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Repairing Write Performance on Flash Devices

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Final DaMoN presentation ... Radu Stoica , Manos Athanassoulis , Ryan Johnson , Anastasia Ailamaki – PowerPoint PPT presentation

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Title: Repairing Write Performance on Flash Devices


1
Repairing Write Performance on Flash Devices
  • Radu Stoica, Manos Athanassoulis, Ryan
    Johnson,
  • Anastasia Ailamaki

Ecole Polytechnique Fédérale de
Lausanne Carnegie Mellon
2
Tape is Dead, Disk is Tape, Flash is Disk
  • Slowly replacing HDDs (price , capacity )
  • Fast, reliable, efficient
  • Potentially huge impact
  • Slow random write
  • Read/write asymmetry
  • -gt not a HDD drop-in replacement

Jim Gray, CIDR 2007
3
DBMS I/O today
Request
DBMS
Data requirements
HDD optimized I/O pattern
Block Device API
Flash optimized I/O pattern
Flash device
Flash memory access
Inadequate device abstraction
Flash devices are not HDD drop-in replacements
4
Random Writes Fusion ioDrive
  • Microbenchmark 8 kiB random writes

Unpredictability
94 performance drop
5
Stabilizing Random Writes
  • Change data placement
  • Flash friendly I/O pattern
  • Avoid all random writes
  • Minimal changes to database engine
  • 6-9x speedup for OLTP-like access patterns

6
Overview
  • Random Write how big of a problem?
  • Random Write why still a problem?
  • Append-Pack Data Placement
  • Experimental results

7
Related work
Request
DBMS
Data requirements
Flash-opt. DB Algs.
HDD optimized I/O pattern
Data placement
Block Device API
Flash FS
Flash optimized I/O pattern
Flash device
FTL
Flash memory access
No solution for OLTP workloads
8
Random Write Other devices
Vendor advertised performance
Rand. Write Rand. Read
Mtron SSD
Rand. Write causes unpredictability
Graph from uFlip, Bouganim et al. CIDR 2009
9
Random Writes Fusion ioDrive
  • Microbenchmark 8 kiB random writes

10
Sequential Writes Fusion ioDrive
  • Microbenchmark 128kiB sequential write

Seq. Writing Good Stable Performance
11
Idea Change Data Placement
  • Flash friendly I/O pattern
  • Avoid all Random Writes
  • Write in big chunks
  • Tradeoffs additional work
  • Give up seq. reads (SR and RR similar
    performance)
  • More seq. writing
  • Other overheads

12
Overview
  • Random Write how big of a problem?
  • Random Write why still a problem?
  • Append-Pack Data Placement
  • Theoretical model
  • Experimental results

13
Append-Pack Algorithm
Update page
Update page
Update page
No more space
Write hot dataset
Write seq.
Reclaim space
No in-place updates
Filter cold pages
Write cold dataset
Reclaim space
Log start
Valid page
Log end
Invalid page
How much additional work?
14
Theoretical Page Reclaiming Overhead
  • Update pages uniformly
  • Equal prob. to replace a page
  • valid pages?

prob(valid) f (a) ? e -a
a
Worst case 36 Easily achievable 6-11
15
Theoretical Speedup
  • Traditional Random Write I/O latency TRW
  • New latency TSWprob(valid)(TRR TSW)
  • Conservative assumption TRW 10TSW

a sizeof(device) / sizeof(data)
Up to 7x speedup
16
Overview
  • RW how big of a problem?
  • RW why still a problem?
  • Append-Pack Data Layout
  • Experimental results

17
Experimental setup
  • 4x Quad-core Opteron
  • X86_64-linux v2.6.18
  • Fusion ioDrive 160GB PCIe
  • 8 kiB I/Os, Direct I/O
  • Parallel threads 16
  • Firmware runs on host
  • Append-Pack implemented as shim library

18
OLTP microbenchmark
  • Microbenchmark 50 Rand Write / 50 Rand Read

FTL?
9x improvement
Time (s)
19
OLTP Microbenchmark Overview
Performance better than predicted
20
What to remember
  • Flash ? HDD
  • We leverage
  • Sequential Writing to avoid Random Writing
  • Random Reading as good as Sequential Reading
  • Append-pack eliminate Random Writes
  • 6-9x speedup

21
  • Thank you!
  • http//dias.epfl.ch

22
Backup
23
FTLs
  • Fully-associative sector translation Lee et al.
    07
  • Superblock FTL Kang et el. 06
  • Locality-Aware Sector Translation Lee et al.
    08
  • No solution for all workloads
  • Static tradeoffs workload independence
  • Lack of semantic knowledge
  • Wrong I/O patterns
  • -gt complicated software layers destroy
    predictability

24
Flash FS
  • Flash aware file systems
  • JFFS2
  • YAFFS
  • No FTL required (handle wear leveling)
  • Mostly for embedded devices

25
Other Flash Devices - Backup
Device RR (IOPS) RW (IOPS) SW (MB/s) SR (MB/s)
Intel x25-E 35,000 3,300 170 250
Memoright GT 10,000 500 130 120
Solidware 10,000 1,000 110 110
Fusion ioDrive 116,046 93,199 (75/25 mix) 750 670
Vendor advertised performance
26
Experimental Results - Backup
RR/RW Baseline Append/Pack Speedup Prediction
50/50 38 MiB/s 349 MiB/s 9.1 6.2
75/25 48 MiB/s 397 MiB/s 8.3 4.3
90/10 131 MiB/s 541 MiB/s 4.1 2.5
(a 2 in all experiments)
27
OLTP microbenchmark - Backup
50 RW/50 RR - before
  • 50 RW/50 RR - after

28
OLTP Microbenchmark - Backup
Traditional I/O
29
OLTP Microbenchmark - Backup
Append-Pack
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