http://hal.inria.fr/docs/01/05/75/41/PDF/simgrid3-journal.pdf}
 }
 
   pdf = {http://hal.inria.fr/docs/01/05/75/41/PDF/simgrid3-journal.pdf}
 }
 


@@ -675,7 +642,6 @@ year={2012},
 month=sep,
 pages={48-57}, 
 keywords={energy consumption;graphics processing units;parallel architectures;AMD Phenom II CPU;CUDA framework;GPU-CPU heterogeneous architectures;GreenGPU;Nvidia GeForce GPU;energy consumption;energy efficiency;high performance computing;holistic approach;Algorithm design and analysis;Computer architecture;Frequency conversion;Graphics processing unit;Green products;Heuristic algorithms;Time frequency analysis;GPU;dynamic frequency scaling;energy efficiency;workload division}, 
 month=sep,
 pages={48-57}, 
 keywords={energy consumption;graphics processing units;parallel architectures;AMD Phenom II CPU;CUDA framework;GPU-CPU heterogeneous architectures;GreenGPU;Nvidia GeForce GPU;energy consumption;energy efficiency;high performance computing;holistic approach;Algorithm design and analysis;Computer architecture;Frequency conversion;Graphics processing unit;Green products;Heuristic algorithms;Time frequency analysis;GPU;dynamic frequency scaling;energy efficiency;workload division}, 

-doi={10.1109/ICPP.2012.31}, 

 ISSN={0190-3918}
 }
 
 ISSN={0190-3918}
 }
 


@@ -689,7 +655,6 @@ year={2013},
 month=oct,
 pages={826-833}, 
 keywords={energy conservation;graphics processing units;parallel processing;power aware computing;power consumption;DVFS schedulers;GPU computing;K20 GPU;Nvidia K20c Kepler GPU;application performance;compute-bound high-performance workloads;dual Intel Sandy Bridge CPU;dynamic voltage and frequency scaling;energy efficiency;high-throughput workloads;power consumption;power-aware heterogeneous system;Benchmark testing;Computer architecture;Energy consumption;Graphics processing units;Market research;Measurement;Power demand;DVFS in GPU Computing;Dynamic Voltage and Frequency Scaling;Energy-Efficient Computing}, 
 month=oct,
 pages={826-833}, 
 keywords={energy conservation;graphics processing units;parallel processing;power aware computing;power consumption;DVFS schedulers;GPU computing;K20 GPU;Nvidia K20c Kepler GPU;application performance;compute-bound high-performance workloads;dual Intel Sandy Bridge CPU;dynamic voltage and frequency scaling;energy efficiency;high-throughput workloads;power consumption;power-aware heterogeneous system;Benchmark testing;Computer architecture;Energy consumption;Graphics processing units;Market research;Measurement;Power demand;DVFS in GPU Computing;Dynamic Voltage and Frequency Scaling;Energy-Efficient Computing}, 

-doi={10.1109/ICPP.2013.98}, 

 ISSN={0190-3918}
 }
 
 ISSN={0190-3918}
 }
 


@@ -700,7 +665,7 @@ ISSN={0190-3918}
        urldate = {2014-10-16},
        institution = {{DTIC} Document},
        author = {Luley, Ryan and Usmail, Courtney and Barnell, Mark},
        urldate = {2014-10-16},
        institution = {{DTIC} Document},
        author = {Luley, Ryan and Usmail, Courtney and Barnell, Mark},

-       year = {2011},
+       year = {2011}

        
 }
 
        
 }
 


@@ -721,7 +686,6 @@ number = "7",
 pages = "1661 - 1670",
 year = "2013",
 issn = "0167-739X",
 pages = "1661 - 1670",
 year = "2013",
 issn = "0167-739X",

-doi = "http://dx.doi.org/10.1016/j.future.2013.02.010",

 author = {Lizhe Wang and Samee U. Khan and Dan Chen and Joanna Kołodziej and Rajiv Ranjan and Cheng-zhong Xu and Albert Zomaya}
 
 
 author = {Lizhe Wang and Samee U. Khan and Dan Chen and Joanna Kołodziej and Rajiv Ranjan and Cheng-zhong Xu and Albert Zomaya}
 
 


@@ -747,8 +711,7 @@ booktitle={International Green Computing Conference and Workshops (IGCC)},
 title={Green governors: A framework for Continuously Adaptive DVFS}, 
 year={2011}, 
 month=jul,
 title={Green governors: A framework for Continuously Adaptive DVFS}, 
 year={2011}, 
 month=jul,

-pages={1-8}, 
-doi={10.1109/IGCC.2011.6008552}
+pages={1-8}

 }
 
 
 }
 
 


@@ -772,7 +735,6 @@ volume={PP},
 number={99},
 pages={1-1},
 keywords={Energy consumption;Optimization;Partitioning algorithms;Processor scheduling;Program processors;Runtime;Time-frequency analysis},
 number={99},
 pages={1-1},
 keywords={Energy consumption;Optimization;Partitioning algorithms;Processor scheduling;Program processors;Runtime;Time-frequency analysis},

-doi={10.1109/TPDS.2014.2313338},

 ISSN={1045-9219},}
 }
 
 ISSN={1045-9219},}
 }
 


@@ -818,7 +780,6 @@ issn={0920-8542},
 journal={The Journal of Supercomputing},
 volume={70},
 number={3},
 journal={The Journal of Supercomputing},
 volume={70},
 number={3},

-doi={10.1007/s11227-014-1236-4},

 title={Energy measurement, modeling, and prediction for processors with frequency scaling},
 publisher={Springer US},
 keywords={Dynamic voltage–frequency scaling; DVFS; SPEC CPU2006 benchmarks; Energy measurement; Energy models},
 title={Energy measurement, modeling, and prediction for processors with frequency scaling},
 publisher={Springer US},
 keywords={Dynamic voltage–frequency scaling; DVFS; SPEC CPU2006 benchmarks; Energy measurement; Energy models},


@@ -845,9 +806,7 @@ journal={Human-centric Computing and Information Sciences},
 eid={28},
 volume={5},
 number={1},
 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},
 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}
 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}


@@ -861,7 +820,6 @@ 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},
 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}
 }
 
 month={Sept}
 }
 


@@ -878,9 +836,7 @@ 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.},
 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},
 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}
 publisher={Springer Berlin Heidelberg},
 author={Nagpal, Rahul and Srikant, Y.N.},
 pages={497-508}