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final submission pdf
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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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