SlideShare uma empresa Scribd logo
1 de 12
DIOS: Dynamic Instrumentation for (not so) Outstanding Scheduling Blake Sutton & Chris Sosa
Motivation ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Approach: Adaptive Distributed Scheduler ,[object Object],[object Object],[object Object],[object Object],[object Object]
Dynamic Instrumentation with Pin ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Application-Specific Information ,[object Object],[object Object],[object Object],[object Object],[object Object]
Evaluation ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
The Good ,[object Object],[object Object],[object Object]
The Bad ,[object Object],[object Object],[object Object],[object Object],7.64 7.90 14.51 6.27 1.25 1.00 lu 5.81 6.04 7.84 2.87 1.48 1.00 ocean 7.26 7.45 5.43 2.65 1.88 1.00 heatedplate latency # mems malloc/free count only pin native application
The “Interesting” ,[object Object]
Conclusion: the Future of DIOS ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
¿ Preguntas?
Wait…hasn’t this been solved? ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]

Mais conteúdo relacionado

Semelhante a DIOS

Embedded Intro India05
Embedded Intro India05Embedded Intro India05
Embedded Intro India05Rajesh Gupta
 
Forecasting database performance
Forecasting database performanceForecasting database performance
Forecasting database performanceShenglin Du
 
operating system question bank
operating system question bankoperating system question bank
operating system question bankrajatdeep kaur
 
LM9 - OPERATIONS, SCHEDULING, Inter process xommuncation
LM9 - OPERATIONS, SCHEDULING, Inter process xommuncationLM9 - OPERATIONS, SCHEDULING, Inter process xommuncation
LM9 - OPERATIONS, SCHEDULING, Inter process xommuncationMani Deepak Choudhry
 
Big Data Day LA 2016/ Big Data Track - Portable Stream and Batch Processing w...
Big Data Day LA 2016/ Big Data Track - Portable Stream and Batch Processing w...Big Data Day LA 2016/ Big Data Track - Portable Stream and Batch Processing w...
Big Data Day LA 2016/ Big Data Track - Portable Stream and Batch Processing w...Data Con LA
 
One Day Version 10.3 Upgrade - How a Large Biotech Plant's DeltaV Systems Wer...
One Day Version 10.3 Upgrade - How a Large Biotech Plant's DeltaV Systems Wer...One Day Version 10.3 Upgrade - How a Large Biotech Plant's DeltaV Systems Wer...
One Day Version 10.3 Upgrade - How a Large Biotech Plant's DeltaV Systems Wer...Emerson Exchange
 
Real Time Operating system (RTOS) - Embedded systems
Real Time Operating system (RTOS) - Embedded systemsReal Time Operating system (RTOS) - Embedded systems
Real Time Operating system (RTOS) - Embedded systemsHariharan Ganesan
 
Real Time OS For Embedded Systems
Real Time OS For Embedded SystemsReal Time OS For Embedded Systems
Real Time OS For Embedded SystemsHimanshu Ghetia
 
Automating the Hunt for Non-Obvious Sources of Latency Spreads
Automating the Hunt for Non-Obvious Sources of Latency SpreadsAutomating the Hunt for Non-Obvious Sources of Latency Spreads
Automating the Hunt for Non-Obvious Sources of Latency SpreadsScyllaDB
 
Cse viii-advanced-computer-architectures-06cs81-solution
Cse viii-advanced-computer-architectures-06cs81-solutionCse viii-advanced-computer-architectures-06cs81-solution
Cse viii-advanced-computer-architectures-06cs81-solutionShobha Kumar
 
The Architecture of Continuous Innovation - OSCON 2015
The Architecture of Continuous Innovation - OSCON 2015The Architecture of Continuous Innovation - OSCON 2015
The Architecture of Continuous Innovation - OSCON 2015Chip Childers
 
Real Time Operating Systems
Real Time Operating SystemsReal Time Operating Systems
Real Time Operating SystemsPawandeep Kaur
 
Talk at the Boston Cloud Foundry Meetup June 2015
Talk at the Boston Cloud Foundry Meetup June 2015Talk at the Boston Cloud Foundry Meetup June 2015
Talk at the Boston Cloud Foundry Meetup June 2015Chip Childers
 
What is operating system
What is operating systemWhat is operating system
What is operating systemvmahesmca
 
What is operating system
What is operating systemWhat is operating system
What is operating systemvmahesmca
 
From Duke of DevOps to Queen of Chaos - Api days 2018
From Duke of DevOps to Queen of Chaos - Api days 2018From Duke of DevOps to Queen of Chaos - Api days 2018
From Duke of DevOps to Queen of Chaos - Api days 2018Christophe Rochefolle
 
Understanding the characteristics of android wear os
Understanding the characteristics of android wear osUnderstanding the characteristics of android wear os
Understanding the characteristics of android wear osPratik Jain
 

Semelhante a DIOS (20)

Embedded Intro India05
Embedded Intro India05Embedded Intro India05
Embedded Intro India05
 
Forecasting database performance
Forecasting database performanceForecasting database performance
Forecasting database performance
 
operating system question bank
operating system question bankoperating system question bank
operating system question bank
 
LM9 - OPERATIONS, SCHEDULING, Inter process xommuncation
LM9 - OPERATIONS, SCHEDULING, Inter process xommuncationLM9 - OPERATIONS, SCHEDULING, Inter process xommuncation
LM9 - OPERATIONS, SCHEDULING, Inter process xommuncation
 
Autosar Basics hand book_v1
Autosar Basics  hand book_v1Autosar Basics  hand book_v1
Autosar Basics hand book_v1
 
Big Data Day LA 2016/ Big Data Track - Portable Stream and Batch Processing w...
Big Data Day LA 2016/ Big Data Track - Portable Stream and Batch Processing w...Big Data Day LA 2016/ Big Data Track - Portable Stream and Batch Processing w...
Big Data Day LA 2016/ Big Data Track - Portable Stream and Batch Processing w...
 
One Day Version 10.3 Upgrade - How a Large Biotech Plant's DeltaV Systems Wer...
One Day Version 10.3 Upgrade - How a Large Biotech Plant's DeltaV Systems Wer...One Day Version 10.3 Upgrade - How a Large Biotech Plant's DeltaV Systems Wer...
One Day Version 10.3 Upgrade - How a Large Biotech Plant's DeltaV Systems Wer...
 
Embedded os
Embedded osEmbedded os
Embedded os
 
Real Time Operating system (RTOS) - Embedded systems
Real Time Operating system (RTOS) - Embedded systemsReal Time Operating system (RTOS) - Embedded systems
Real Time Operating system (RTOS) - Embedded systems
 
Real Time OS For Embedded Systems
Real Time OS For Embedded SystemsReal Time OS For Embedded Systems
Real Time OS For Embedded Systems
 
Automating the Hunt for Non-Obvious Sources of Latency Spreads
Automating the Hunt for Non-Obvious Sources of Latency SpreadsAutomating the Hunt for Non-Obvious Sources of Latency Spreads
Automating the Hunt for Non-Obvious Sources of Latency Spreads
 
Cse viii-advanced-computer-architectures-06cs81-solution
Cse viii-advanced-computer-architectures-06cs81-solutionCse viii-advanced-computer-architectures-06cs81-solution
Cse viii-advanced-computer-architectures-06cs81-solution
 
The Architecture of Continuous Innovation - OSCON 2015
The Architecture of Continuous Innovation - OSCON 2015The Architecture of Continuous Innovation - OSCON 2015
The Architecture of Continuous Innovation - OSCON 2015
 
Os Concepts
Os ConceptsOs Concepts
Os Concepts
 
Real Time Operating Systems
Real Time Operating SystemsReal Time Operating Systems
Real Time Operating Systems
 
Talk at the Boston Cloud Foundry Meetup June 2015
Talk at the Boston Cloud Foundry Meetup June 2015Talk at the Boston Cloud Foundry Meetup June 2015
Talk at the Boston Cloud Foundry Meetup June 2015
 
What is operating system
What is operating systemWhat is operating system
What is operating system
 
What is operating system
What is operating systemWhat is operating system
What is operating system
 
From Duke of DevOps to Queen of Chaos - Api days 2018
From Duke of DevOps to Queen of Chaos - Api days 2018From Duke of DevOps to Queen of Chaos - Api days 2018
From Duke of DevOps to Queen of Chaos - Api days 2018
 
Understanding the characteristics of android wear os
Understanding the characteristics of android wear osUnderstanding the characteristics of android wear os
Understanding the characteristics of android wear os
 

Mais de awesomesos

A Hardware Architecture For Implementing Protection Rings
A Hardware Architecture For Implementing Protection RingsA Hardware Architecture For Implementing Protection Rings
A Hardware Architecture For Implementing Protection Ringsawesomesos
 
Amazon’s Cloud Computing Efforts
Amazon’s Cloud Computing EffortsAmazon’s Cloud Computing Efforts
Amazon’s Cloud Computing Effortsawesomesos
 
Bringing The Grid Home for Grid2008
Bringing The Grid Home for Grid2008Bringing The Grid Home for Grid2008
Bringing The Grid Home for Grid2008awesomesos
 
Handling Byzantine Faults
Handling Byzantine FaultsHandling Byzantine Faults
Handling Byzantine Faultsawesomesos
 
Masters of Science presentation: Bringing The Grid Home
Masters of Science presentation:  Bringing The Grid HomeMasters of Science presentation:  Bringing The Grid Home
Masters of Science presentation: Bringing The Grid Homeawesomesos
 
Distributed Snapshots
Distributed SnapshotsDistributed Snapshots
Distributed Snapshotsawesomesos
 
PicFS presentation
PicFS presentationPicFS presentation
PicFS presentationawesomesos
 
Online feedback correlation using clustering
Online feedback correlation using clusteringOnline feedback correlation using clustering
Online feedback correlation using clusteringawesomesos
 
Web Service Choreography Interface (Wsci)
Web Service Choreography Interface (Wsci)Web Service Choreography Interface (Wsci)
Web Service Choreography Interface (Wsci)awesomesos
 
Hadoop Tutorial
Hadoop TutorialHadoop Tutorial
Hadoop Tutorialawesomesos
 
Lustre And Nfs V4
Lustre And Nfs V4Lustre And Nfs V4
Lustre And Nfs V4awesomesos
 
An Installable File System For Genesis II
An Installable File System For Genesis IIAn Installable File System For Genesis II
An Installable File System For Genesis IIawesomesos
 
A Web Based Covert File System
A Web Based Covert File SystemA Web Based Covert File System
A Web Based Covert File Systemawesomesos
 
Distributed File Systems
Distributed File SystemsDistributed File Systems
Distributed File Systemsawesomesos
 
Exploring The Cloud
Exploring The CloudExploring The Cloud
Exploring The Cloudawesomesos
 
Data Grid Taxonomies
Data Grid TaxonomiesData Grid Taxonomies
Data Grid Taxonomiesawesomesos
 
A Guide to DAGMan
A Guide to DAGManA Guide to DAGMan
A Guide to DAGManawesomesos
 

Mais de awesomesos (17)

A Hardware Architecture For Implementing Protection Rings
A Hardware Architecture For Implementing Protection RingsA Hardware Architecture For Implementing Protection Rings
A Hardware Architecture For Implementing Protection Rings
 
Amazon’s Cloud Computing Efforts
Amazon’s Cloud Computing EffortsAmazon’s Cloud Computing Efforts
Amazon’s Cloud Computing Efforts
 
Bringing The Grid Home for Grid2008
Bringing The Grid Home for Grid2008Bringing The Grid Home for Grid2008
Bringing The Grid Home for Grid2008
 
Handling Byzantine Faults
Handling Byzantine FaultsHandling Byzantine Faults
Handling Byzantine Faults
 
Masters of Science presentation: Bringing The Grid Home
Masters of Science presentation:  Bringing The Grid HomeMasters of Science presentation:  Bringing The Grid Home
Masters of Science presentation: Bringing The Grid Home
 
Distributed Snapshots
Distributed SnapshotsDistributed Snapshots
Distributed Snapshots
 
PicFS presentation
PicFS presentationPicFS presentation
PicFS presentation
 
Online feedback correlation using clustering
Online feedback correlation using clusteringOnline feedback correlation using clustering
Online feedback correlation using clustering
 
Web Service Choreography Interface (Wsci)
Web Service Choreography Interface (Wsci)Web Service Choreography Interface (Wsci)
Web Service Choreography Interface (Wsci)
 
Hadoop Tutorial
Hadoop TutorialHadoop Tutorial
Hadoop Tutorial
 
Lustre And Nfs V4
Lustre And Nfs V4Lustre And Nfs V4
Lustre And Nfs V4
 
An Installable File System For Genesis II
An Installable File System For Genesis IIAn Installable File System For Genesis II
An Installable File System For Genesis II
 
A Web Based Covert File System
A Web Based Covert File SystemA Web Based Covert File System
A Web Based Covert File System
 
Distributed File Systems
Distributed File SystemsDistributed File Systems
Distributed File Systems
 
Exploring The Cloud
Exploring The CloudExploring The Cloud
Exploring The Cloud
 
Data Grid Taxonomies
Data Grid TaxonomiesData Grid Taxonomies
Data Grid Taxonomies
 
A Guide to DAGMan
A Guide to DAGManA Guide to DAGMan
A Guide to DAGMan
 

Último

IESVE for Early Stage Design and Planning
IESVE for Early Stage Design and PlanningIESVE for Early Stage Design and Planning
IESVE for Early Stage Design and PlanningIES VE
 
Breaking Down the Flutterwave Scandal What You Need to Know.pdf
Breaking Down the Flutterwave Scandal What You Need to Know.pdfBreaking Down the Flutterwave Scandal What You Need to Know.pdf
Breaking Down the Flutterwave Scandal What You Need to Know.pdfUK Journal
 
Secure Zero Touch enabled Edge compute with Dell NativeEdge via FDO _ Brad at...
Secure Zero Touch enabled Edge compute with Dell NativeEdge via FDO _ Brad at...Secure Zero Touch enabled Edge compute with Dell NativeEdge via FDO _ Brad at...
Secure Zero Touch enabled Edge compute with Dell NativeEdge via FDO _ Brad at...FIDO Alliance
 
State of the Smart Building Startup Landscape 2024!
State of the Smart Building Startup Landscape 2024!State of the Smart Building Startup Landscape 2024!
State of the Smart Building Startup Landscape 2024!Memoori
 
Integrating Telephony Systems with Salesforce: Insights and Considerations, B...
Integrating Telephony Systems with Salesforce: Insights and Considerations, B...Integrating Telephony Systems with Salesforce: Insights and Considerations, B...
Integrating Telephony Systems with Salesforce: Insights and Considerations, B...CzechDreamin
 
PLAI - Acceleration Program for Generative A.I. Startups
PLAI - Acceleration Program for Generative A.I. StartupsPLAI - Acceleration Program for Generative A.I. Startups
PLAI - Acceleration Program for Generative A.I. StartupsStefano
 
TopCryptoSupers 12thReport OrionX May2024
TopCryptoSupers 12thReport OrionX May2024TopCryptoSupers 12thReport OrionX May2024
TopCryptoSupers 12thReport OrionX May2024Stephen Perrenod
 
ECS 2024 Teams Premium - Pretty Secure
ECS 2024   Teams Premium - Pretty SecureECS 2024   Teams Premium - Pretty Secure
ECS 2024 Teams Premium - Pretty SecureFemke de Vroome
 
Behind the Scenes From the Manager's Chair: Decoding the Secrets of Successfu...
Behind the Scenes From the Manager's Chair: Decoding the Secrets of Successfu...Behind the Scenes From the Manager's Chair: Decoding the Secrets of Successfu...
Behind the Scenes From the Manager's Chair: Decoding the Secrets of Successfu...CzechDreamin
 
Easier, Faster, and More Powerful – Notes Document Properties Reimagined
Easier, Faster, and More Powerful – Notes Document Properties ReimaginedEasier, Faster, and More Powerful – Notes Document Properties Reimagined
Easier, Faster, and More Powerful – Notes Document Properties Reimaginedpanagenda
 
Microsoft CSP Briefing Pre-Engagement - Questionnaire
Microsoft CSP Briefing Pre-Engagement - QuestionnaireMicrosoft CSP Briefing Pre-Engagement - Questionnaire
Microsoft CSP Briefing Pre-Engagement - QuestionnaireExakis Nelite
 
Working together SRE & Platform Engineering
Working together SRE & Platform EngineeringWorking together SRE & Platform Engineering
Working together SRE & Platform EngineeringMarcus Vechiato
 
Google I/O Extended 2024 Warsaw
Google I/O Extended 2024 WarsawGoogle I/O Extended 2024 Warsaw
Google I/O Extended 2024 WarsawGDSC PJATK
 
BT & Neo4j _ How Knowledge Graphs help BT deliver Digital Transformation.pptx
BT & Neo4j _ How Knowledge Graphs help BT deliver Digital Transformation.pptxBT & Neo4j _ How Knowledge Graphs help BT deliver Digital Transformation.pptx
BT & Neo4j _ How Knowledge Graphs help BT deliver Digital Transformation.pptxNeo4j
 
Long journey of Ruby Standard library at RubyKaigi 2024
Long journey of Ruby Standard library at RubyKaigi 2024Long journey of Ruby Standard library at RubyKaigi 2024
Long journey of Ruby Standard library at RubyKaigi 2024Hiroshi SHIBATA
 
Enterprise Knowledge Graphs - Data Summit 2024
Enterprise Knowledge Graphs - Data Summit 2024Enterprise Knowledge Graphs - Data Summit 2024
Enterprise Knowledge Graphs - Data Summit 2024Enterprise Knowledge
 
The Metaverse: Are We There Yet?
The  Metaverse:    Are   We  There  Yet?The  Metaverse:    Are   We  There  Yet?
The Metaverse: Are We There Yet?Mark Billinghurst
 
Extensible Python: Robustness through Addition - PyCon 2024
Extensible Python: Robustness through Addition - PyCon 2024Extensible Python: Robustness through Addition - PyCon 2024
Extensible Python: Robustness through Addition - PyCon 2024Patrick Viafore
 
WSO2CONMay2024OpenSourceConferenceDebrief.pptx
WSO2CONMay2024OpenSourceConferenceDebrief.pptxWSO2CONMay2024OpenSourceConferenceDebrief.pptx
WSO2CONMay2024OpenSourceConferenceDebrief.pptxJennifer Lim
 

Último (20)

IESVE for Early Stage Design and Planning
IESVE for Early Stage Design and PlanningIESVE for Early Stage Design and Planning
IESVE for Early Stage Design and Planning
 
Breaking Down the Flutterwave Scandal What You Need to Know.pdf
Breaking Down the Flutterwave Scandal What You Need to Know.pdfBreaking Down the Flutterwave Scandal What You Need to Know.pdf
Breaking Down the Flutterwave Scandal What You Need to Know.pdf
 
Secure Zero Touch enabled Edge compute with Dell NativeEdge via FDO _ Brad at...
Secure Zero Touch enabled Edge compute with Dell NativeEdge via FDO _ Brad at...Secure Zero Touch enabled Edge compute with Dell NativeEdge via FDO _ Brad at...
Secure Zero Touch enabled Edge compute with Dell NativeEdge via FDO _ Brad at...
 
State of the Smart Building Startup Landscape 2024!
State of the Smart Building Startup Landscape 2024!State of the Smart Building Startup Landscape 2024!
State of the Smart Building Startup Landscape 2024!
 
Integrating Telephony Systems with Salesforce: Insights and Considerations, B...
Integrating Telephony Systems with Salesforce: Insights and Considerations, B...Integrating Telephony Systems with Salesforce: Insights and Considerations, B...
Integrating Telephony Systems with Salesforce: Insights and Considerations, B...
 
PLAI - Acceleration Program for Generative A.I. Startups
PLAI - Acceleration Program for Generative A.I. StartupsPLAI - Acceleration Program for Generative A.I. Startups
PLAI - Acceleration Program for Generative A.I. Startups
 
TopCryptoSupers 12thReport OrionX May2024
TopCryptoSupers 12thReport OrionX May2024TopCryptoSupers 12thReport OrionX May2024
TopCryptoSupers 12thReport OrionX May2024
 
ECS 2024 Teams Premium - Pretty Secure
ECS 2024   Teams Premium - Pretty SecureECS 2024   Teams Premium - Pretty Secure
ECS 2024 Teams Premium - Pretty Secure
 
Behind the Scenes From the Manager's Chair: Decoding the Secrets of Successfu...
Behind the Scenes From the Manager's Chair: Decoding the Secrets of Successfu...Behind the Scenes From the Manager's Chair: Decoding the Secrets of Successfu...
Behind the Scenes From the Manager's Chair: Decoding the Secrets of Successfu...
 
Easier, Faster, and More Powerful – Notes Document Properties Reimagined
Easier, Faster, and More Powerful – Notes Document Properties ReimaginedEasier, Faster, and More Powerful – Notes Document Properties Reimagined
Easier, Faster, and More Powerful – Notes Document Properties Reimagined
 
Microsoft CSP Briefing Pre-Engagement - Questionnaire
Microsoft CSP Briefing Pre-Engagement - QuestionnaireMicrosoft CSP Briefing Pre-Engagement - Questionnaire
Microsoft CSP Briefing Pre-Engagement - Questionnaire
 
Overview of Hyperledger Foundation
Overview of Hyperledger FoundationOverview of Hyperledger Foundation
Overview of Hyperledger Foundation
 
Working together SRE & Platform Engineering
Working together SRE & Platform EngineeringWorking together SRE & Platform Engineering
Working together SRE & Platform Engineering
 
Google I/O Extended 2024 Warsaw
Google I/O Extended 2024 WarsawGoogle I/O Extended 2024 Warsaw
Google I/O Extended 2024 Warsaw
 
BT & Neo4j _ How Knowledge Graphs help BT deliver Digital Transformation.pptx
BT & Neo4j _ How Knowledge Graphs help BT deliver Digital Transformation.pptxBT & Neo4j _ How Knowledge Graphs help BT deliver Digital Transformation.pptx
BT & Neo4j _ How Knowledge Graphs help BT deliver Digital Transformation.pptx
 
Long journey of Ruby Standard library at RubyKaigi 2024
Long journey of Ruby Standard library at RubyKaigi 2024Long journey of Ruby Standard library at RubyKaigi 2024
Long journey of Ruby Standard library at RubyKaigi 2024
 
Enterprise Knowledge Graphs - Data Summit 2024
Enterprise Knowledge Graphs - Data Summit 2024Enterprise Knowledge Graphs - Data Summit 2024
Enterprise Knowledge Graphs - Data Summit 2024
 
The Metaverse: Are We There Yet?
The  Metaverse:    Are   We  There  Yet?The  Metaverse:    Are   We  There  Yet?
The Metaverse: Are We There Yet?
 
Extensible Python: Robustness through Addition - PyCon 2024
Extensible Python: Robustness through Addition - PyCon 2024Extensible Python: Robustness through Addition - PyCon 2024
Extensible Python: Robustness through Addition - PyCon 2024
 
WSO2CONMay2024OpenSourceConferenceDebrief.pptx
WSO2CONMay2024OpenSourceConferenceDebrief.pptxWSO2CONMay2024OpenSourceConferenceDebrief.pptx
WSO2CONMay2024OpenSourceConferenceDebrief.pptx
 

DIOS

Notas do Editor

  1. Long-running, short-running, memory-intensive, cpu-bound…don’t know what kind of jobs to expect. So how can the scheduler put them where they should be if it doesn’t know these things? Transition: Wouldn’t it be nice if the scheduler could just “handle it” – without the user having specify characteristics of their jobs in advance?
  2. Our approach to this problem is DIOS – an adaptive distributed scheduler. Describe diagram. Transition: So you must be thinking…wait, how are you going to just “gather application-specific info”?
  3. The answer is – we’ll write a tool with Pin, a dynamic instrumentation framework. Describe diagram – how it’s a mini VM. Describe points for inserting instrumentation and the tradeoffs – routine level, instruction level.
  4. So we’ve established that Pin is a tool for what we want to do – dynamically instrument applications. But what code do we want to insert? What are we looking to get from our pintool? Since we are trying to detect and avoid memory contention between processes, it makes senses to study the memory behavior of the applications. To this end, we chose three things to start with (describe them). The figure to side there shows how the pintool fits in to our overall plan – it would collect information for each application and report the results to Hare, the local scheduler. Then Hare, which is also monitoring the memory subsystem of the local machine, reports to Rhino, and Rhino decides what to do.
  5. Considering our motivation, it was important to try to evaluate it on a somewhat realistic workload. Since it seems like most long-running jobs on clusters are scientific applications, we wanted to use real scientific benchmarks. Describe benchmarks. To evaluate the scheduler, we measured the total runtime from… Then, to evaluate our pintool, we measured the overhead from running each application with our pintool and also tracked the information we collected over time to see if we could correlate it to interesting behavior or differences between programs.
  6. Potential for improvement – we saw this from our baseline, using a simple policy to react to the presence of memory contention. Might be able to get even better results on long-running jobs, with better information on the running processes (like we could get from dynamic instrumentation!)
  7. But on the other hand, there’s the bad. Although our scheduler works perfectly well with the pintool, we discovered that the overhead introduced by Pin is just too much. Some of our overhead results are below – we show the time to run the application natively, with pin (no pintool), with a tool that only counts instructions, and with our three metrics. The way we hoped to solve the overhead problem originally was to basically only instrument when we needed to –like when the scheduler decided the machine was performing badly. Then, the relatively high overhead to run the analysis wouldn’t have to make much of an impact overall. However, we were unable to get the performance gains we hoped – Pin doesn’t offer the ability to completely attach and detach from a running program, only to attach, and we discovered when we tried to add and remove insturmentation dynamically that we lost the gains from code caching. So while this idea could work with another system or with a new Pin, we couldn’t manage to bring the overhead down.
  8. But on the bright side, at least it collected some interesting information. Note how similar the patterns of LU and heatedplate are – talk about how that’s probably because they are tightly looped and very repetitive, whereas Ocean is obviously performing a more irregular and complex analysis with some possible distinct phases in it. Possibility of using the variation in a metric like this to “predict the predictability” to separate applications that are better left alone from those that are more likely to be safely handled by common heuristics, etc.
  9. So – the future of DIOS.
  10. Questions?
  11. Kind of...but no comprehensive solution.