Leveraging Performance and Power Savings for Embedded Systems
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Transcript of Leveraging Performance and Power Savings for Embedded Systems
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LEVERAGING PERFORMANCE ANDPOWER SAVINGS FOR EMBEDDED
SYSTEMS USING MULTIPLE TARGETDEADLINES
Presentation By:
DHANESH.M.S
Roll.No:2007
M.Tech (Electronics) with specialization inVLSI and Embedded systems
Guided By:
Mr.MANU.T.SLecturer
Dept. of ECE
TKI, Karuvelil
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CONTENTS:
INTRODUCTION
DVFS
TGPM-ALL FLOWCHART
FLOW CHART EXPLANATION TGPM-ALL ALGORITHM
TGPM-N FLOWCHART
TGPM-N ALGORITHM
PERFORMANCE COMPARISON
CONCLUSION
REFERENCES2
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INTRODUCTION:
Increasing the performance is one of thefundamental aim of embedded system design.
Our aim is to increase performance while keepingenergy consumption low.
To achieve this we define TGPM algorithm.
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DYNAMIC VOLTAGE AND FREQUENCYSCALING(DVFS):
P f V2
V f
P f 3
3 approaches: interval, inter-task , intra-task
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TGPM-ALL ALGORITHM.
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TGPM-ALLFLOW CHART:
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Pre processing steps
Queue
Compute f*
All constraints
met ?
Remove all test casesFrom queue.
Execute task at f*
Start
stop
Remove that testcases from queue.
Is queueempty ?
Execute task at full
speed.
Yes
YesNo
No
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PREPROCESSING STEP:
Task(Ti) Task cases(Tij)Dij , Pij , tij
tij = tijon + tij
off
Pass these values to a queue.
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Case P(ij
) tij
on tij
off Dij
i1 0.1 40 0 100
i2 0.1 10.001 0 20
i3 0.1 10 0 20
i4 0.3 30 0 60
i5 0.4 20 0 40
Case P(ij) t
ij
on tij
off Dij
i1 0.1 40 0 100
i23 0.2 10. 0 20
i4 0.3 30 0 60
i5 0.4 20 0 40
Case P(ij) t
ij
on tij
off Dij
i23 0.2 10 0 20
i5 0.4 20 0 40
i4 0.3 30 0 60
i1 0.1 40 0 100
Case P(ij) t
ij
on tij
off Dij
i5 0.4 20 0 40
i4 0.3 30 0 60
i1 0.1 40 0 100
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VERIFICATION:
Checks whether task gets completed as expected.
If yes, remove all other task case from the queueand operate at this frequency.
If No, remove that task case from the queue andrepeat this algorithm.
If queue is empty, operate at full speed.
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TGPM-ALL ALGORITHM:
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COMPLEXITY:
Checks test cases until appropriate test cases areselected.
If no: of test cases are very large and no test casegives correct frequency, then after examining all thetest case task has to be completed at full speed.
This will increase the complexity with out anybenefit.
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TGPM-N ALGORITHM.
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Pre processing steps & k=0
Queue
Compute f*
All constraintsmet ?
Remove all test casesFrom queue.
Execute task at f*
Start
stop
Remove that testcases from
queue,k=k+1
Is queueempty ?
Execute task at full
speed.
Yes
Yes
No
No
Yes
NoIs k=N?
TGPM-NFLOW CHART:
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This algorithm keeps track of the number of failedtest case attempts for task T.
If it meets the predefined value N, it will discardremaining test cases for the task.
Execute the task at full speed until completion.
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TGPM-N ALGORITHM
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PERFORMANCE COMPARISON;
EFFECTS OF Poff,C AND ti*off
Effects of these parameters are similar on allDVFS-based power management schemes.
As (poff
/pon
(f)) increases, off-chip componentsconsume relatively more energy.
Increased switching capacitance (C) and off-chipworkload reduce energy-efficient frequencies.
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EFFECTS OF TEST CASE SIZE ON ENERGYCONSUMPTION.
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TGPM-ALL slowly deteriorates as the number oftest cases and failed test cases increases.
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EFFECTS OF SLACKS ON ENERGYCONSUMPTION.
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TGPM-ALL and BEST have very similar sensitivity toavailable slacks.
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EFFECTS OF TEST CASE SIZE ONEFFICINCENCY.
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TGPM-1 ensures shorter completion of tasks andefficient frequency assignment by switching to fullspeed after the most probable test case fails to hold.
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CONCLUSION:
TGPM algorithm is introduced to increaseperformance while keeping energy consumptionlow
There are two versions of this algorithm TGPM-ALLand TGPM-N
Can save up to 60% of CPU power by using thisalgorithm.
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REFERENCES:
i. Edward Y. Y. Kan , W. K. Chan and T. H. Tse.Leveraging Performance and Power Savings forEmbedded Systems using Multiple TargetDeadlines, Quality Software (QSIC), 2010 10th
International Conference, IEEE.ii. T. K. Tan , A. Raghunathan , and N. K. Jha.
Embedded Operating System Energy Analysisand Macro-modeling, IEEE.
iii. S. Boyd and L. Vandenberghe. Convex
Optimization. Cambridge University Press,Cambridge, 2004.
iv. http://www.stanford.edu/class/ee364b/lectures/trunc_newton_slides.pdf 21
http://ieeexplore.ieee.org/xpl/mostRecentIssue.jsp?punumber=5562736http://ieeexplore.ieee.org/xpl/mostRecentIssue.jsp?punumber=5562736http://ieeexplore.ieee.org/xpl/mostRecentIssue.jsp?punumber=5562736http://ieeexplore.ieee.org/xpl/mostRecentIssue.jsp?punumber=5562736