impact of power-management granularity on the energy-quality trade-off for soft and hard real-time...
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Impact of Power-Management Granularity on The Energy-Quality
Trade-off for Soft And Hard Real-Time ApplicationsInternational Symposium on System-on-Chip, 2008
A. Milutinovic, K. Goossens, and G.J.M. Smit
Advisor: Shiann-Rong KuangSpeaker: Hao-Yi Jheng (鄭浩逸 )
2009.2.26
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Outline Introduction
Application model Work and slack
Policy Conservativeness and Granularity Experimental Results Conclusions
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Application model
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In this paper they evaluate two power-management policies for a number of different granularities on an MPEG4 application, on energy and quality (deadline misses). Granularity (N) : frequency of operating point
changes
Hard real-time applications Don’t allow any frame miss deadline Use conservative power-management
Soft real-time applications Allow a limited number of frame miss deadline Use non-conservative power-management
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Work and slack
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Work : the number of processor cycles Relative deadline :
Relative deadline miss means this frame over deadline
Relative slack (r) :
Absolute deadline :
Absolute deadline miss means that the accumulative execution time frame 0 to i is over the total deadline
Absolute slack(s) :
1/i FRacet T f
i ir T acet
0
i
jjacet iT
0( 1)
i
i jjs i T acet
deadlineT actual execution time /i i iacet w f
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Outline
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Introduction Application model Work and slack
Policy Conservativeness and Granularity Experimental Results Conclusions
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Conservative Policy Conservative power-management policy :
Does not introduce any deadline misses compared to operating at .
Non-conservative power-management policy : Some frames maybe miss it’s deadline.
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maxf
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Policy
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Perfect predictor policy (non-conservative) : Accurately predicts the next N frames workload and
scaled the average frequency for those frame
Proven slack policy (conservative) : Proven slack : the cumulative slack of the frames
before it Assume that the next N frames all require the worst-
case work, but use all the proven slack of previous group to reduce the frequency of the processor
1
*0( ) / ( ) for group
i
N
avg i N jjf w NT i
max 0 1( ) / ( ) for group i j j if NMax w NT s i
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Outline
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Introduction Application model Work and slack
Policy Conservativeness and Granularity Experimental Results Conclusions
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Experimental Results (1/5) An MPEG4 decoder running on an ARM946 at
86 MHz 25 frames per second (fps), and a resolution
of 176*144 pixel
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Experimental Results (2/5) Energy savings w.r.t. operating at are around 30%
for 1-128 frames 2% cost for the power management Above 128 frames the proven-slack policy energy
linearly raise
maxf
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Experimental Results (3/5)
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The proven-slack policy cannot always exploit the accumulated slack
Average slack :
Worst-case slack :
1
0/ , for a sequence of S frames
S
iis S
10 , for a sequence of S framesS
i iMax s
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Experimental Results (4/5)
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Perfect predictor policy : 95% quality improvement costs only 3% additional energy Optimum is 13000 mJ
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Experimental Results (5/5)
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Many frames can be processed in the range of 240-250 MHz.
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Outline
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Introduction Application model Work and slack
Policy Conservativeness and Granularity Experimental Results Conclusions
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Conclusions
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1. A long tail in the work distribution results in a steep quality improvement : from almost 0% to almost 100% at an additional energy cost of only 3%.
2. The proven-slack policy offers 100% quality at only 0.3% more energy than the perfect-predictor policy, which is theoretical upper bound and hard to achieve in practice.
3. The energy of the policies increases by only 2% when increasing the granularity to 128 frames.
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Conclusions Non-conservation
Conservation Tardiness
(sum of frame delay time / frame number)/deadline
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2arg
1
( ),
Niact t et
iiact i
fps fpsi
FRV fpsN T
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Comparison
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Progress report
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Advisor: Shiann-Rong Kuang
Speaker: Hao-Yi Jheng
2009.2.23
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Outline Adaptive Inter-compensation
How to choose voltage/frequency level Adaptive Experimental Result
Future Work
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How to choose voltage/frequency level
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5.83 3.57 1.16 1.52 1.30 0.08 0.97
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Why need inter-compensation
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Inter-compensation PID
Adaptive inter-compensation If (previous frame predictive cycle number is more
cycles) current frame predictive voltage level decreases one
else current frame predictive voltage doesn’t change
If( ) = 2000
else = 27000
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ii w-w(t)( ) ( )1( ) ( )
I
Di p
T D
t t TK t t D
I T
1 ii i
( ) ( )IT
t t
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Inter-compensation
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Experimental Result
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Energy(e+08)
No-inter 2000 27000 adaptive
API_00 2.13389 1.89694 2.10778 1.98991
API_01 1.41421 1.18232 1.25112 1.23007
API_02 2.57939 2.20497 2.34232 2.29719
API_03 1.65572 1.4108 1.49139 1.45527
API_04 2.20379 1.88178 2.06792 1.99084
API_05 1.24353 1.04672 1.16125 1.11097
FRV No-inter 2000 27000 adaptive
API_00 66.2636 32.0008 76.9116 39.8287
API_01 35.9665 8.86423
0.5415340.281196
API_02 24.9081 6.53828 1.00831 1.28403
API_03 41.9968 12.2053 0.341697 1.0757
API_04 18.3523 7.35752 3.91522 1.03591
API_05 25.4673 26.3545 1.5618 3.66423
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Future Work We need Hardware GM and RM cycle numbers
to verify the experimental Result
Driver is needed to support the GM and RM dump cycle number for prediction
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