SlideShare uma empresa Scribd logo
1 de 37
Distributed Computing Seminar Lecture 1: Introduction to Distributed  Computing & Systems Background Christophe Bisciglia, Aaron Kimball, & Sierra Michels-Slettvet Summer 2007 Except where otherwise noted, the contents of this presentation are © Copyright 2007 University of Washington and are licensed under the Creative Commons Attribution 2.5 License.
Course Overview ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Outline ,[object Object],[object Object],[object Object],[object Object],[object Object]
Computer Speedup Moore’s Law: “ The density of transistors on a chip doubles every 18 months, for the same cost”  (1965) Image: Tom’s Hardware and not subject to the Creative Commons license applicable to the rest of this work.  Image: Tom’s Hardware
Scope of problems ,[object Object],[object Object],[object Object]
Distributed problems ,[object Object],Image: DreamWorks Animation and not subject to the Creative Commons license applicable to the rest of this work.
Distributed problems ,[object Object],Happy Feet  © Kingdom Feature Productions; Lord of the Rings  © New Line Cinema, neither image is subject to the Creative Commons license applicable to the rest of the work.
Distributed problems ,[object Object],[object Object],[object Object],What is the key attribute that all these examples have in common?
Parallel vs. Distributed ,[object Object],[object Object],[object Object],[object Object]
A Brief History… 1975-85 ,[object Object],[object Object],[object Object],Image:  Computer Pictures Database and Cray Research Corp and is not subject to the Creative Commons license applicable to the rest of this work.
[object Object],[object Object],[object Object],A Brief History… 1985-95
A Brief History… 1995-Today ,[object Object],[object Object],[object Object],[object Object]
Parallelization & Synchronization
Parallelization Idea ,[object Object]
Parallelization Idea (2) In a parallel computation, we would like to have as many threads as we have processors. e.g., a four-processor computer would be able to run four threads at the same time.
Parallelization Idea (3)
Parallelization Idea (4)
Parallelization Pitfalls ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],What is the common theme of all of these problems?
Parallelization Pitfalls (2) ,[object Object],[object Object]
What is Wrong With This? ,[object Object],[object Object],[object Object],[object Object],[object Object],Thread 2: void bar() { y++; x+=3; } If the initial state is y = 0, x = 6, what happens after these threads finish running?
Multithreaded = Unpredictability ,[object Object],Thread 1: void foo() { eax = mem[x]; inc eax; mem[x] = eax; ebx = mem[x]; mem[y] = ebx; } Thread 2: void bar() { eax = mem[y]; inc eax; mem[y] = eax; eax = mem[x]; add eax, 3; mem[x] = eax; } ,[object Object]
Multithreaded = Unpredictability ,[object Object],[object Object],[object Object],[object Object],[object Object]
Synchronization Primitives ,[object Object],[object Object]
Semaphores ,[object Object],[object Object],Only one side of the semaphore can ever be red! (Can both be green?)
Semaphores ,[object Object],[object Object],[object Object]
The “corrected” example Thread 1: void foo() { sem.lock(); x++; y = x; sem.unlock(); } Thread 2: void bar() { sem.lock(); y++; x+=3; sem.unlock(); } Global var “Semaphore sem = new Semaphore();” guards access to x & y
Condition Variables ,[object Object],[object Object],[object Object]
The final example Thread 1: void foo() { sem.lock(); x++; y = x; fooDone = true; sem.unlock(); fooFinishedCV.notify(); } Thread 2: void bar() { sem.lock(); if(!fooDone) fooFinishedCV.wait(sem); y++; x+=3; sem.unlock(); } Global vars: Semaphore sem = new Semaphore(); ConditionVar fooFinishedCV = new ConditionVar(); boolean fooDone = false;
Too Much Synchronization? Deadlock Synchronization becomes even more complicated when multiple locks can be used Can cause entire system to “get stuck” Thread A: semaphore1.lock(); semaphore2.lock(); /* use data guarded by  semaphores */ semaphore1.unlock();  semaphore2.unlock(); Thread B: semaphore2.lock(); semaphore1.lock(); /* use data guarded by  semaphores */ semaphore1.unlock();  semaphore2.unlock(); (Image: RPI CSCI.4210 Operating Systems notes)
The Moral: Be Careful! ,[object Object],[object Object],[object Object],[object Object],[object Object]
Fundamentals of Networking
Sockets: The Internet = tubes? ,[object Object],[object Object],[object Object]
Ports ,[object Object],[object Object]
What makes this work? ,[object Object],[object Object],Even more low-level protocols handle how data is sent over Ethernet wires, or how bits are sent through the air using 802.11 wireless…
Why is This Necessary? ,[object Object],[object Object]
Networking Issues ,[object Object],[object Object],[object Object],[object Object]
Conclusions ,[object Object],[object Object],[object Object],[object Object]

Mais conteúdo relacionado

Mais procurados

Mais procurados (20)

IPC
IPCIPC
IPC
 
WiMAX implementation in ns3
WiMAX implementation in ns3WiMAX implementation in ns3
WiMAX implementation in ns3
 
5.distributed file systems
5.distributed file systems5.distributed file systems
5.distributed file systems
 
Processes and threads
Processes and threadsProcesses and threads
Processes and threads
 
.ppt
.ppt.ppt
.ppt
 
Distributed Shared Memory Systems
Distributed Shared Memory SystemsDistributed Shared Memory Systems
Distributed Shared Memory Systems
 
Interprocess communication (IPC) IN O.S
Interprocess communication (IPC) IN O.SInterprocess communication (IPC) IN O.S
Interprocess communication (IPC) IN O.S
 
ITFT_Inter process communication
ITFT_Inter process communicationITFT_Inter process communication
ITFT_Inter process communication
 
Porting dmtcp mac_slides
Porting dmtcp mac_slidesPorting dmtcp mac_slides
Porting dmtcp mac_slides
 
Apple continuity
Apple continuityApple continuity
Apple continuity
 
PThreads Vs Win32 Threads
PThreads  Vs  Win32 ThreadsPThreads  Vs  Win32 Threads
PThreads Vs Win32 Threads
 
Unit 1
Unit 1Unit 1
Unit 1
 
INET for Starters
INET for StartersINET for Starters
INET for Starters
 
NS-3
NS-3 NS-3
NS-3
 
Processes and Threads in Windows Vista
Processes and Threads in Windows VistaProcesses and Threads in Windows Vista
Processes and Threads in Windows Vista
 
From Mainframe to Microservice: An Introduction to Distributed Systems
From Mainframe to Microservice: An Introduction to Distributed SystemsFrom Mainframe to Microservice: An Introduction to Distributed Systems
From Mainframe to Microservice: An Introduction to Distributed Systems
 
Ns 3 simulation of wi max networks
Ns 3 simulation of wi max networksNs 3 simulation of wi max networks
Ns 3 simulation of wi max networks
 
IPC
IPCIPC
IPC
 
Chap 4
Chap 4Chap 4
Chap 4
 
Inter Process Communication
Inter Process CommunicationInter Process Communication
Inter Process Communication
 

Semelhante a Introduction to Cluster Computing and Map Reduce (from Google)

Introduction & Parellelization on large scale clusters
Introduction & Parellelization on large scale clustersIntroduction & Parellelization on large scale clusters
Introduction & Parellelization on large scale clustersSri Prasanna
 
Distributed computing presentation
Distributed computing presentationDistributed computing presentation
Distributed computing presentationDelhi/NCR HUG
 
Multithreading 101
Multithreading 101Multithreading 101
Multithreading 101Tim Penhey
 
Software and the Concurrency Revolution : Notes
Software and the Concurrency Revolution : NotesSoftware and the Concurrency Revolution : Notes
Software and the Concurrency Revolution : NotesSubhajit Sahu
 
Processes, Threads and Scheduler
Processes, Threads and SchedulerProcesses, Threads and Scheduler
Processes, Threads and SchedulerMunazza-Mah-Jabeen
 
Operating System 4 1193308760782240 2
Operating System 4 1193308760782240 2Operating System 4 1193308760782240 2
Operating System 4 1193308760782240 2mona_hakmy
 
Operating System 4
Operating System 4Operating System 4
Operating System 4tech2click
 
Significance
SignificanceSignificance
SignificanceJulie May
 
1 osi model
1 osi model1 osi model
1 osi modelSpacSec
 
Concurrency and Parallelism, Asynchronous Programming, Network Programming
Concurrency and Parallelism, Asynchronous Programming, Network ProgrammingConcurrency and Parallelism, Asynchronous Programming, Network Programming
Concurrency and Parallelism, Asynchronous Programming, Network ProgrammingPrabu U
 
Introto netthreads-090906214344-phpapp01
Introto netthreads-090906214344-phpapp01Introto netthreads-090906214344-phpapp01
Introto netthreads-090906214344-phpapp01Aravindharamanan S
 
The deep learning tour - Q1 2017
The deep learning tour - Q1 2017 The deep learning tour - Q1 2017
The deep learning tour - Q1 2017 Eran Shlomo
 
Network and distributed systems
Network and distributed systemsNetwork and distributed systems
Network and distributed systemsSri Prasanna
 

Semelhante a Introduction to Cluster Computing and Map Reduce (from Google) (20)

Lec1 Intro
Lec1 IntroLec1 Intro
Lec1 Intro
 
Lec1 Intro
Lec1 IntroLec1 Intro
Lec1 Intro
 
Introduction & Parellelization on large scale clusters
Introduction & Parellelization on large scale clustersIntroduction & Parellelization on large scale clusters
Introduction & Parellelization on large scale clusters
 
Distributed computing presentation
Distributed computing presentationDistributed computing presentation
Distributed computing presentation
 
Multithreading 101
Multithreading 101Multithreading 101
Multithreading 101
 
Software and the Concurrency Revolution : Notes
Software and the Concurrency Revolution : NotesSoftware and the Concurrency Revolution : Notes
Software and the Concurrency Revolution : Notes
 
Again music
Again musicAgain music
Again music
 
Processes, Threads and Scheduler
Processes, Threads and SchedulerProcesses, Threads and Scheduler
Processes, Threads and Scheduler
 
Operating System 4 1193308760782240 2
Operating System 4 1193308760782240 2Operating System 4 1193308760782240 2
Operating System 4 1193308760782240 2
 
Operating System 4
Operating System 4Operating System 4
Operating System 4
 
Significance
SignificanceSignificance
Significance
 
1 osi model
1 osi model1 osi model
1 osi model
 
Concurrency and Parallelism, Asynchronous Programming, Network Programming
Concurrency and Parallelism, Asynchronous Programming, Network ProgrammingConcurrency and Parallelism, Asynchronous Programming, Network Programming
Concurrency and Parallelism, Asynchronous Programming, Network Programming
 
Introducing Parallel Pixie Dust
Introducing Parallel Pixie DustIntroducing Parallel Pixie Dust
Introducing Parallel Pixie Dust
 
CN QNAs.pdf
CN QNAs.pdfCN QNAs.pdf
CN QNAs.pdf
 
Introto netthreads-090906214344-phpapp01
Introto netthreads-090906214344-phpapp01Introto netthreads-090906214344-phpapp01
Introto netthreads-090906214344-phpapp01
 
Parallel computing persentation
Parallel computing persentationParallel computing persentation
Parallel computing persentation
 
The deep learning tour - Q1 2017
The deep learning tour - Q1 2017 The deep learning tour - Q1 2017
The deep learning tour - Q1 2017
 
Osi model
Osi modelOsi model
Osi model
 
Network and distributed systems
Network and distributed systemsNetwork and distributed systems
Network and distributed systems
 

Mais de Sri Prasanna (20)

Qr codes para tech radar
Qr codes para tech radarQr codes para tech radar
Qr codes para tech radar
 
Qr codes para tech radar 2
Qr codes para tech radar 2Qr codes para tech radar 2
Qr codes para tech radar 2
 
Test
TestTest
Test
 
Test
TestTest
Test
 
assds
assdsassds
assds
 
assds
assdsassds
assds
 
asdsa
asdsaasdsa
asdsa
 
dsd
dsddsd
dsd
 
About stacks
About stacksAbout stacks
About stacks
 
About Stacks
About  StacksAbout  Stacks
About Stacks
 
About Stacks
About  StacksAbout  Stacks
About Stacks
 
About Stacks
About  StacksAbout  Stacks
About Stacks
 
About Stacks
About  StacksAbout  Stacks
About Stacks
 
About Stacks
About  StacksAbout  Stacks
About Stacks
 
About Stacks
About StacksAbout Stacks
About Stacks
 
About Stacks
About StacksAbout Stacks
About Stacks
 
Mapreduce: Theory and implementation
Mapreduce: Theory and implementationMapreduce: Theory and implementation
Mapreduce: Theory and implementation
 
Other distributed systems
Other distributed systemsOther distributed systems
Other distributed systems
 
Distributed file systems
Distributed file systemsDistributed file systems
Distributed file systems
 
Map reduce (from Google)
Map reduce (from Google)Map reduce (from Google)
Map reduce (from Google)
 

Último

ASRock Industrial FDO Solutions in Action for Industrial Edge AI _ Kenny at A...
ASRock Industrial FDO Solutions in Action for Industrial Edge AI _ Kenny at A...ASRock Industrial FDO Solutions in Action for Industrial Edge AI _ Kenny at A...
ASRock Industrial FDO Solutions in Action for Industrial Edge AI _ Kenny at A...FIDO Alliance
 
Oauth 2.0 Introduction and Flows with MuleSoft
Oauth 2.0 Introduction and Flows with MuleSoftOauth 2.0 Introduction and Flows with MuleSoft
Oauth 2.0 Introduction and Flows with MuleSoftshyamraj55
 
Choosing the Right FDO Deployment Model for Your Application _ Geoffrey at In...
Choosing the Right FDO Deployment Model for Your Application _ Geoffrey at In...Choosing the Right FDO Deployment Model for Your Application _ Geoffrey at In...
Choosing the Right FDO Deployment Model for Your Application _ Geoffrey at In...FIDO Alliance
 
WebRTC and SIP not just audio and video @ OpenSIPS 2024
WebRTC and SIP not just audio and video @ OpenSIPS 2024WebRTC and SIP not just audio and video @ OpenSIPS 2024
WebRTC and SIP not just audio and video @ OpenSIPS 2024Lorenzo Miniero
 
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
 
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
 
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
 
ERP Contender Series: Acumatica vs. Sage Intacct
ERP Contender Series: Acumatica vs. Sage IntacctERP Contender Series: Acumatica vs. Sage Intacct
ERP Contender Series: Acumatica vs. Sage IntacctBrainSell Technologies
 
Intro in Product Management - Коротко про професію продакт менеджера
Intro in Product Management - Коротко про професію продакт менеджераIntro in Product Management - Коротко про професію продакт менеджера
Intro in Product Management - Коротко про професію продакт менеджераMark Opanasiuk
 
What's New in Teams Calling, Meetings and Devices April 2024
What's New in Teams Calling, Meetings and Devices April 2024What's New in Teams Calling, Meetings and Devices April 2024
What's New in Teams Calling, Meetings and Devices April 2024Stephanie Beckett
 
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
 
WebAssembly is Key to Better LLM Performance
WebAssembly is Key to Better LLM PerformanceWebAssembly is Key to Better LLM Performance
WebAssembly is Key to Better LLM PerformanceSamy Fodil
 
1111 ChatGPT Prompts PDF Free Download - Prompts for ChatGPT
1111 ChatGPT Prompts PDF Free Download - Prompts for ChatGPT1111 ChatGPT Prompts PDF Free Download - Prompts for ChatGPT
1111 ChatGPT Prompts PDF Free Download - Prompts for ChatGPTiSEO AI
 
Enterprise Knowledge Graphs - Data Summit 2024
Enterprise Knowledge Graphs - Data Summit 2024Enterprise Knowledge Graphs - Data Summit 2024
Enterprise Knowledge Graphs - Data Summit 2024Enterprise Knowledge
 
Where to Learn More About FDO _ Richard at FIDO Alliance.pdf
Where to Learn More About FDO _ Richard at FIDO Alliance.pdfWhere to Learn More About FDO _ Richard at FIDO Alliance.pdf
Where to Learn More About FDO _ Richard at FIDO Alliance.pdfFIDO Alliance
 
TEST BANK For, Information Technology Project Management 9th Edition Kathy Sc...
TEST BANK For, Information Technology Project Management 9th Edition Kathy Sc...TEST BANK For, Information Technology Project Management 9th Edition Kathy Sc...
TEST BANK For, Information Technology Project Management 9th Edition Kathy Sc...marcuskenyatta275
 
WSO2CONMay2024OpenSourceConferenceDebrief.pptx
WSO2CONMay2024OpenSourceConferenceDebrief.pptxWSO2CONMay2024OpenSourceConferenceDebrief.pptx
WSO2CONMay2024OpenSourceConferenceDebrief.pptxJennifer Lim
 
Microsoft CSP Briefing Pre-Engagement - Questionnaire
Microsoft CSP Briefing Pre-Engagement - QuestionnaireMicrosoft CSP Briefing Pre-Engagement - Questionnaire
Microsoft CSP Briefing Pre-Engagement - QuestionnaireExakis Nelite
 
AI mind or machine power point presentation
AI mind or machine power point presentationAI mind or machine power point presentation
AI mind or machine power point presentationyogeshlabana357357
 

Último (20)

ASRock Industrial FDO Solutions in Action for Industrial Edge AI _ Kenny at A...
ASRock Industrial FDO Solutions in Action for Industrial Edge AI _ Kenny at A...ASRock Industrial FDO Solutions in Action for Industrial Edge AI _ Kenny at A...
ASRock Industrial FDO Solutions in Action for Industrial Edge AI _ Kenny at A...
 
Oauth 2.0 Introduction and Flows with MuleSoft
Oauth 2.0 Introduction and Flows with MuleSoftOauth 2.0 Introduction and Flows with MuleSoft
Oauth 2.0 Introduction and Flows with MuleSoft
 
Choosing the Right FDO Deployment Model for Your Application _ Geoffrey at In...
Choosing the Right FDO Deployment Model for Your Application _ Geoffrey at In...Choosing the Right FDO Deployment Model for Your Application _ Geoffrey at In...
Choosing the Right FDO Deployment Model for Your Application _ Geoffrey at In...
 
WebRTC and SIP not just audio and video @ OpenSIPS 2024
WebRTC and SIP not just audio and video @ OpenSIPS 2024WebRTC and SIP not just audio and video @ OpenSIPS 2024
WebRTC and SIP not just audio and video @ OpenSIPS 2024
 
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
 
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
 
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
 
ERP Contender Series: Acumatica vs. Sage Intacct
ERP Contender Series: Acumatica vs. Sage IntacctERP Contender Series: Acumatica vs. Sage Intacct
ERP Contender Series: Acumatica vs. Sage Intacct
 
Intro in Product Management - Коротко про професію продакт менеджера
Intro in Product Management - Коротко про професію продакт менеджераIntro in Product Management - Коротко про професію продакт менеджера
Intro in Product Management - Коротко про професію продакт менеджера
 
What's New in Teams Calling, Meetings and Devices April 2024
What's New in Teams Calling, Meetings and Devices April 2024What's New in Teams Calling, Meetings and Devices April 2024
What's New in Teams Calling, Meetings and Devices April 2024
 
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
 
WebAssembly is Key to Better LLM Performance
WebAssembly is Key to Better LLM PerformanceWebAssembly is Key to Better LLM Performance
WebAssembly is Key to Better LLM Performance
 
1111 ChatGPT Prompts PDF Free Download - Prompts for ChatGPT
1111 ChatGPT Prompts PDF Free Download - Prompts for ChatGPT1111 ChatGPT Prompts PDF Free Download - Prompts for ChatGPT
1111 ChatGPT Prompts PDF Free Download - Prompts for ChatGPT
 
Enterprise Knowledge Graphs - Data Summit 2024
Enterprise Knowledge Graphs - Data Summit 2024Enterprise Knowledge Graphs - Data Summit 2024
Enterprise Knowledge Graphs - Data Summit 2024
 
Where to Learn More About FDO _ Richard at FIDO Alliance.pdf
Where to Learn More About FDO _ Richard at FIDO Alliance.pdfWhere to Learn More About FDO _ Richard at FIDO Alliance.pdf
Where to Learn More About FDO _ Richard at FIDO Alliance.pdf
 
TEST BANK For, Information Technology Project Management 9th Edition Kathy Sc...
TEST BANK For, Information Technology Project Management 9th Edition Kathy Sc...TEST BANK For, Information Technology Project Management 9th Edition Kathy Sc...
TEST BANK For, Information Technology Project Management 9th Edition Kathy Sc...
 
WSO2CONMay2024OpenSourceConferenceDebrief.pptx
WSO2CONMay2024OpenSourceConferenceDebrief.pptxWSO2CONMay2024OpenSourceConferenceDebrief.pptx
WSO2CONMay2024OpenSourceConferenceDebrief.pptx
 
Microsoft CSP Briefing Pre-Engagement - Questionnaire
Microsoft CSP Briefing Pre-Engagement - QuestionnaireMicrosoft CSP Briefing Pre-Engagement - Questionnaire
Microsoft CSP Briefing Pre-Engagement - Questionnaire
 
AI mind or machine power point presentation
AI mind or machine power point presentationAI mind or machine power point presentation
AI mind or machine power point presentation
 

Introduction to Cluster Computing and Map Reduce (from Google)

  • 1. Distributed Computing Seminar Lecture 1: Introduction to Distributed Computing & Systems Background Christophe Bisciglia, Aaron Kimball, & Sierra Michels-Slettvet Summer 2007 Except where otherwise noted, the contents of this presentation are © Copyright 2007 University of Washington and are licensed under the Creative Commons Attribution 2.5 License.
  • 2.
  • 3.
  • 4. Computer Speedup Moore’s Law: “ The density of transistors on a chip doubles every 18 months, for the same cost” (1965) Image: Tom’s Hardware and not subject to the Creative Commons license applicable to the rest of this work. Image: Tom’s Hardware
  • 5.
  • 6.
  • 7.
  • 8.
  • 9.
  • 10.
  • 11.
  • 12.
  • 14.
  • 15. Parallelization Idea (2) In a parallel computation, we would like to have as many threads as we have processors. e.g., a four-processor computer would be able to run four threads at the same time.
  • 18.
  • 19.
  • 20.
  • 21.
  • 22.
  • 23.
  • 24.
  • 25.
  • 26. The “corrected” example Thread 1: void foo() { sem.lock(); x++; y = x; sem.unlock(); } Thread 2: void bar() { sem.lock(); y++; x+=3; sem.unlock(); } Global var “Semaphore sem = new Semaphore();” guards access to x & y
  • 27.
  • 28. The final example Thread 1: void foo() { sem.lock(); x++; y = x; fooDone = true; sem.unlock(); fooFinishedCV.notify(); } Thread 2: void bar() { sem.lock(); if(!fooDone) fooFinishedCV.wait(sem); y++; x+=3; sem.unlock(); } Global vars: Semaphore sem = new Semaphore(); ConditionVar fooFinishedCV = new ConditionVar(); boolean fooDone = false;
  • 29. Too Much Synchronization? Deadlock Synchronization becomes even more complicated when multiple locks can be used Can cause entire system to “get stuck” Thread A: semaphore1.lock(); semaphore2.lock(); /* use data guarded by semaphores */ semaphore1.unlock(); semaphore2.unlock(); Thread B: semaphore2.lock(); semaphore1.lock(); /* use data guarded by semaphores */ semaphore1.unlock(); semaphore2.unlock(); (Image: RPI CSCI.4210 Operating Systems notes)
  • 30.
  • 32.
  • 33.
  • 34.
  • 35.
  • 36.
  • 37.

Notas do Editor

  1. There are multiple possible final states. Y is definitely a problem, because we don’t know if it will be “1” or “7”… but X can also be 7, 10, or 11!
  2. Inform students that the term we want here is “race condition”
  3. Ask: are there still any problems? (Yes – we still have two possible outcomes. We want some other system that allows us to serialize access on an event.)
  4. Go over wait() / notify() / broadcast() --- must be combined with a semaphore!