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![Page 1: 1 Conserving Energy in RAID Systems with Conventional Disks Dong Li, Jun Wang Dept. of Computer Science & Engineering University of Nebraska-Lincoln Peter.](https://reader036.fdocuments.in/reader036/viewer/2022072005/56649cda5503460f949a3f9c/html5/thumbnails/1.jpg)
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Conserving Energy in RAID Systems with Conventional Disks
Dong Li, Jun WangDept. of Computer Science & Engineering
University of Nebraska-LincolnPeter Varman
Dept. of Electrical and Computer EngineeringRice University
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References[1] S. Gurumurthi, A. Sivasubramaniam, M. Kandemir, and H. Franke,
“DRPM: dynamic speed control for power management in server class disks,” ISCA’03
[2] D. Colarelli and D. Grunwald, “Massive arrays of idle disks for storage archives,” in Proceedings of Super Computing’ 2002
[3] E. Pinheiro and R. Bianchini, “Energy conservation techniques for disk array-based servers,” in Proceedings of the 18th International Conference on Supercomputing, 2004
[4] E. Varki, A. Merchant, J. Z. Xu, and X. Z. Qiu, “Issues and challenges in the performance analysis of real disk arrays,” IEEE Transactions on Parallel and Distributed Systems, 2004.
[5] D. Li and J. Wang, “EERAID: Energy-efficient redundant and inexpensive disk array,” in Proceedings of 11th ACM SIGOPS European Workshop, 2004.
[6] D. Li, H. Cai, X. Yao, and J. Wang, “Exploiting redundancy to construct energy-efficient, high-performance RAIDs,” Tech. Rep. TR-05-07-04, Computer Science and Engineering Department, University of Nebraska Lincoln, 2005.
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Outline
Introduction Motivation eRAID Design Evaluation Leveraging eRAID Conclusions
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Introduction
Energy-efficient storage system, total cost of ownership (TCO), …
Short request inter-arrival time Long disk state switch time of conventional disks Current solutions: multi-speed disks[1] Create long idle period for conventional disks
unbalance workloads Two approaches
Relocating data: MAID[2], PDC[3] Redirecting requests: EERAID[5]
• Introduction
• Motivation
• Evaluation
• Conclusions
• Leveraging
• Design
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Motivation
Major limitations of state of the art few workable solutions for conventional disk base
d systems single performance measurement no differentiation of workload time criticality
Three observations redundant information of RAID systems spare service capacity queueing model
• Introduction
• Motivation
• Evaluation
• Conclusions
• Leveraging
• Design
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eRAID Design Main idea
spin down, partially or entirely, mirror disks to standby read, write
Features soft solution --- no hardware change consider two performance metrics
Research issue maximize energy saving without violating predefined performance degradation
limits for both throughput and response time assume workloads have little change between two
consecutive time windows
• Introduction
• Motivation
• Evaluation
• Conclusions
• Leveraging
• Design
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Solving for Performance Degradation Our approach: using queueing models to do predictions
1. model RAID-1 system and get performance measures
2. examine how the input parameters are changed
3. get new performance measures with changed input parameters
4. compare these two results
Four workloads: synchronous read (SR), asynchronous read (AR), synchronous write (SW) and asynchronous write (AW)
Real system: HP SureStore E Disk Array FC60
• Introduction
• Motivation
• Evaluation
• Conclusions
• Leveraging
• Design
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Read Load Models
• Introduction
• Motivation
• Evaluation
• Conclusions
• Leveraging
• Design
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Read Load Performance Computing The possible changes of input parameters:
disk access probability disk service time --- negligible
Synchronous read load: Mean Value Analysis (MVA) technique eRAID --- double access probabilities of corresponding pri
mary disks Asynchronous read load:
no throughput degradation for stable systems eRAID --- double work loads of corresponding primary disk
s
• Introduction
• Motivation
• Evaluation
• Conclusions
• Leveraging
• Design
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Write Load Model
• Introduction
• Motivation
• Evaluation
• Conclusions
• Leveraging
• Design
Controller cache write back policy
FC60: two-threshold write back policy destage_threshold, max_ditry
Disk array: M/M/1/K queueing model[4]
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Write Load Performance Computing Dirty data arrival rate d
SW load: d= * cache_miss_rate : max throughput with infinite cache size
AW load: d= * cache_miss_rate independent with the system
The possible changes of input parameters: service rate: N/2 => (N-2i)/2 maximum queue length cache miss rate --- unnoticeable
• Introduction
• Motivation
• Evaluation
• Conclusions
• Leveraging
• Design
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Solving for Energy Saving
N-disk RAID1 Time window length T Request number R Mean service time t
Asyn. load: 2=1
Sync. load: 2<1
NT
tR11
• Introduction
• Motivation
• Evaluation
• Conclusions
• Leveraging
• Design
1
21
)(
)())((
iai
wwssiia
base
eRAIDbaseE PPP
TTPTP
PNi
PP
E
EES
EeRAID= Eactive+Eidle+Estandby+Eswitch
(N-i) disks i disks
N disks
Ebase = Eactive+Eidle
NT
tR22
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Control Algorithm
Time-window Solve multi-constraint
problem: select LFU disks
Conservative control
• Introduction
• Motivation
• Evaluation
• Conclusions
• Leveraging
• Design
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Evaluation
Disk power model: IBM Ultrastar 36Z15 Simulator: augmented Disksim Traces: Cello99 and TPC-C20 8-disk RAID1 system Two scenarios
• Introduction
• Motivation
• Evaluation
• Conclusions
• Leveraging
• Design
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Preliminary Results
• Introduction
• Motivation
• Evaluation
• Conclusions
• Leveraging
• Design
CASE I: LimitT10% & LimitX3%Load Overall DT Overall DX Overall SE
AR 7.5% 0.0% 10.2%SR 7.1% 1.5% 11.8%AW 4.3% 0.0% 13.3%SW 0.0% 0.0% 0.0%
CASE II: LimitT50% & LimitX6%Load Overall DT Overall DX Overall SE
AR 29.5% 0.0% 30.0%SR 25.9% 4.6% 27.7%AW 14.3% 0.0% 23.5%SW 41.4% 1.6% 7.4%
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Leveraging eRAID
Associate a load threshold f (1/2<f<1) for each disk when primary disk load exceeds f, spin up mirror disk to
share the load conventional mirrored layout: spin up one mirror disk our new layout: spin up less than one mirror disk
Layout files of one primary disk to a set of mirror disks
• Introduction
• Motivation
• Evaluation
• Conclusions
• Leveraging
• Design
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An example: N=10 and f=2/3
• Introduction
• Motivation
• Evaluation
• Conclusions
• Leveraging
• Design
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Conclusions
An energy saving policy, eRAID, for conventional disk based RAID-1 systems
30% energy-saving without violating predefined performance constraints
A new data layout scheme for further energy-saving Limitations
circumscribed by the accuracy of queueing models approximated input parameters, e.g. process number and
mean process delay conservative control
• Introduction
• Motivation
• Evaluation
• Conclusions
• Leveraging
• Design
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Thank you!
Questions?
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Creating Disk Idle Period in RAID-5: An Example
4-disk RAID 5 system A parity group containing data stripe 1, 2, 3 and
parity stripe p that are saved in disk 1, 2, 3 and 4 respectively
There is a read request for stripe 1. To service such a read, we could either read stripe 1 from disk 1, or read stripe 2, 3 and p, then calculate stripe 1 on the fly by an XOR calculation.
More details can be found in our technical report[6]