Commit 815fc1b9b8096898e6f7ff0912987699c5f8ab8f

Authored by Rizwana Begum
1 parent 0a83da7a

final submission pdf

inefficiency.tex
@@ -53,7 +53,7 @@ minimum energy it requires. @@ -53,7 +53,7 @@ minimum energy it requires.
53 % 53 %
54 We define the ratio of application's energy consumption ($E$) and the minimum 54 We define the ratio of application's energy consumption ($E$) and the minimum
55 energy the application could have consumed ($E_{min}$) on the same device as 55 energy the application could have consumed ($E_{min}$) on the same device as
56 -inefficiency: $I = \frac{E}{E_{min}}$ 56 +inefficiency: $I = \frac{E}{E_{min}}$.
57 % 57 %
58 An \textit{inefficiency} of $1$ represents an application's most efficient 58 An \textit{inefficiency} of $1$ represents an application's most efficient
59 execution, while $1.5$ indicate the the application consumed $50\%$ more 59 execution, while $1.5$ indicate the the application consumed $50\%$ more
@@ -78,19 +78,27 @@ constraints for real systems: @@ -78,19 +78,27 @@ constraints for real systems:
78 \end{enumerate} 78 \end{enumerate}
79 79
80 We continue by addressing these questions. 80 We continue by addressing these questions.
81 -  
82 \subsection{Inefficiency Bounds and Inefficiency Budget} 81 \subsection{Inefficiency Bounds and Inefficiency Budget}
83 -  
84 % 27 Apr 2015 : GWA : I didn't understand this. 82 % 27 Apr 2015 : GWA : I didn't understand this.
85 83
86 % We argue that absolute value of $I_{max}$ is irrelevant because, even when 84 % We argue that absolute value of $I_{max}$ is irrelevant because, even when
87 % energy is unconstrained, algorithms should focus on delivering the best 85 % energy is unconstrained, algorithms should focus on delivering the best
88 % performance. 86 % performance.
89 -  
90 Devices will operate between an inefficiency of 1 and $I_{max}$ which 87 Devices will operate between an inefficiency of 1 and $I_{max}$ which
91 represents the unbounded energy constraint allowing the application to 88 represents the unbounded energy constraint allowing the application to
92 consume unbounded energy to deliver the best performance. 89 consume unbounded energy to deliver the best performance.
93 % 90 %
  91 +$I_{max}$ depends upon applications and devices.
  92 +%
  93 +We argue that absolute value of $I_{max}$ is irrelevant
  94 +because, when energy is unconstrained, algorithms can burn unbounded energy and
  95 +only focus on
  96 +delivering the best performance.
  97 +%
  98 +The inefficiency budget matters the most when application has bounded energy
  99 +constraints and it can be set by the user or the applications.
  100 +%For example, an inefficiency budget of 1.2 means that the user is willing to lose 20\% more energy to execute the application.
  101 +%
94 The OS can also set the inefficiency budget based on application's priority 102 The OS can also set the inefficiency budget based on application's priority
95 allowing the higher priority applications to burn more energy than lower 103 allowing the higher priority applications to burn more energy than lower
96 priority applications. 104 priority applications.
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