Early Lessons from Energy-Saving Storage Systems Research
Sara Alspaugh and Arka Bhattacharya
Saving Energy At the Block Device Level
SSD Opportunities and Challenges
Exploring the Design Space
Takeaways
Redundancy: reconstruct request from parity group on active disks and cache
(Examples: RIMAC, Diverted Access, PARAID, EERAID)
Caching and Layout: keep less frequently accessed data on spun down disks, eject blocks to active disks
(Examples: MAID, PA-LRU, PB-LRU, Hibernator, EED, PDC)
Multispeed Disks: adjust disk speed according to workload demands and performance requirements
(Examples: Hibernator, DPRM)
Device Idle Seq. Read Seq. Write Ran. Read Ran. Write
Corsair F60 (Consumer SSD)
0.70 W 0.80 W 228Mb/sec
0.99W 195Mb/sec 0.75 W 229 Mb/sec 0.98 W 194 Mb/sec
Intel X25-E Extreme (Enterprise SSD)
0.60 W 1.51 W200Mb/sec
2.70 W158Mb/sec
1.51W201 Mb/sec
2.71 W186 Mb/sec
Seagate Momentus XT (Hybrid SSD)
1.63 W 3.46W104Mb/sec
3.03W90Mb/sec
3.41 W 96 Mb/sec
2.97W88 Mb/sec
Western Digital 1600BEVS (HDD)
2.26 W 2.27W59Mb/sec
3.34W43Mb/sec
3.58W36 Mb/sec
3.17W36 Mb/sec
Scheme Block Device / RAID Level
File System Level
Fixed Thresh-hold
Pred-ictive Erasure Codes (RAID5)
Mirror-ing (RAID1)
Write Logging
Access Freq.-Based Layout
Solid State Devices
Multi-speed Disks
Hybrid / Tiered
DIV-ACC X X X X
EERAID1 X X X X
EERAID5 X X X X X
RIMAC X X X X
PARAID X X X X
PDC X X X
PA-LRU X X X
PB-LRU X X X X
HIBERN X X X X X X
DPRM X X X X
WOL X X X X X X
MAID X X X X
SSD-RAID X X X X X X
EED X X X X X X
SIERRA X X X X
RABBIT X X X X X
Effects of Workload Characteristics
Choosing the Best Scheme
Left: Idle periods longer than 10 seconds represent opportunities to spin down disks to save power.
Right: Most workloads display a high degree of skew. In this MSR build server trace, 75% of the requests go to 35% of the blocks.
Increased skew results in decreased latency, but write-dominated workloads have lower latencies than their read-dominated counterparts – an artifact of DiskSim.
When caching-based techniques are used especially with SSDs, power and performance are correlated.
Comparison of 95th percentile latencies for varying cache replacement algorithms and number of SSDs.
Most promising: hybrid of SSDs and traditional disks, place most frequently accessed data on SSDs (does not preclude use of redundancy-based techniques)
Cache- and layout-based strategies that reduce power consumption also improve performance; redundancy-based strategies do not have this effect
Assumptions about the workload play an important role
SSDs not a panacea: cost, black box flash translation layer
Future WorkOptimizations: prefetching, zero-copy
Using file system and above level knowledge (super challenge: co-located storage and computation)
Considerations of cost and capacity requirements
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