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Driving IMC Compu/ng Efficiency with Flash Extended Memory Dan Baigent, Sr Director Strategic Partner Ecosystems June 30, 2015
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Forward-‐Looking Statements
During our mee;ng today we will make forward-‐looking statements.
Any statement that refers to expecta;ons, projec;ons or other characteriza;ons of future events or circumstances is a forward-‐looking statement, including those rela;ng to market growth, products and their capabili;es, performance and compa;bility, cost savings and other benefits to customers. Informa;on in this presenta;on may also include or be based upon informa;on from third par;es, which reflects their expecta;ons and projec;ons as of the date of issuance.
We undertake no obliga;on to update these forward-‐looking statements, which speak only as of the date hereof.
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Widening Performance Gap
1990 1995 2000 2005 2010 2015
Server CPU Performance
Mega Trend: Legacy Storage I/O BoKleneck
Aligning Performance
SSD Performance
HDD Performance
Source: StorageIOblog; Sep 2009; hSp://storageioblog.com/data-‐center-‐io-‐boSlenecks-‐performance-‐issues-‐and-‐impacts/
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Non-‐Vola/le Memory (NVM) ! Today: NAND Flash
– Capacity: 100s of GB to 100s of TB per device – Trends: Higher capacity, lower cost/GB, lower write cycles, SLC-‐>MLC-‐>3BPC
– IOPS: 100K to millions, GB/s of bandwidth
! Tomorrow: Non-‐Vola;le Memory technologies (Phase Change Memory, MRAM, STT-‐RAM, etc.)
– Poten;al for orders of magnitude performance improvement
Fusion ioMemory™ PCIe
SAS and SATA SSDs
InfiniFlash™ System
SanDisk ION Accelerator™
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Why Do Applica/ons Need Op/miza/on for Flash? ! Many applica;ons assume high latency storage (some even op;mize for read/write head posi;oning)
! Flash is different from disk – Performance, endurance, addressing – Geeng more different over ;me
! Flash-‐focused applica;on accelera;on – Shifing boSlenecks (Compute to I/O to
Network to Applica;on) – Managed writes = greater device life;me
(wear leveling, endurance) – Improved system efficiency (TCO and TCA) – Even lower power and cooling costs
Area Hard Disk Drives Flash Devices
Read/Write Performance
Largely symmetrical
Heavily asymmetrical.
Sequen;al vs Random Performance
100x difference. <10x difference.
Background ops Rare Regular
Wear out Largely unlimited Limited writes
IOPS 100s to 1,000s 100Ks to Millions
Latency 10s milli sec 10s-‐100s micro sec
Addressing Sequence, Sector
Direct, byte addressable
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Becoming “Flash Aware”: SanDisk NVMFS
Value ! Increase life expectancy of flash devices ! Consistent low latency ! Consistent high performance
How ! Reducing MySQL™ Writes to flash ! Op;mize IO Write path for flash ! Applica;ons leverage enhanced I/O interface
Available today!
Non-‐Vola;le Memory File System – Op;mized for Flash and Beyond
Native Flash Translation Layer block allocation, mapping, recycling
ACID updates, logging/journaling, crash-recovery
NVMFS file metadata mgmt
Kernel block layer
kernel-space user-space
Standard Linux File Systems file metadata mgmt,
block allocation, mapping, recycling,
ACID updates, logging/journaling, crash-recovery
Flash Primitives
MySQL™ Database
Linux VFS (virtual file system) abstraction layer
New File system
Elimina;ng Duplicate Logic and Leveraging New Primi;ves for Op;mal Flash Performance and Efficiency
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Persistent Storage
In-‐Memory Database and Persistence Checkpoints, Logs and Data Tiering, Oh My!
Logs
Mem Image Checkpoints
State Changes
Transac'ons over Time
Warm Data
Data Tiering
Backup Systems
In-‐Memory Compute
(transac/ons, processing, analy/cs)
“Hot Data”
Persistent Snapshots
Transac;on Commit
Restore Data into memory
Backup and Archiving
Possible wait condi;ons
Logs
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Emergence of Flash Extended Memory
Flash Devices Memory Persistent Memory HDDs
Memory Addressable and I/O Addressable
“Flash as Memory”
“Flash as Disk”
Tradi;onal Block I/O
Storage Device Technologies:
Flash Extended Memory
Decoupling of the physical infrastructure (memory) from the management and u/liza/on of that infrastructure through a so[ware interface
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Flash Extended Memory Example: MongoDB – Lowering TCO through transparent DRAM/Flash /ering
MongoDB Throughput (opera;ons/second)
0 2000 4000 6000 8000
24 GB Node 12 GB Node 8 GB Node
-‐26% -‐33%
Throughput Devia;on (opera;ons/second)
0 100 200 300 400
24 GB Node 12 GB Node 8 GB Node
3x Improvement
YCSB Workload A
DRAM reduc;ons of 2x and 3x yield 26% and 33% throughput degrada;ons respec;vely. Throughput predictability actually improves with less DRAM. Latency shows similar trend.
Source: Based on internal tes;ng by SanDisk; Nov 2014
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RA New Memory-‐Storage Hierarchy
Range of persistence –
I/O becomes Load-‐Store
Storage Memory Convergence: Rethinking the Memory Hierarchy
L1, L2, L3 CPU Caches DRAM Persistent Memories Flash Hard Drive
Mic r o s e cond s Nano s e cond s
CYCLES TO WAIT
Main Memory System High Performance I/O System
Accessed Like Memory and Managed Like Storage
Mi l l i s e c ond s
ACCESS DELAY
2 c y c l e s 4 m i l l i o n c y c l e s
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Implica/ons for Applica/ons ! Extremely low latency transac;on commits
– 10-‐100us reduced to <1us
! Accelerate logs, indexes etc. ! Convergence of in-‐memory and disk approaches
– New data structures to op;mize directly for memory access
! Rich variety of programming models – Tradi;onal I/O will s;ll be available – Mmap directly to persistent memory is alterna;ve model: use pointer opera;ons to
manipulate persistent data – SNIA Non-‐Vola;le Memory Programming TWG – standardize mmap for persistent memory
! New challenges – CPU cache management – Atomicity?
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Technology Preview: Database Accelera/on Through Flash Extended Memory
NVMFS (POSIX compliant file system) ACM (Auto-‐Commit Memory) So[ware
• A “transparent” Sofware Defined Memory layer can provide accelerated I/O over a “baseline” unaware interface
• But “flash-‐aware” applica;ons can op;mize that accelera;on
Flash Devices Memory Persistent Memory
Memory Device Technologies:
Memory Interfaces
Oracle MySQL™
(No applica;on changes) (Applica;on op;mized)
“Flash -‐Aware” “Transparent”
Flash Extended Memory
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Technology Preview Example Configura/on
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HP ProLiant DL380 Gen8
Fusion ioMemory™ PCIe-‐based flash
Standard MySQL database
“Baseline”
Flash Extended Memory Enabled
Standard Flash Accelera/on
HP ProLiant DL380 Gen8
Fusion ioMemory™ and persistent memory with
NVMFS
Standard MySQL database
“Transparent”
NVMFS and ACM
HP ProLiant DL380 Gen8
Op/mized MySQL database
“Flash Aware”
NVMFS and ACM
Fusion ioMemory™ and persistent memory with
NVMFS
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Performance Results
Latency (lower is beSer)
Throughput (higher is beSer)
Source: Based on internal tes;ng by SanDisk; Nov 2014
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Advantages & Benefits ! Improve “Baseline” MySQL throughput performance by roughly
60% via “Transparent” accelera;on (no sofware mods)
! Op;mize MySQL throughput performance by over 3x with “Flash Aware” accelera;on (modified sofware)
! Improve “Baseline” MySQL latency by roughly 2.3x (Transparent) and op;mized latency by more than 4x (Flash Aware)
! Uses “Flash-‐as-‐Memory” byte-‐addressable architecture and interface
! Seamless deployment – add ioMemory and NVMFS/ACM sofware to Linux
! Increase performance and capacity in flexible configura;ons Source: Based on internal tes;ng by SanDisk; Nov 2014
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Restore Data into memory
Backup and Archiving
In-‐Memory Compu/ng – New Approach to I/O
Backup Systems
In-‐Memory Compute (transac/ons, processing, analy/cs)
“Hot Data”
Transac'ons over Time
Persistence via CPU Load/Store
POSIX File System
Persistent Storage Flash Extended Memory
Persistent Memory
Memory Flash Devices
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Thank You! @BigDataFlash #bigdataflash
ITblog.sandisk.com hSp://bigdataflash.sandisk.com
©2015 SanDisk Corpora;on. All rights reserved. SanDisk is a trademark of SanDisk Corpora;on, registered in the United States and other countries. InfiniFlash, SanDisk ION Accelerator, Fusion ioMemory, ioDrive, Cloudspeed MAX, Op;mus MAX and Lightning Ultra are trademarks of SanDisk Enterprise IP LLC. All other product and company names are used for iden;fica;on purposes and may be trademarks of their respec;ve holder(s).
