Extending Datacenter Capacity To Drive ROI

Transcription

1 Extending Datacenter Capacity To Drive ROI Ajay Bhatia Director, Product Marketing Management Aug 6, 2014 Flash Memory Summit 2014 Santa Clara, CA 1

2 Hyperscale Datacenters & Adoption 2013 Enterprise s Over $3B USD* *Forward Insights

3 Flash in Datacenters IOPS (K) Typical IOPS/Drive 40 $3.00 $2.00 Typical $/GB $1.00 $ Flash is clearly faster than s IOPS (K) Typical IOPS/$ However $/GB alone is too high to replace all s Although the performance tier has over 5x better performance/$

4 Flash in Datacenters IOPS (K) Typical IOPS/Drive What if you could triple the capacity of the same flash? You Flash get is the clearly same performance faster than over Typical s IOPS/$ IOPS (K) $3.00 $2.00 $1.00 $0.00 Typical $/GB The However $/GB $/GB drops alone to is a third too high to replace all s Although And the the performance tier tier is has 16x over higher 5x per better $ performance/$

5 Is this really feasible in an? Most data does not have 100% entropy and data reduction helps Linux Web hosting distributions Show ~% entropy 1 Binaries and Shared Libraries Database entropy as low as only ~30% 2 html pst Oracle exe xls doc pdf dll ppt pptx xlsx docx jpg mp3 Entropy by file type 3 3% 24% 30% 32% 32% 35% 49% 57% 65% 85% 87% 96% 98% 98% 0% 25% 50% 75% 100% Entropy 1 LSI calculations on Oracle Database solutions Measured by WinZip

6 Is this really feasible in an? Most data does not have 100% entropy and data reduction helps Entropy by file type 3 html pst Oracle exe xls doc pdf dll ppt pptx xlsx docx jpg mp3 3% 24% 30% 32% 32% 35% 49% 57% 65% 85% 87% 96% 98% 98% 0% 25% 50% 75% 100% Entropy 1 LSI calculations on Oracle Database solutions Measured by WinZip

7 On-the-fly Compression Issues Compression Engine Location All Locations CPU Issue Need some level of predictable entropy Operating systems today don t understand variable max capacity Expensive resource and limited max throughput No variable mapping table; assumes 1:1 map from host FTL must be re-architected to support non-constant data size Solution / Concern Datacenters now have more knowledge of their data Customize drivers or modify already custom OS Use a device-based solution Major re-architecting required Complex FTL must be created for data placement, garbage collection, etc. This is not a simple problem to solve

8 What s today support variable map sizes? LSI SandForce Flash Controllers employ DuraWrite data reduction Manages variable-size data placement on the flash DuraWrite Feature Incorporates a novel Flash Translation Layer (FTL) Supports variable data length Provides for multiple flash page sizes to support variable code rate Benefit Handles variable-sized data for writing, reading, and garbage collection Manages data spanning flash page boundaries to maximize space utilization Incoming data size not restricted to be a power-of-two Each LBAs can be a unique size Working in conjunction with SHIELD technology

9 LSI DuraWrite Virtual Capacity (DVC) Oracle Database Application Raw Physical Capacity Projected Capacity from LSI DVC x 1x 2x 3x 4x Capacity DVC greatly lowers the $/GB of available capacity to the user Source: Projection based on LSI internal testing of Oracle database entropy. Results published in LSI white paper, Using DuraWrite Technology to Accelerates Flash Performance and Extend Write Lifetimes on the Nytro WarpDrive Application Acceleration Card, 2012

10 DVC Explained Speed & Endurance Enterprise Data Drive Extra user data space 30% entropy database Minimize costs % entropy boot drive 120 GB User Data 8 GB OP 120 GB User Data 8 GB OP 88GB User Data 8 GB OP 128 GB 128 GB 96GB 120 GB User Data in 40GB 1 88 GB Dynamic OP 120 GB User Data in 40GB 1 Gives 80 GB More Space for User Data 8 GB OP 120GB of data 2 8 GB OP Greater Dynamic Over Provisioning increases performance and endurance Database actually sees 3GB of high performance Able to use a lower cost solution 1 Assumes a 33% entropy. Actual size reduction dependent upon data entropy. 2 Assumes a % entropy. Actual size reduction dependent upon data entropy.

11 DVC Use Cases Use Case Native User Data Storage Dynamic Caching What Pros Cons Support Market Additional flash space appears as a user accessible User capacity increases for same flash cost Requires OS driver changes Easier with Linux or custom OS LSI Nytro product line Select SandForce Driven program s Enterprise with custom OS or Linux Client with Linux Additional flash space managed by caching application Increases cache size for same flash cost No OS changes Requires integrated caching application LSI Nytro product line Select SandForce Driven program s Enterprise focus

12 Summary