SlideShare a Scribd company logo
1 of 6
Download to read offline
SSD Benchmark Testing Panel


         Shirish Jamthe
 Director of System Engineering
     Virident Systems, Inc.
           August 2011
Performance Characterization
                        Methodology
Focus on sustained performance and application-level metrics
•   Level 1: Baseline performance
•   Level 2: Sustained performance and IO-QoS metrics
•   Level 3: Application performance and real-world workloads

Performance
                                                                QD=1     QD=128




      Specified Performance   “Seasoned” Device     Mixed read-write        Device filled to capacity,
                                                  (Databases, Caching,          Continuous GC
                                                                                                         Workload
                                                  Metadata serving, …)                                   Conditions
I/O Quality of Service

Measure of latency in real world scenarios
•   Mixed Read/Write workload sustained over time
•   Mixed Read/Writes of various block sizes that simulate real workloads
Baseline Performance

•   Sweep across 10+ parameters (6000+ data points on OS, system, card combo)
     •   Operation mix: Reads, Writes, R+W mix; sequential, random; aligned/unaligned
     •   Block sizes: 512B – 1M; Threads/Queue-depth: 1-256; File system types: (Linux) ext3, xfs
     •   Card configs: Capacity-optimized, Performance-optimized, Balanced; With and without RAID
     •   With and without garbage collection, …


•   Measurements: Bandwidth, IOPS, Latency, Latency Standard Deviation, System resource
    overheads
Application Tests With Real-World
                 Workloads…
Measure performance in real life scenario with varying application settings
•   Simulated DB workloads: ORION, SysBench, SQLIO, …
•   Oracle: Flash cache, Preferred Read, ASM store on TPCC, TPCH, Calling circle etc.
•   MySQL: Varying cache sizes, buffered writes vs. direct, OLTP, TPCC




                                                                  Competition
                                                                  Virident
Virident Systems, Inc.
        Booth #416

        Shirish Jamthe
Director of System Engineering
    Virident Systems, Inc.
          August 2011

More Related Content

What's hot

MongoDB Evenings Boston - An Update on MongoDB's WiredTiger Storage Engine
MongoDB Evenings Boston - An Update on MongoDB's WiredTiger Storage EngineMongoDB Evenings Boston - An Update on MongoDB's WiredTiger Storage Engine
MongoDB Evenings Boston - An Update on MongoDB's WiredTiger Storage EngineMongoDB
 
20141206 4 q14_dataconference_i_am_your_db
20141206 4 q14_dataconference_i_am_your_db20141206 4 q14_dataconference_i_am_your_db
20141206 4 q14_dataconference_i_am_your_dbhyeongchae lee
 
WiredTiger Overview
WiredTiger OverviewWiredTiger Overview
WiredTiger OverviewWiredTiger
 
Microsoft azure for sql server professionals
Microsoft azure for sql server professionalsMicrosoft azure for sql server professionals
Microsoft azure for sql server professionalsArmando Lacerda
 
In-Memory Computing: How, Why? and common Patterns
In-Memory Computing: How, Why? and common PatternsIn-Memory Computing: How, Why? and common Patterns
In-Memory Computing: How, Why? and common PatternsSrinath Perera
 
인메모리 클러스터링 아키텍처
인메모리 클러스터링 아키텍처인메모리 클러스터링 아키텍처
인메모리 클러스터링 아키텍처Jaehong Cheon
 
MongoDB Internals
MongoDB InternalsMongoDB Internals
MongoDB InternalsSiraj Memon
 
Webinar: Introduction to MongoDB 3.0
Webinar: Introduction to MongoDB 3.0Webinar: Introduction to MongoDB 3.0
Webinar: Introduction to MongoDB 3.0MongoDB
 
Load testing Cassandra applications
Load testing Cassandra applicationsLoad testing Cassandra applications
Load testing Cassandra applicationsBen Slater
 
Running deep neural nets in your Java application with Deeplearning4j
Running deep neural nets in your Java application with Deeplearning4jRunning deep neural nets in your Java application with Deeplearning4j
Running deep neural nets in your Java application with Deeplearning4jAlexander Fedintsev
 
Azure intoduksjon for it pro 02 data protection public
Azure intoduksjon for it pro 02 data protection publicAzure intoduksjon for it pro 02 data protection public
Azure intoduksjon for it pro 02 data protection publicMorgan Simonsen
 
SQL Server 2014 Hybrid Cloud Features
SQL Server 2014 Hybrid Cloud FeaturesSQL Server 2014 Hybrid Cloud Features
SQL Server 2014 Hybrid Cloud FeaturesGuillermo Caicedo
 
Ops Jumpstart: MongoDB Administration 101
Ops Jumpstart: MongoDB Administration 101Ops Jumpstart: MongoDB Administration 101
Ops Jumpstart: MongoDB Administration 101MongoDB
 
IMC Summit 2016 Breakout - Andy Pavlo - What Non-Volatile Memory Means for th...
IMC Summit 2016 Breakout - Andy Pavlo - What Non-Volatile Memory Means for th...IMC Summit 2016 Breakout - Andy Pavlo - What Non-Volatile Memory Means for th...
IMC Summit 2016 Breakout - Andy Pavlo - What Non-Volatile Memory Means for th...In-Memory Computing Summit
 
[Pgday.Seoul 2018] 이기종 DB에서 PostgreSQL로의 Migration을 위한 DB2PG
[Pgday.Seoul 2018]  이기종 DB에서 PostgreSQL로의 Migration을 위한 DB2PG[Pgday.Seoul 2018]  이기종 DB에서 PostgreSQL로의 Migration을 위한 DB2PG
[Pgday.Seoul 2018] 이기종 DB에서 PostgreSQL로의 Migration을 위한 DB2PGPgDay.Seoul
 
Times Ten in-memory database when time counts - Laszlo Ludas
Times Ten in-memory database when time counts - Laszlo LudasTimes Ten in-memory database when time counts - Laszlo Ludas
Times Ten in-memory database when time counts - Laszlo LudasORACLE USER GROUP ESTONIA
 
MongoDB WiredTiger Internals
MongoDB WiredTiger InternalsMongoDB WiredTiger Internals
MongoDB WiredTiger InternalsNorberto Leite
 
Integrating your network with windows azure
Integrating your network with windows azureIntegrating your network with windows azure
Integrating your network with windows azureMorgan Simonsen
 
IMC Summit 2016 Breakout - Per Minoborg - Work with Multiple Hot Terabytes in...
IMC Summit 2016 Breakout - Per Minoborg - Work with Multiple Hot Terabytes in...IMC Summit 2016 Breakout - Per Minoborg - Work with Multiple Hot Terabytes in...
IMC Summit 2016 Breakout - Per Minoborg - Work with Multiple Hot Terabytes in...In-Memory Computing Summit
 

What's hot (20)

MongoDB Evenings Boston - An Update on MongoDB's WiredTiger Storage Engine
MongoDB Evenings Boston - An Update on MongoDB's WiredTiger Storage EngineMongoDB Evenings Boston - An Update on MongoDB's WiredTiger Storage Engine
MongoDB Evenings Boston - An Update on MongoDB's WiredTiger Storage Engine
 
20141206 4 q14_dataconference_i_am_your_db
20141206 4 q14_dataconference_i_am_your_db20141206 4 q14_dataconference_i_am_your_db
20141206 4 q14_dataconference_i_am_your_db
 
WiredTiger Overview
WiredTiger OverviewWiredTiger Overview
WiredTiger Overview
 
Microsoft azure for sql server professionals
Microsoft azure for sql server professionalsMicrosoft azure for sql server professionals
Microsoft azure for sql server professionals
 
In-Memory Computing: How, Why? and common Patterns
In-Memory Computing: How, Why? and common PatternsIn-Memory Computing: How, Why? and common Patterns
In-Memory Computing: How, Why? and common Patterns
 
인메모리 클러스터링 아키텍처
인메모리 클러스터링 아키텍처인메모리 클러스터링 아키텍처
인메모리 클러스터링 아키텍처
 
MongoDB Internals
MongoDB InternalsMongoDB Internals
MongoDB Internals
 
Webinar: Introduction to MongoDB 3.0
Webinar: Introduction to MongoDB 3.0Webinar: Introduction to MongoDB 3.0
Webinar: Introduction to MongoDB 3.0
 
Load testing Cassandra applications
Load testing Cassandra applicationsLoad testing Cassandra applications
Load testing Cassandra applications
 
Running deep neural nets in your Java application with Deeplearning4j
Running deep neural nets in your Java application with Deeplearning4jRunning deep neural nets in your Java application with Deeplearning4j
Running deep neural nets in your Java application with Deeplearning4j
 
Azure intoduksjon for it pro 02 data protection public
Azure intoduksjon for it pro 02 data protection publicAzure intoduksjon for it pro 02 data protection public
Azure intoduksjon for it pro 02 data protection public
 
SQL Server 2014 Hybrid Cloud Features
SQL Server 2014 Hybrid Cloud FeaturesSQL Server 2014 Hybrid Cloud Features
SQL Server 2014 Hybrid Cloud Features
 
Ops Jumpstart: MongoDB Administration 101
Ops Jumpstart: MongoDB Administration 101Ops Jumpstart: MongoDB Administration 101
Ops Jumpstart: MongoDB Administration 101
 
IMC Summit 2016 Breakout - Andy Pavlo - What Non-Volatile Memory Means for th...
IMC Summit 2016 Breakout - Andy Pavlo - What Non-Volatile Memory Means for th...IMC Summit 2016 Breakout - Andy Pavlo - What Non-Volatile Memory Means for th...
IMC Summit 2016 Breakout - Andy Pavlo - What Non-Volatile Memory Means for th...
 
[Pgday.Seoul 2018] 이기종 DB에서 PostgreSQL로의 Migration을 위한 DB2PG
[Pgday.Seoul 2018]  이기종 DB에서 PostgreSQL로의 Migration을 위한 DB2PG[Pgday.Seoul 2018]  이기종 DB에서 PostgreSQL로의 Migration을 위한 DB2PG
[Pgday.Seoul 2018] 이기종 DB에서 PostgreSQL로의 Migration을 위한 DB2PG
 
Times Ten in-memory database when time counts - Laszlo Ludas
Times Ten in-memory database when time counts - Laszlo LudasTimes Ten in-memory database when time counts - Laszlo Ludas
Times Ten in-memory database when time counts - Laszlo Ludas
 
MongoDB WiredTiger Internals
MongoDB WiredTiger InternalsMongoDB WiredTiger Internals
MongoDB WiredTiger Internals
 
Windows Azure Virtual Machines
Windows Azure Virtual MachinesWindows Azure Virtual Machines
Windows Azure Virtual Machines
 
Integrating your network with windows azure
Integrating your network with windows azureIntegrating your network with windows azure
Integrating your network with windows azure
 
IMC Summit 2016 Breakout - Per Minoborg - Work with Multiple Hot Terabytes in...
IMC Summit 2016 Breakout - Per Minoborg - Work with Multiple Hot Terabytes in...IMC Summit 2016 Breakout - Per Minoborg - Work with Multiple Hot Terabytes in...
IMC Summit 2016 Breakout - Per Minoborg - Work with Multiple Hot Terabytes in...
 

Viewers also liked

BEM it! Introduction to BEM
BEM it! Introduction to BEMBEM it! Introduction to BEM
BEM it! Introduction to BEMVarya Stepanova
 
Introduction & Session 1 - Innovation
Introduction & Session 1 - InnovationIntroduction & Session 1 - Innovation
Introduction & Session 1 - InnovationThe Digital Insurer
 
Sample Work
Sample WorkSample Work
Sample Workbjm190
 
Lessons for Africa’s Integration inspired by the EU Integration
Lessons for Africa’s Integration inspired by the EU IntegrationLessons for Africa’s Integration inspired by the EU Integration
Lessons for Africa’s Integration inspired by the EU IntegrationGaia Manco
 
ระเบียบคลัง1 3
ระเบียบคลัง1 3ระเบียบคลัง1 3
ระเบียบคลัง1 3Rpg Thailand
 
Session 4 - Startup InsurTech Asia Award
Session 4 - Startup InsurTech Asia AwardSession 4 - Startup InsurTech Asia Award
Session 4 - Startup InsurTech Asia AwardThe Digital Insurer
 
Powerpoint rationale
Powerpoint rationalePowerpoint rationale
Powerpoint rationaleKeppsy
 
JavaScript в БЭМ терминах
JavaScript в БЭМ терминахJavaScript в БЭМ терминах
JavaScript в БЭМ терминахVarya Stepanova
 
A2 examen et corrige edu isl 2010 1-am t2
A2 examen et corrige edu isl 2010 1-am t2A2 examen et corrige edu isl 2010 1-am t2
A2 examen et corrige edu isl 2010 1-am t2Ahmed Mesellem
 
презентация Монтессори-центра
презентация Монтессори-центрапрезентация Монтессори-центра
презентация Монтессори-центраMarisha Romanova
 
DTC Lab Kickoff: Data Viz Content Mashup Agnes Chang (NY Times R&D Lab) Talk
DTC Lab Kickoff: Data Viz Content Mashup Agnes Chang (NY Times R&D Lab) Talk DTC Lab Kickoff: Data Viz Content Mashup Agnes Chang (NY Times R&D Lab) Talk
DTC Lab Kickoff: Data Viz Content Mashup Agnes Chang (NY Times R&D Lab) Talk DTC Lab
 
Cultual Olympiad
Cultual OlympiadCultual Olympiad
Cultual Olympiadjoelyp
 
Sistemes informatics
Sistemes informaticsSistemes informatics
Sistemes informaticsEilaRuiz
 

Viewers also liked (20)

BEM it! Introduction to BEM
BEM it! Introduction to BEMBEM it! Introduction to BEM
BEM it! Introduction to BEM
 
Introduction & Session 1 - Innovation
Introduction & Session 1 - InnovationIntroduction & Session 1 - Innovation
Introduction & Session 1 - Innovation
 
Sample Work
Sample WorkSample Work
Sample Work
 
Lessons for Africa’s Integration inspired by the EU Integration
Lessons for Africa’s Integration inspired by the EU IntegrationLessons for Africa’s Integration inspired by the EU Integration
Lessons for Africa’s Integration inspired by the EU Integration
 
ระเบียบคลัง1 3
ระเบียบคลัง1 3ระเบียบคลัง1 3
ระเบียบคลัง1 3
 
trabajo 16/09/11
trabajo 16/09/11trabajo 16/09/11
trabajo 16/09/11
 
Session 4 - Startup InsurTech Asia Award
Session 4 - Startup InsurTech Asia AwardSession 4 - Startup InsurTech Asia Award
Session 4 - Startup InsurTech Asia Award
 
Powerpoint rationale
Powerpoint rationalePowerpoint rationale
Powerpoint rationale
 
Numbers activities
Numbers activitiesNumbers activities
Numbers activities
 
JavaScript в БЭМ терминах
JavaScript в БЭМ терминахJavaScript в БЭМ терминах
JavaScript в БЭМ терминах
 
Foss intro-sep-2016
Foss intro-sep-2016Foss intro-sep-2016
Foss intro-sep-2016
 
Dr. death
Dr. deathDr. death
Dr. death
 
Unit plan sittie2
Unit plan sittie2Unit plan sittie2
Unit plan sittie2
 
Session 7 - Poll
Session 7 - PollSession 7 - Poll
Session 7 - Poll
 
A2 examen et corrige edu isl 2010 1-am t2
A2 examen et corrige edu isl 2010 1-am t2A2 examen et corrige edu isl 2010 1-am t2
A2 examen et corrige edu isl 2010 1-am t2
 
презентация Монтессори-центра
презентация Монтессори-центрапрезентация Монтессори-центра
презентация Монтессори-центра
 
DTC Lab Kickoff: Data Viz Content Mashup Agnes Chang (NY Times R&D Lab) Talk
DTC Lab Kickoff: Data Viz Content Mashup Agnes Chang (NY Times R&D Lab) Talk DTC Lab Kickoff: Data Viz Content Mashup Agnes Chang (NY Times R&D Lab) Talk
DTC Lab Kickoff: Data Viz Content Mashup Agnes Chang (NY Times R&D Lab) Talk
 
Mpeg Powerpoint
Mpeg PowerpointMpeg Powerpoint
Mpeg Powerpoint
 
Cultual Olympiad
Cultual OlympiadCultual Olympiad
Cultual Olympiad
 
Sistemes informatics
Sistemes informaticsSistemes informatics
Sistemes informatics
 

Similar to SSD Performance Benchmarking

Engineering practices in big data storage and processing
Engineering practices in big data storage and processingEngineering practices in big data storage and processing
Engineering practices in big data storage and processingSchubert Zhang
 
GPU Acceleration for Financial Services
GPU Acceleration for Financial ServicesGPU Acceleration for Financial Services
GPU Acceleration for Financial ServicesKinetica
 
DAT101 Understanding AWS Database Options - AWS re: Invent 2012
DAT101 Understanding AWS Database Options - AWS re: Invent 2012DAT101 Understanding AWS Database Options - AWS re: Invent 2012
DAT101 Understanding AWS Database Options - AWS re: Invent 2012Amazon Web Services
 
Millions quotes per second in pure java
Millions quotes per second in pure javaMillions quotes per second in pure java
Millions quotes per second in pure javaRoman Elizarov
 
Scotas - Oracle Open World Sao Pablo
Scotas - Oracle Open World Sao PabloScotas - Oracle Open World Sao Pablo
Scotas - Oracle Open World Sao PabloJulian Arocena
 
Complex Er[jl]ang Processing with StreamBase
Complex Er[jl]ang Processing with StreamBaseComplex Er[jl]ang Processing with StreamBase
Complex Er[jl]ang Processing with StreamBasedarach
 
The Art & Sience of Optimization
The Art & Sience of OptimizationThe Art & Sience of Optimization
The Art & Sience of OptimizationHertzel Karbasi
 
Accelerating big data with ioMemory and Cisco UCS and NOSQL
Accelerating big data with ioMemory and Cisco UCS and NOSQLAccelerating big data with ioMemory and Cisco UCS and NOSQL
Accelerating big data with ioMemory and Cisco UCS and NOSQLSumeet Bansal
 
Processing Big Data
Processing Big DataProcessing Big Data
Processing Big Datacwensel
 
MySQL Cluster Scaling to a Billion Queries
MySQL Cluster Scaling to a Billion QueriesMySQL Cluster Scaling to a Billion Queries
MySQL Cluster Scaling to a Billion QueriesBernd Ocklin
 
Streaming Solutions for Real time problems
Streaming Solutions for Real time problemsStreaming Solutions for Real time problems
Streaming Solutions for Real time problemsAbhishek Gupta
 
Know More About Rational Performance - Snehamoy K
Know More About Rational Performance - Snehamoy KKnow More About Rational Performance - Snehamoy K
Know More About Rational Performance - Snehamoy KRoopa Nadkarni
 
3 know more_about_rational_performance_tester_8-1-snehamoy_k
3 know more_about_rational_performance_tester_8-1-snehamoy_k3 know more_about_rational_performance_tester_8-1-snehamoy_k
3 know more_about_rational_performance_tester_8-1-snehamoy_kIBM
 
Kognitio overview jan 2013
Kognitio overview jan 2013Kognitio overview jan 2013
Kognitio overview jan 2013Kognitio
 
Kognitio overview jan 2013
Kognitio overview jan 2013Kognitio overview jan 2013
Kognitio overview jan 2013Michael Hiskey
 
Overcoming the Top Four Challenges to Real-Time Performance in Large-Scale, D...
Overcoming the Top Four Challenges to Real-Time Performance in Large-Scale, D...Overcoming the Top Four Challenges to Real-Time Performance in Large-Scale, D...
Overcoming the Top Four Challenges to Real-Time Performance in Large-Scale, D...SL Corporation
 
Fixing twitter
Fixing twitterFixing twitter
Fixing twitterRoger Xia
 

Similar to SSD Performance Benchmarking (20)

Engineering practices in big data storage and processing
Engineering practices in big data storage and processingEngineering practices in big data storage and processing
Engineering practices in big data storage and processing
 
GPU Acceleration for Financial Services
GPU Acceleration for Financial ServicesGPU Acceleration for Financial Services
GPU Acceleration for Financial Services
 
Introduction to Hadoop
Introduction to HadoopIntroduction to Hadoop
Introduction to Hadoop
 
DAT101 Understanding AWS Database Options - AWS re: Invent 2012
DAT101 Understanding AWS Database Options - AWS re: Invent 2012DAT101 Understanding AWS Database Options - AWS re: Invent 2012
DAT101 Understanding AWS Database Options - AWS re: Invent 2012
 
Millions quotes per second in pure java
Millions quotes per second in pure javaMillions quotes per second in pure java
Millions quotes per second in pure java
 
Scotas - Oracle Open World Sao Pablo
Scotas - Oracle Open World Sao PabloScotas - Oracle Open World Sao Pablo
Scotas - Oracle Open World Sao Pablo
 
Cosbench apac
Cosbench apacCosbench apac
Cosbench apac
 
Complex Er[jl]ang Processing with StreamBase
Complex Er[jl]ang Processing with StreamBaseComplex Er[jl]ang Processing with StreamBase
Complex Er[jl]ang Processing with StreamBase
 
The Art & Sience of Optimization
The Art & Sience of OptimizationThe Art & Sience of Optimization
The Art & Sience of Optimization
 
Accelerating big data with ioMemory and Cisco UCS and NOSQL
Accelerating big data with ioMemory and Cisco UCS and NOSQLAccelerating big data with ioMemory and Cisco UCS and NOSQL
Accelerating big data with ioMemory and Cisco UCS and NOSQL
 
Processing Big Data
Processing Big DataProcessing Big Data
Processing Big Data
 
MySQL Cluster Scaling to a Billion Queries
MySQL Cluster Scaling to a Billion QueriesMySQL Cluster Scaling to a Billion Queries
MySQL Cluster Scaling to a Billion Queries
 
Streaming Solutions for Real time problems
Streaming Solutions for Real time problemsStreaming Solutions for Real time problems
Streaming Solutions for Real time problems
 
Know More About Rational Performance - Snehamoy K
Know More About Rational Performance - Snehamoy KKnow More About Rational Performance - Snehamoy K
Know More About Rational Performance - Snehamoy K
 
3 know more_about_rational_performance_tester_8-1-snehamoy_k
3 know more_about_rational_performance_tester_8-1-snehamoy_k3 know more_about_rational_performance_tester_8-1-snehamoy_k
3 know more_about_rational_performance_tester_8-1-snehamoy_k
 
Kognitio overview jan 2013
Kognitio overview jan 2013Kognitio overview jan 2013
Kognitio overview jan 2013
 
Kognitio overview jan 2013
Kognitio overview jan 2013Kognitio overview jan 2013
Kognitio overview jan 2013
 
Overcoming the Top Four Challenges to Real-Time Performance in Large-Scale, D...
Overcoming the Top Four Challenges to Real-Time Performance in Large-Scale, D...Overcoming the Top Four Challenges to Real-Time Performance in Large-Scale, D...
Overcoming the Top Four Challenges to Real-Time Performance in Large-Scale, D...
 
Microservices
MicroservicesMicroservices
Microservices
 
Fixing twitter
Fixing twitterFixing twitter
Fixing twitter
 

Recently uploaded

The Codex of Business Writing Software for Real-World Solutions 2.pptx
The Codex of Business Writing Software for Real-World Solutions 2.pptxThe Codex of Business Writing Software for Real-World Solutions 2.pptx
The Codex of Business Writing Software for Real-World Solutions 2.pptxMalak Abu Hammad
 
Kotlin Multiplatform & Compose Multiplatform - Starter kit for pragmatics
Kotlin Multiplatform & Compose Multiplatform - Starter kit for pragmaticsKotlin Multiplatform & Compose Multiplatform - Starter kit for pragmatics
Kotlin Multiplatform & Compose Multiplatform - Starter kit for pragmaticscarlostorres15106
 
My Hashitalk Indonesia April 2024 Presentation
My Hashitalk Indonesia April 2024 PresentationMy Hashitalk Indonesia April 2024 Presentation
My Hashitalk Indonesia April 2024 PresentationRidwan Fadjar
 
Human Factors of XR: Using Human Factors to Design XR Systems
Human Factors of XR: Using Human Factors to Design XR SystemsHuman Factors of XR: Using Human Factors to Design XR Systems
Human Factors of XR: Using Human Factors to Design XR SystemsMark Billinghurst
 
Advanced Test Driven-Development @ php[tek] 2024
Advanced Test Driven-Development @ php[tek] 2024Advanced Test Driven-Development @ php[tek] 2024
Advanced Test Driven-Development @ php[tek] 2024Scott Keck-Warren
 
Transforming Data Streams with Kafka Connect: An Introduction to Single Messa...
Transforming Data Streams with Kafka Connect: An Introduction to Single Messa...Transforming Data Streams with Kafka Connect: An Introduction to Single Messa...
Transforming Data Streams with Kafka Connect: An Introduction to Single Messa...HostedbyConfluent
 
Understanding the Laravel MVC Architecture
Understanding the Laravel MVC ArchitectureUnderstanding the Laravel MVC Architecture
Understanding the Laravel MVC ArchitecturePixlogix Infotech
 
Install Stable Diffusion in windows machine
Install Stable Diffusion in windows machineInstall Stable Diffusion in windows machine
Install Stable Diffusion in windows machinePadma Pradeep
 
SIEMENS: RAPUNZEL – A Tale About Knowledge Graph
SIEMENS: RAPUNZEL – A Tale About Knowledge GraphSIEMENS: RAPUNZEL – A Tale About Knowledge Graph
SIEMENS: RAPUNZEL – A Tale About Knowledge GraphNeo4j
 
GenCyber Cyber Security Day Presentation
GenCyber Cyber Security Day PresentationGenCyber Cyber Security Day Presentation
GenCyber Cyber Security Day PresentationMichael W. Hawkins
 
Key Features Of Token Development (1).pptx
Key  Features Of Token  Development (1).pptxKey  Features Of Token  Development (1).pptx
Key Features Of Token Development (1).pptxLBM Solutions
 
08448380779 Call Girls In Diplomatic Enclave Women Seeking Men
08448380779 Call Girls In Diplomatic Enclave Women Seeking Men08448380779 Call Girls In Diplomatic Enclave Women Seeking Men
08448380779 Call Girls In Diplomatic Enclave Women Seeking MenDelhi Call girls
 
CloudStudio User manual (basic edition):
CloudStudio User manual (basic edition):CloudStudio User manual (basic edition):
CloudStudio User manual (basic edition):comworks
 
Making_way_through_DLL_hollowing_inspite_of_CFG_by_Debjeet Banerjee.pptx
Making_way_through_DLL_hollowing_inspite_of_CFG_by_Debjeet Banerjee.pptxMaking_way_through_DLL_hollowing_inspite_of_CFG_by_Debjeet Banerjee.pptx
Making_way_through_DLL_hollowing_inspite_of_CFG_by_Debjeet Banerjee.pptxnull - The Open Security Community
 
Unblocking The Main Thread Solving ANRs and Frozen Frames
Unblocking The Main Thread Solving ANRs and Frozen FramesUnblocking The Main Thread Solving ANRs and Frozen Frames
Unblocking The Main Thread Solving ANRs and Frozen FramesSinan KOZAK
 
AI as an Interface for Commercial Buildings
AI as an Interface for Commercial BuildingsAI as an Interface for Commercial Buildings
AI as an Interface for Commercial BuildingsMemoori
 
Swan(sea) Song – personal research during my six years at Swansea ... and bey...
Swan(sea) Song – personal research during my six years at Swansea ... and bey...Swan(sea) Song – personal research during my six years at Swansea ... and bey...
Swan(sea) Song – personal research during my six years at Swansea ... and bey...Alan Dix
 
Slack Application Development 101 Slides
Slack Application Development 101 SlidesSlack Application Development 101 Slides
Slack Application Development 101 Slidespraypatel2
 
Breaking the Kubernetes Kill Chain: Host Path Mount
Breaking the Kubernetes Kill Chain: Host Path MountBreaking the Kubernetes Kill Chain: Host Path Mount
Breaking the Kubernetes Kill Chain: Host Path MountPuma Security, LLC
 

Recently uploaded (20)

The Codex of Business Writing Software for Real-World Solutions 2.pptx
The Codex of Business Writing Software for Real-World Solutions 2.pptxThe Codex of Business Writing Software for Real-World Solutions 2.pptx
The Codex of Business Writing Software for Real-World Solutions 2.pptx
 
Kotlin Multiplatform & Compose Multiplatform - Starter kit for pragmatics
Kotlin Multiplatform & Compose Multiplatform - Starter kit for pragmaticsKotlin Multiplatform & Compose Multiplatform - Starter kit for pragmatics
Kotlin Multiplatform & Compose Multiplatform - Starter kit for pragmatics
 
My Hashitalk Indonesia April 2024 Presentation
My Hashitalk Indonesia April 2024 PresentationMy Hashitalk Indonesia April 2024 Presentation
My Hashitalk Indonesia April 2024 Presentation
 
Human Factors of XR: Using Human Factors to Design XR Systems
Human Factors of XR: Using Human Factors to Design XR SystemsHuman Factors of XR: Using Human Factors to Design XR Systems
Human Factors of XR: Using Human Factors to Design XR Systems
 
Advanced Test Driven-Development @ php[tek] 2024
Advanced Test Driven-Development @ php[tek] 2024Advanced Test Driven-Development @ php[tek] 2024
Advanced Test Driven-Development @ php[tek] 2024
 
Transforming Data Streams with Kafka Connect: An Introduction to Single Messa...
Transforming Data Streams with Kafka Connect: An Introduction to Single Messa...Transforming Data Streams with Kafka Connect: An Introduction to Single Messa...
Transforming Data Streams with Kafka Connect: An Introduction to Single Messa...
 
Understanding the Laravel MVC Architecture
Understanding the Laravel MVC ArchitectureUnderstanding the Laravel MVC Architecture
Understanding the Laravel MVC Architecture
 
Install Stable Diffusion in windows machine
Install Stable Diffusion in windows machineInstall Stable Diffusion in windows machine
Install Stable Diffusion in windows machine
 
SIEMENS: RAPUNZEL – A Tale About Knowledge Graph
SIEMENS: RAPUNZEL – A Tale About Knowledge GraphSIEMENS: RAPUNZEL – A Tale About Knowledge Graph
SIEMENS: RAPUNZEL – A Tale About Knowledge Graph
 
GenCyber Cyber Security Day Presentation
GenCyber Cyber Security Day PresentationGenCyber Cyber Security Day Presentation
GenCyber Cyber Security Day Presentation
 
Key Features Of Token Development (1).pptx
Key  Features Of Token  Development (1).pptxKey  Features Of Token  Development (1).pptx
Key Features Of Token Development (1).pptx
 
08448380779 Call Girls In Diplomatic Enclave Women Seeking Men
08448380779 Call Girls In Diplomatic Enclave Women Seeking Men08448380779 Call Girls In Diplomatic Enclave Women Seeking Men
08448380779 Call Girls In Diplomatic Enclave Women Seeking Men
 
CloudStudio User manual (basic edition):
CloudStudio User manual (basic edition):CloudStudio User manual (basic edition):
CloudStudio User manual (basic edition):
 
Making_way_through_DLL_hollowing_inspite_of_CFG_by_Debjeet Banerjee.pptx
Making_way_through_DLL_hollowing_inspite_of_CFG_by_Debjeet Banerjee.pptxMaking_way_through_DLL_hollowing_inspite_of_CFG_by_Debjeet Banerjee.pptx
Making_way_through_DLL_hollowing_inspite_of_CFG_by_Debjeet Banerjee.pptx
 
Unblocking The Main Thread Solving ANRs and Frozen Frames
Unblocking The Main Thread Solving ANRs and Frozen FramesUnblocking The Main Thread Solving ANRs and Frozen Frames
Unblocking The Main Thread Solving ANRs and Frozen Frames
 
AI as an Interface for Commercial Buildings
AI as an Interface for Commercial BuildingsAI as an Interface for Commercial Buildings
AI as an Interface for Commercial Buildings
 
The transition to renewables in India.pdf
The transition to renewables in India.pdfThe transition to renewables in India.pdf
The transition to renewables in India.pdf
 
Swan(sea) Song – personal research during my six years at Swansea ... and bey...
Swan(sea) Song – personal research during my six years at Swansea ... and bey...Swan(sea) Song – personal research during my six years at Swansea ... and bey...
Swan(sea) Song – personal research during my six years at Swansea ... and bey...
 
Slack Application Development 101 Slides
Slack Application Development 101 SlidesSlack Application Development 101 Slides
Slack Application Development 101 Slides
 
Breaking the Kubernetes Kill Chain: Host Path Mount
Breaking the Kubernetes Kill Chain: Host Path MountBreaking the Kubernetes Kill Chain: Host Path Mount
Breaking the Kubernetes Kill Chain: Host Path Mount
 

SSD Performance Benchmarking

  • 1. SSD Benchmark Testing Panel Shirish Jamthe Director of System Engineering Virident Systems, Inc. August 2011
  • 2. Performance Characterization Methodology Focus on sustained performance and application-level metrics • Level 1: Baseline performance • Level 2: Sustained performance and IO-QoS metrics • Level 3: Application performance and real-world workloads Performance QD=1 QD=128 Specified Performance “Seasoned” Device Mixed read-write Device filled to capacity, (Databases, Caching, Continuous GC Workload Metadata serving, …) Conditions
  • 3. I/O Quality of Service Measure of latency in real world scenarios • Mixed Read/Write workload sustained over time • Mixed Read/Writes of various block sizes that simulate real workloads
  • 4. Baseline Performance • Sweep across 10+ parameters (6000+ data points on OS, system, card combo) • Operation mix: Reads, Writes, R+W mix; sequential, random; aligned/unaligned • Block sizes: 512B – 1M; Threads/Queue-depth: 1-256; File system types: (Linux) ext3, xfs • Card configs: Capacity-optimized, Performance-optimized, Balanced; With and without RAID • With and without garbage collection, … • Measurements: Bandwidth, IOPS, Latency, Latency Standard Deviation, System resource overheads
  • 5. Application Tests With Real-World Workloads… Measure performance in real life scenario with varying application settings • Simulated DB workloads: ORION, SysBench, SQLIO, … • Oracle: Flash cache, Preferred Read, ASM store on TPCC, TPCH, Calling circle etc. • MySQL: Varying cache sizes, buffered writes vs. direct, OLTP, TPCC Competition Virident
  • 6. Virident Systems, Inc. Booth #416 Shirish Jamthe Director of System Engineering Virident Systems, Inc. August 2011