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"Achieving Flash Memory's Full Potential" @ Flash Memory Summit 2012


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Tutorial Description:
Big data, virtualization, OLTP systems, and a host of performance-intensive applications have led to much greater use of flash memory in data centers. Data center managers and engineers must therefore focus on when to use flash memory, how to keep costs at a reasonable level, and where to employ flash (whether in caches, in tiers, or as main storage). This session focuses on why flash is being used and what benefits it brings to data centers.

The impact of flash memory in data center infrastructure
Benefits of flash technology
Flash and the data center ecosystem
Growing flash utilization within data centers and IT infrastructures

Intended Audience:
Storage specialists; storage engineers; data center, network, and storage managers; product designers and managers; system analysts; computer managers and engineers; data center engineers

Published in: Technology, Business
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"Achieving Flash Memory's Full Potential" @ Flash Memory Summit 2012

  1. 1. Achieving Flash Memory’s Full Potential Darpan Dinker Senior Director, Engineering SanDiskFlash Memory Summit 2012Santa Clara, CA 1
  2. 2. Forward Looking StatementDuring our meeting today we will be making forward-looking statements.Any statement that refers to expectations, projections or othercharacterizations of future events or circumstances is a forward-lookingstatement, including those relating to revenue, pricing, market share, marketgrowth, product sales, industry trends, expenses, gross margin, futurememory technology, production capacity and technology transitions and futureproducts.Actual results may differ materially from those expressed in these forward-looking statements due to the factors detailed under the caption “RiskFactors” and elsewhere in the documents we file from time-to-time with theSEC, including our annual and quarterly reports.We undertake no obligation to update these forward-looking statements,which speak only as of the date hereof. Flash Memory Summit 2012 2 Santa Clara, CA
  3. 3. Agenda§  Flash memory application in the data-center§  Why focus on balanced systems§  Architectural approaches to exploit flash§  Scenarios to leverage flash§  Lessons learned Flash Memory Summit 2012 3 Santa Clara, CA
  4. 4. Flash Memory Applicationin Data Centers VDI Cloud DatabasesVirtualization Hadoop Big Data SharePoint Multi-tier storage NoSQLSAN NAS Memcached MongoDB Exchange MySQL Flash Memory Summit 2012 4 Santa Clara, CA
  5. 5. Why Focus on Balanced Systems 10 ms§  CPU Magnetic Storage 1 ms§  Main-Memory Remote memory 100 µs Flash memory§  Storage 10GbE, InfiniBand 10 µs§  Network PCIe 1 µs 100 ns DRAM 10 ns CPU Cache CPU Register 1 ns Flash Memory Summit 2012 5 Santa Clara, CA
  6. 6. Architectural Approaches to ExploitingFlash Memory1.  Augment main-memory •  Directly (mmap, system paging, custom kernel) Memcached •  Indirectly (object cache) Flash Memory Summit 2012 6 Santa Clara, CA
  7. 7. Architectural Approaches to ExploitingFlash Memory1.  Augment main-memory •  Directly (mmap, system paging, custom kernel) •  Indirectly (object cache)2.  Cache blocks of magnetic storage •  Disjoint from storage (WB or WT) •  Integrated with storage Flash Memory Summit 2012 7 Santa Clara, CA
  8. 8. Architectural Approaches to ExploitingFlash Memory1.  Augment main-memory •  Directly (mmap, system paging, custom kernel) •  Indirectly (object cache)2.  Cache blocks of magnetic storage •  Disjoint from storage (WB or WT) •  Integrated with storage3.  Replace magnetic storage •  DAS •  NAS or SAN Flash Memory Summit 2012 8 Santa Clara, CA
  9. 9. Scenarios for Leveraging Flash Memory1.  Applications are IO bound2.  Lots of random IO3.  Prepare for data growth4.  Heavily virtualized environment5.  Prepare for unpredictable load6.  Improved response time / SLAs7.  Improved reliability8.  Save on space, power, cooling Flash Memory Summit 2012 9 Santa Clara, CA
  10. 10. Scenarios for Leveraging Flash Memory1. Applications are IO bound§  Common symptoms •  Low CPU usage •  High io-wait •  Sluggish response time (are locks to blame?) Flash Memory Summit 2012 10 Santa Clara, CA
  11. 11. Scenarios for Leveraging Flash Memory2. Lots of random IO Databases§  Magnetic drive heads cannot MongoDB keep up with random IO (~200 IOPS/drive) MySQL§  Common symptoms observed with ‘iostat’ •  High IO service time, queue size, wait time •  Low IO bandwidth Flash Memory Summit 2012 11 Santa Clara, CA
  12. 12. Scenarios for Leveraging Flash Memory3. Prepare for data growth Big Data§  Data growth can increase demand for IO Hadoop§  Common symptoms •  Database queries slow down as table size increases •  Wrong trends observed with ‘iostat’ as data grows Flash Memory Summit 2012 12 Santa Clara, CA
  13. 13. Scenarios for Leveraging Flash Memory4. Heavily virtualized environment Cloud§  Individual VMs with low IO requirements build up a heavy VDI IO workload for a shared storage Virtualization system§  Many individual sequential accesses create a random IO workload§  IO path is not particularly optimized in VMs Flash Memory Summit 2012 13 Santa Clara, CA
  14. 14. Scenarios for Leveraging Flash Memory5. Prepare for unpredictable load§  DAS with magnetic disks have SAN limited upper bound for IOPS. In order to size systems for peak NAS load, the “work” per server may require substantial throttling à resulting in underperforming servers Flash Memory Summit 2012 14 Santa Clara, CA
  15. 15. Scenarios for Leveraging Flash Memory6. Improved response time / SLAs§  Many applications require disk SharePoint access. Disk access can be responsible for significant portion Exchange of the response time§  Sequential and random access times are asymmetric for magnetic drives. Defining SLAs is thus non trivial Flash Memory Summit 2012 15 Santa Clara, CA
  16. 16. Scenarios for Leveraging Flash Memory7. Improved reliability§  Moving mechanical parts make magnetic drives quite susceptible to failure. RAID is a common practice even if data is made redundant on another server Flash Memory Summit 2012 16 Santa Clara, CA
  17. 17. Scenarios for Leveraging Flash Memory8. Save on space, power, cooling§  Magnetic drives take power and dissipate a lot of heat (>10X that of flash memory)§  Random IOPS are expensive with magnetic drives Flash Memory Summit 2012 17 Santa Clara, CA
  18. 18. Lessons Learned:Don’t Trust the Folk Lore§  Can observe response time and throughput improvements for most IO-bound workloads after exploiting flash, but… •  Nothing close to 100X theoretical improvement (5-10ms à 50-100µs) •  Most existing software applications unable to push IOPS •  May observe “write cliff” for workloads with heavy writes Flash Memory Summit 2012 18 Santa Clara, CA
  19. 19. Lessons Learned:Your Mileage May Vary §  Workload: DBT2 open-source OLTP version of TPC-C 75 •  1000 warehouses, 32 connections •  0 think-time #2 •  Result metric: TPM (new order)TPM (in thousands) 50 §  Measurement Configuration •  2 node Master-Slave configuration 25 •  2 socket 6C Westmere, #1 72GB DRAM 0 #1 Replace HDD with flash MySQL 5.5 SchoonerSQL #2 Understand application architecture & design. HDD Flash Re-implement portions and integrate with flash. Flash Memory Summit 2012 19 Santa Clara, CA
  20. 20. Lessons Learned:Tweak or Rewrite Application SW§  Tips •  Consider bypassing OS IO schedulers (noop) •  When IO throughput is more important, employ larger block size •  Target keeping high number of outstanding IOs§  To push 10k-50k IOPS, tweak storage access layer of application§  To push 50k+ IOPS, consider rewriting parallelization and storage access layer Flash Memory Summit 2012 20 Santa Clara, CA
  21. 21. Lessons Learned:Know the Technology§  Consumer grade vs. enterprise grade device§  Random writes and non-uniform size writes •  Algorithmic differences between vendors for space and wear management§  IOPS is not everything in production •  Determine distribution and sustained latency •  Does the device really offer “durability”?§  Compression in devices fare differently based on data (e.g. jpeg, mpeg)§  Monitor SMART metrics Flash Memory Summit 2012 21 Santa Clara, CA
  22. 22. Lessons Learned:Know About the Form Factor§  1 SAS with 1 PCIe flash device is apples : oranges comparison for throughput§  SAS/SATA based flash •  Easier to RAID •  Typically hot swappable and easy to replace •  Not all HBAs are built to match flash memory speeds§  PCIe based flash •  Typically offer IOs with lower latency •  Convenient to add to existing systems for caching Flash Memory Summit 2012 22 Santa Clara, CA
  23. 23. acquiresF R E E YOUR DATAJune 21, 2012 Flash Memory Summit 2012 23 Santa Clara, CA
  24. 24. SanDisk Flash-Accelerated Products Schooner Membrain Enterprise NoSQL Cache/Store SchoonerSQL Enterprise SQL DatabaseFlashSoft™ Caching software Enterprise Storage CachingLightning® SAS Enterprise SSD Enterprise Flash HardwareLightning® PCIe Enterprise SSA Flash Memory Summit 2012 24 Santa Clara, CA