Chapter 4: Threads PDF

Chapter 4: Threads Operating System Concepts – 9th Edition Silberschatz, Galvin and Gagne ©2013  Chapter 4: Threads Overview Multicore Programming Multithreading Models Thread Libraries...

Chapter 4: Threads Operating System Concepts – 9th Edition Silberschatz, Galvin and Gagne ©2013  Chapter 4: Threads Overview Multicore Programming Multithreading Models Thread Libraries Implicit Threading Threading Issues Operating System Examples Operating System Concepts – 9th Edition 4.2 Silberschatz, Galvin and Gagne ©2013  Objectives To introduce the notion of a thread—a fundamental unit of CPU utilization that forms the basis of multithreaded computer systems To discuss the APIs for the Pthreads, Windows, and Java thread libraries To explore several strategies that provide implicit threading To examine issues related to multithreaded programming To cover operating system support for threads in Windows and Linux Operating System Concepts – 9th Edition 4.3 Silberschatz, Galvin and Gagne ©2013  Uniprogramming Program A Run Wait Run Wait Time (a) Uniprogramming The processor spends a certain amount of time executing, Program A it reaches until Run an I/OWait instruction; it Run Wait must then wait until that I/O instruction concludes before proceeding Program B Wait Run Wait Run Wait © 2017 Pearson Education, Inc., Hoboken, NJ. All rights reserved.System Concepts – 9th Edition Operating 4.4 Silberschatz, Galvin and Gagne ©2013  Program A Run Wait Run Wait Multiprogramming Time (a) Uniprogramming Program A Run Wait Run Wait Program B Wait Run Wait Run Wait Run Run Run Run Combined Wait Wait A B A B Time (b) Multiprogramming with two programs There must be enough memory to hold the OS (resident monitor) and one user Program A program Run Wait Run Wait When one job needs to wait for I/O, the processor can switch to the other job, which is likely Program B not Wait waiting Runfor I/O Wait Run Wait © 2017 Pearson Education, Inc., Hoboken, NJ. All rights reserved.System Concepts – 9th Edition Operating 4.5 Silberschatz, Galvin and Gagne ©2013  Program B Wait Run Wait Run Wait Run Run Run Run Combined Wait Wait A B A B Multiprogramming Time (b) Multiprogramming with two programs Program A Run Wait Run Wait Program B Wait Run Wait Run Wait Program C Wait Run Wait Run Wait Run Run Run Run Run Run Combined Wait Wait A B C A B C Time (c) Multiprogramming with three programs Figure 2.5 Multiprogramming Example  Also known as multitasking  Memory is expanded to hold three, four, or more programs and switch among all of them © 2017 Pearson Education, Inc., Hoboken, NJ. All rights reserved.System Concepts – 9th Edition Operating 4.6 Silberschatz, Galvin and Gagne ©2013  Multiprogramming Example JOB1 JOB2 JOB3 Type of job Heavy compute Heavy I/O Heavy I/O Duration 5 min 15 min 10 min Memory required 50 M 100 M 75 M Need disk? No No Yes Need terminal? No Yes No Need printer? No No Yes Table 2.1 Sample Program Execution Attributes © 2017 Pearson Education, Inc., Hoboken, NJ. All rights reserved.System Concepts – 9th Edition Operating 4.7 Silberschatz, Galvin and Gagne ©2013  Uniprogramming Multiprogramming Processor use 20% 40% Memory use 33% 67% Disk use 33% 67% Printer use 33% 67% Elapsed time 30 min 15 min Throughput 6 jobs/hr 12 jobs/hr Mean response time 18 min 10 min Table 2.2 Effects of Multiprogramming on Resource Utilization © 2017 Pearson Education, Inc., Hoboken, NJ. All rights reserved.System Concepts – 9th Edition Operating 4.8 Silberschatz, Galvin and Gagne ©2013  100% 100% CPU CPU 0% 0% 100% 100% Memory Memory 0% 0% 100% 100% Disk Disk 0% 0% 100% 100% Terminal Terminal 0% 0% 100% 100% Printer Printer 0% 0% Job History Job History JOB1 JOB1 JOB2 JOB3 JOB2 0 5 10 15 20 25 30 minutes JOB3 0 5 10 15 time minutes time (a) Uniprogramming (b) Multiprogramming Figure 2.6 Utilization Histograms © 2017 Pearson Education, Inc., Hoboken, NJ. All rights reserved.System Concepts – 9th Edition Operating 4.9 Silberschatz, Galvin and Gagne ©2013  Some Concepts Operating System Concepts – 9th Edition 4.10 Silberschatz, Galvin and Gagne ©2013  Some Concepts Operating System Concepts – 9th Edition 4.11 Silberschatz, Galvin and Gagne ©2013  Some Concepts Operating System Concepts – 9th Edition 4.12 Silberschatz, Galvin and Gagne ©2013  Some Concepts Operating System Concepts – 9th Edition 4.13 Silberschatz, Galvin and Gagne ©2013  Some Concepts Operating System Concepts – 9th Edition 4.14 Silberschatz, Galvin and Gagne ©2013  Motivation Most modern applications are multithreaded Threads run within application Multiple tasks with the application can be implemented by separate threads Update display Fetch data Spell checking Answer a network request Process creation is heavy-weight while thread creation is light-weight Can simplify code, increase efficiency Kernels are generally multithreaded Operating System Concepts – 9th Edition 4.15 Silberschatz, Galvin and Gagne ©2013  Benefits Responsiveness – may allow continued execution if part of process is blocked, especially important for user interfaces Resource Sharing – threads share resources of process, easier than shared memory or message passing Economy – cheaper than process creation, thread switching lower overhead than context switching Scalability – process can take advantage of multiprocessor architectures Operating System Concepts – 9th Edition 4.16 Silberschatz, Galvin and Gagne ©2013  Multicore Programming Multicore or multiprocessor systems putting pressure on programmers, challenges include: Dividing activities Balance Data splitting Data dependency Testing and debugging Parallelism implies a system can perform more than one task simultaneously Concurrency supports more than one task making progress Single processor / core, scheduler providing concurrency Operating System Concepts – 9th Edition 4.17 Silberschatz, Galvin and Gagne ©2013  Multicore Programming (Cont.) Types of parallelism Data parallelism – distributes subsets of the same data across multiple cores, same operation on each Task parallelism – distributing threads across cores, each thread performing unique operation As # of threads grows, so does architectural support for threading CPUs have cores as well as hardware threads Consider Oracle SPARC T4 with 8 cores, and 8 hardware threads per core Operating System Concepts – 9th Edition 4.18 Silberschatz, Galvin and Gagne ©2013  Multithreaded Server Architecture Operating System Concepts – 9th Edition 4.19 Silberschatz, Galvin and Gagne ©2013  Concurrency vs. Parallelism Concurrent execution on single-core system: Parallelism on a multi-core system: Operating System Concepts – 9th Edition 4.20 Silberschatz, Galvin and Gagne ©2013  Single and Multithreaded Processes Operating System Concepts – 9th Edition 4.21 Silberschatz, Galvin and Gagne ©2013  Amdahl’s Law Identifies performance gains from adding additional cores to an application that has both serial and parallel components S is serial portion N processing cores That is, if application is 75% parallel / 25% serial, moving from 1 to 2 cores results in speedup of 1.6 times As N approaches infinity, speedup approaches 1 / S Serial portion of an application has disproportionate effect on performance gained by adding additional cores But does the law take into account contemporary multicore systems? Operating System Concepts – 9th Edition 4.22 Silberschatz, Galvin and Gagne ©2013  User Threads and Kernel Threads User threads - management done by user-level threads library Three primary thread libraries: POSIX Pthreads Windows threads Java threads Kernel threads - Supported by the Kernel Examples – virtually all general purpose operating systems, including: Windows Solaris Linux Tru64 UNIX Mac OS X Operating System Concepts – 9th Edition 4.23 Silberschatz, Galvin and Gagne ©2013  Multithreading Models Many-to-One One-to-One Many-to-Many Operating System Concepts – 9th Edition 4.24 Silberschatz, Galvin and Gagne ©2013  Many-to-One Many user-level threads mapped to single kernel thread One thread blocking causes all to block Multiple threads may not run in parallel on muticore system because only one may be in kernel at a time Few systems currently use this model Examples: Solaris Green Threads GNU Portable Threads Operating System Concepts – 9th Edition 4.25 Silberschatz, Galvin and Gagne ©2013  One-to-One Each user-level thread maps to kernel thread Creating a user-level thread creates a kernel thread More concurrency than many-to-one Number of threads per process sometimes restricted due to overhead Examples Windows Linux Solaris 9 and later Operating System Concepts – 9th Edition 4.26 Silberschatz, Galvin and Gagne ©2013  Many-to-Many Model Allows many user level threads to be mapped to many kernel threads Allows the operating system to create a sufficient number of kernel threads Solaris prior to version 9 Windows with the ThreadFiber package Operating System Concepts – 9th Edition 4.27 Silberschatz, Galvin and Gagne ©2013  Two-level Model Similar to M:M, except that it allows a user thread to be bound to kernel thread Examples IRIX HP-UX Tru64 UNIX Solaris 8 and earlier Operating System Concepts – 9th Edition 4.28 Silberschatz, Galvin and Gagne ©2013  Thread Libraries Thread library provides programmer with API for creating and managing threads Two primary ways of implementing Library entirely in user space Kernel-level library supported by the OS Operating System Concepts – 9th Edition 4.29 Silberschatz, Galvin and Gagne ©2013  Pthreads May be provided either as user-level or kernel-level A POSIX standard (IEEE 1003.1c) API for thread creation and synchronization Specification, not implementation API specifies behavior of the thread library, implementation is up to development of the library Common in UNIX operating systems (Solaris, Linux, Mac OS X) Operating System Concepts – 9th Edition 4.30 Silberschatz, Galvin and Gagne ©2013  Pthreads Example Operating System Concepts – 9th Edition 4.31 Silberschatz, Galvin and Gagne ©2013  Pthreads Example (Cont.) Operating System Concepts – 9th Edition 4.32 Silberschatz, Galvin and Gagne ©2013  Pthreads Code for Joining 10 Threads Operating System Concepts – 9th Edition 4.33 Silberschatz, Galvin and Gagne ©2013  A Simple pthreads Example pthread1.c Operating System Concepts – 9th Edition 4.34 Silberschatz, Galvin and Gagne ©2013  A Not So Simple pthreads Example pthread2.c Operating System Concepts – 9th Edition 4.35 Silberschatz, Galvin and Gagne ©2013  Windows Multithreaded C Program Operating System Concepts – 9th Edition 4.36 Silberschatz, Galvin and Gagne ©2013  Windows Multithreaded C Program (Cont.) Operating System Concepts – 9th Edition 4.37 Silberschatz, Galvin and Gagne ©2013  Java Threads Java threads are managed by the JVM Typically implemented using the threads model provided by underlying OS Java threads may be created by: Extending Thread class Implementing the Runnable interface Operating System Concepts – 9th Edition 4.38 Silberschatz, Galvin and Gagne ©2013  Java Multithreaded Program Operating System Concepts – 9th Edition 4.39 Silberschatz, Galvin and Gagne ©2013  Java Multithreaded Program (Cont.) Operating System Concepts – 9th Edition 4.40 Silberschatz, Galvin and Gagne ©2013  Implicit Threading Growing in popularity as numbers of threads increase, program correctness more difficult with explicit threads Creation and management of threads done by compilers and run-time libraries rather than programmers Three methods explored Thread Pools OpenMP Grand Central Dispatch Other methods include Microsoft Threading Building Blocks (TBB), java.util.concurrent package Operating System Concepts – 9th Edition 4.41 Silberschatz, Galvin and Gagne ©2013  Thread Pools Create a number of threads in a pool where they await work Advantages: Usually slightly faster to service a request with an existing thread than create a new thread Allows the number of threads in the application(s) to be bound to the size of the pool Separating task to be performed from mechanics of creating task allows different strategies for running task  i.e.Tasks could be scheduled to run periodically Windows API supports thread pools: Operating System Concepts – 9th Edition 4.42 Silberschatz, Galvin and Gagne ©2013  OpenMP Set of compiler directives and an API for C, C++, FORTRAN Provides support for parallel programming in shared-memory environments Identifies parallel regions – blocks of code that can run in parallel #pragma omp parallel Create as many threads as there are cores #pragma omp parallel for for(i=0;i