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Arindam Mallik Jack Cosgrove Robert P. Dick Gokhan Memik Peter Dinda Northwestern University...
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![Page 1: Arindam Mallik Jack Cosgrove Robert P. Dick Gokhan Memik Peter Dinda Northwestern University Department of Electrical Engineering and Computer Science.](https://reader031.fdocuments.in/reader031/viewer/2022033107/56649c725503460f949246ce/html5/thumbnails/1.jpg)
Arindam MallikJack CosgroveRobert P. DickGokhan MemikPeter Dinda
Northwestern UniversityDepartment of Electrical Engineering and Computer ScienceEvanston, Illinois, USA
ASPLOS • March 3, 2008 • Seattle, Washington, USA 1
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Traditional performance metrics do not measure user-perceived performance well
Our performance metrics measure user-perceived performance better
PICSEL is a power management policy that uses our metrics to achieve system power improvements of up to 12.1% compared to existing policies
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CPU
Display Main Memory
Screenshot
Compare consecutive screenshots
Change frequency
Redrawscreen
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Display Main Memory
Screenshot
Compare consecutive screenshots
CPU
Change frequency
Redrawscreen
“The ultimate goal of a computer system is to satisfy the user”
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Power problem DVFS
System performance Traditional vs. user-perceived
PICSEL How it works Results
Conclusions
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Energy-hungry processors present three major problems: Higher energy consumption Shorter battery life Higher temperatures
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Dynamic voltage and frequency scaling (DVFS) addresses all three problems Trades off processor frequency for
energy savings Commonly used
Ideal DVFS policy: Find the lowest level of performance acceptable to the user to maximize power savings
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Human in loop is often rate-limiter
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Output Devices
(kHz)User(Hz)
Processor(GHz)
Input Devices(kHz)
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Traditional performance metrics focus on processor performance “Close to metal”
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Output Devices
User
Input Devices
Processor(IPS)
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User-perceived performance metrics focus on interface device performance “Close to flesh”Output Devices
(Display, Speakers)
User(N/A)
Input Devices(Mouse,
Keyboard)
Processor
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Use change in pixel intensities as metric for user-perceived performance
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PerceptionInformedCPU performanceScaling toExtend batteryLife
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Windows GDI Screenshot Capture contiguous area of screen Repeat periodically Compare RGB intensities across samples
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Ri
Gi
Bi
Ri-1
Gi-1
Bi-1
- =
RΔ
G Δ
B Δ
Cached
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Average Pixel Change (APC) APC = (RΔ + GΔ + BΔ) / 3 Averaged across all pixels Measures “slowness” of display
Rate of Average Pixel Change (APR) APR = (APCi – APCi-1)/(Ti – Ti-1) Measures “jitter” of display
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PICSEL uses <2% CPU utilizationCost of target applications is 50-
100% CPU utilization
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APC
APR
Make a decision on these marks
Time
Increase frequency
“No change” band
“No change” band
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State Variables Adaptation Parameters
Processor frequency (f) Hysteresis factor (α)
APC in the last interval (μAPC) APC change threshold (ρ)
APR in the last interval (μAPR) APR change threshold (γ)
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IF (APCinit - μAPC) < ρ ×(1-α) × APCinit
OR |APRinit - μAPR| < γ ×(1-α) × APRinit
Reduce f by one level
Reset α of the last level to 0.0
ELSE
Increase f by one level
Increment α by 0.1
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PICSEL Version Tinitialize
(sec)Tdecide
(sec)APC
ChangeAPR
ChangeHyst.Factor
Conservative PICSEL
(cPICSEL)10 7 0.05 0.15 0.0
Aggressive PICSEL
(aPICSEL)10 7 0.10 0.30 0.0All values chosen by authors after
testing using target applicationsToo long (243 days) to construct
ideal valuesUser evaluation “closed the loop”
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20 users Shockwave animation and DVD movie
play for 2 minutes FIFA game plays for 3.5 minutes Three randomly selected trials per
application One double-blind DVFS policy for each
trial User rates satisfaction from one (lowest)
to five (highest) after each trial
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DVFS Policy
System Power
Improvement
Dynamic Power
Improvement
CPU Peak Temperat
ure Reduction
User Satisfacti
on(out of five)
aPICSEL 12.1% 18.2% 4.3C 3.65*
cPICSEL 7.1% 9.1% 1.7C 3.80**
Windows DVFS
Control Control Control 3.68
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* Not Different with 95% confidence ** Different with 90% confidence
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DVFS Policy
System Power
Improvement
Dynamic Power
Improvement
CPU Peak Temperat
ure Reduction
User Satisfacti
on(out of five)
aPICSEL 12.1% 18.2% 4.3C 3.65*
cPICSEL 7.1% 9.1% 1.7C 3.80**Windows
DVFSControl Control Control 3.68
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* Not Different with 95% confidence ** Different with 90% confidence
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Perceived slowdown
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DVFS PolicyTotal Thermal
Emergencies during Game for All Users
aPICSEL 52
cPICSEL 51
Windows DVFS 59
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User satisfaction is maximized by cPICSEL Frequency is high enough to deliver good
performance but not high enough to trigger thermal emergencies
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Display performance is a better metric for controlling DVFS than processor performance Existing processor performance-based
DVFS policies have slack that can be exploited
Cost of monitoring the display output is low
User satisfaction is the same or better
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Based on GUI events Gurun, S. and Krintz, C. 2005. AutoDVS: an Automatic,
General-purpose, Dynamic Clock Scheduling System for Hand-held Devices. In Proc. of the 5th ACM Int. Conf. on Embedded Software (EMSOFT’05), 218-226.
Based on application messages Flautner, K. and Mudge, T. 2002. Vertigo: Automatic
Performance-Setting for Linux. ACM SIGOPS Operating Systems Review 36, SI (Winter 2002), 105-116.
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Check out “Empathic Computer Architectures and Systems” at Wild and Crazy Ideas and visit
empathicsystems.org
for more user-centered systems research
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