ghosts in the machine: interfaces for better power management
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Ghosts in the Machine:Interfaces for Better Power Management
Manish Anand
Edmund B. Nightingale
Jason Flinn
Electrical Engineering and Computer Science Dept.University of Michigan
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Need for improved power management
Capabilities of mobile handheld devices improving rapidly: Wireless connectivity Storage capacity
Battery capacity improving slowly I/O devices decrease handheld battery lifetime by 60% OEMs provide techniques to reduce battery consumption by
severely compromising the performance Careful power management needed
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Tradeoff between energy and performance
Inherent tradeoff exists between performance and energy conservation
Goals of power management involve:
Lower energy usage
Lower interactive response time (performance)
Time
En
erg
y
Good performance
Extended battery life
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Current device power management
better performance and energy conservation
simplicityMODULARITY
moreless
Problem: Device-centric strategies do not consider the operating environment contexts, such as Base power of mobile computer Activity of other devices Application intent
Our Approach: Provide an infrastructure to expose additional information about operating environment to both applications and devices
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Goals and contributions
Goals: Improve both performance and energy Enable cross-device optimization Allow end users to specify their relative priorities for
performance and energy conservation
Contributions: Simple interfaces to expose additional contexts Power manager for querying device state Self-tuning power management (STPM) modules for disk, n/w Ghost hints for cross-device power management
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Outline Motivation and background Overview of our solution Interfaces for better power management Adaptive caching Evaluation Related work and conclusions
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Review: power management Network Device: 802.11b wireless
CAM – Continuously Active Mode PSM – Power Saving Mode
+ power usage reduced by 70 to 80%
- delay proportional to polling period (100 ms)
Disk Device: IBM/Hitachi microdrive Active Low Power Idle / Standby
+ power usage reduced by 55% / 90%
- transition time of 300ms / 800ms
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Impact of power management
Assumption: Fetching data from local storage is less costly
Web Fetch Time
0
500
1000
1500
2000
2500
0 100 200 300 400 500 600
File Size (KB)
Fet
ch t
ime
(ms)
Disk Standby
Disk Active
Network PSM
Network CAM
Local data access could be more expensive for small files Break-even point is dependent on the state of the device Simple adaptation through cache hierarchy
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Limitation of adaptation
Example: Browser fetching many small images For single image fetching from network is correct For many images fetching from disk is correct
Amortized transition cost over many reads
Problem: Reactive adaptive caching does not help Disk continues to be in standby state
Solution: Apps disclose “accesses that might have been” We use ghost hints to implement this
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Outline Motivation and background Overview of our solution Interfaces for better power management Adaptive caching Evaluation Related work and conclusions
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Energy-aware architecture
Applications
Power Manager
NetworkHints
DeviceCharacteristics & Current State
STPMNetwork
STPMDisk
ModeTransitions
ModeTransitions
Cache Manager
Ghost HintsGhost Hints
Data AccessDecision
Notify NetworkState Change
Notify DiskState Change
Operating System
Disk Device Driver
Network Device Driver
MobiCom ‘03
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Power manager Central repository that maintains information about:
State of the device Performance characteristics of I/O devices Energy characteristics of I/O devices
Power manager interface 3 calls for devices – register, deregister and notify 5 calls for applications – 4 to query device state and
characteristics, 1 for registering callbacks
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Self-tuning power management STPM modules consider:
Application access patterns Base power of mobile computer Energy and performance characteristics of the device Relative priority of performance and energy conservation
STPM modules decide: Time to transition to high power state Time to transition to low power state
Energy conservation
Performance0 100knob
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Disk power management with STPM
Transition to power saving mode employs Break-even heuristic
Disk is likely to remain idle if it has been idle for a period Incorporate the STPM principles
Transition to active mode employs both Reactive strategy
Transition on a request Proactive strategy
Use ghost hints to transition even with no device access
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Ghost hints
Ghost Hint Ghost Hint
Expended Energy between hints
Break-even Threshold
Ghost hints contain opportunity cost in terms of time and energy Issued by the application, when a poor I/O path is chosen due to inappropriate device state
Decrements energy cost of being active between hints Transitions to high performance state on an overflow
state change on overflow
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Cache manager
Keeps the meta-data information in-memory hash table Determines the weighted cost of going to network or disk Maintains a write queue and delays writes to the disk
ApplicationsCache
Manager
Disk
CacheStatus?
network bettern/w fetch
data PutData
flush
ghost hint
STPMModule
PowerManagerdevice state
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Outline Motivation and background Overview of our solution Interfaces for better power management Adaptive caching Evaluation Related work and conclusions
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Evaluation Goals:
Effect of cache manager’s adaptive, cross-device strategy
Influence of global knob
Benefits of ghost hints
Client: iPAQ handheld with Cisco 350 wireless card and IBM/Hitachi microdrive
Test applications:
Email-sync - recorded e-mail activity
Dillo web browser with wwwoffle - Berkeley web traces
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Effectiveness of energy-aware caching
0
100
200
300
400
500
600
700
Average Response Time
(ms)
E-mail Web
Static
Adaptive
0
500
1000
1500
2000
2500
3000
Energy (Joules)
E-mail Web
Equal priority for performance and energy Average response time is reduced by 27% to 42% Total energy usage is reduced by 5% to 9%
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E-mail and web with no ghost hints
STPM modules base their decision solely on device accesses No change for knob value less than 95
k=100
k=99
k=95-0 static
2000
2500
3000
3500
4000
4500
5000
0 200 400 600
Average Response Time(ms)
En
erg
y(J
)
k=100
k=99
k=95-0static
120014001600
1800200022002400
260028003000
0 200 400 600
Average Response Time(ms)
En
erg
y(J
)
E-mail Web
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Importance of ghost hints
Email: Substantial benefit when performance is high priority Web: Less likely to see run of accesses clustered together
k=100
k=99
k=95k=90-0
k=99
k=95-0 static
2000
2500
3000
3500
4000
4500
5000
0 200 400 600
Average Response Time(ms)
En
erg
y(J
)
k=100
k=99
k=95
k=70-0k=90
k=99
k=95-0static
1200140016001800200022002400260028003000
0 200 400 600
Average Response Time(ms)
En
erg
y(J
)
E-mail Web
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Importance of ghost hints
static
knob=50-0knob=70knob=90
knob=95
knob=99
knob=95-0
knob=99
knob=100
2000
2500
3000
3500
4000
4500
5000
0 200 400 600
Average Response Time(ms)
En
erg
y(J)
Web with full cache
Ghost hints show a positive effect on the system
Ghost hints yield substantial benefit for some workloads, and do no harm in the situations where they seem ineffective
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Related work We are the first system to efficiently access data on multiple I/O
Burstiness for energy efficiency (Weissel ’02, Papathanasiou ’03, Heath ‘02)
ACPI: similar to power manager but too complex, does not disclose device characteristics
Wake on Wireless (Shih ’02)
OS level power management (ECOSystem, Odyssey)
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Conclusions
Contributions: Improved power management interfaces: Power manager for querying device state STPM modules for disk, network Ghost hints for cross-device power management
Current work: Modification of cached data Multiple network and storage devices Feedback loop to dynamically set the global knob
Ghosts in the Machine:Interfaces for Better Power Management
Manish Anand
Edmund B. Nightingale
Jason Flinn
Electrical Engineering and Computer Science Dept.University of Michigan
Manish Anand
26
Dynamic Power Management
The energy used by the I/O devices can be prohibitive, without power managementHitachi Microdrive Cisco 350 wireless card
Mode Power Mode Power
Performance Idle 760 mW CAM 1410 mW
Low-Power Idle 340 mW PSM 390 mW
Standby 80 mW
Battery lifetime is decreased by 60% without power management
Drawback of using power management Network device
Delay proportional to the polling period Disk device
Transition cost to switch to active mode (300ms to 800ms)
ghostrealized disk spin-up
PSMswitch
CAMswitch
Network access Disk access
ghost hints STPM disk hints
STPM network hints
Applications
Disk
Network
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Network Power Management with STPM
STPM network switches from PSM to CAM when: Application specifies max delay < beacon period Disclosed transfer size > break-even size Many forthcoming transfers are likely
To predict forthcoming transfers STPM network generates an empirical distribution of run lengths
>150 ms >150 ms>150 ms
Transfers
Run Run Run Run
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