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Chapter 4: Threads Operating System Concepts Silberschatz, Galvin and Gagne  Chapter 4: Threads Introduction Multicore Programming Multithreading Models Thread Libraries Impl...

Chapter 4: Threads Operating System Concepts Silberschatz, Galvin and Gagne  Chapter 4: Threads Introduction Multicore Programming Multithreading Models Thread Libraries Implicit Threading Threading Issues Examples Operating System Concepts 3.30 Silberschatz, Galvin and Gagne  Introduction 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 3.31 Silberschatz, Galvin and Gagne  Multithreaded Server Architecture Operating System Concepts 3.32 Silberschatz, Galvin and Gagne  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 3.33 Silberschatz, Galvin and Gagne  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 3.34 Silberschatz, Galvin and Gagne  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 3.35 Silberschatz, Galvin and Gagne  Concurrency vs. Parallelism Concurrent execution on single-core system: Parallelism on a multi-core system: Operating System Concepts 3.36 Silberschatz, Galvin and Gagne  Single and Multithreaded Processes Operating System Concepts 3.37 Silberschatz, Galvin and Gagne  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 3.38 Silberschatz, Galvin and Gagne  Multithreading Models Many-to-One One-to-One Many-to-Many Two-Level Operating System Concepts 3.39 Silberschatz, Galvin and Gagne  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 3.40 Silberschatz, Galvin and Gagne  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 3.41 Silberschatz, Galvin and Gagne  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 Examples:  Solaris prior to version 9  Windows with the ThreadFiber package Operating System Concepts 3.42 Silberschatz, Galvin and Gagne  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 3.43 Silberschatz, Galvin and Gagne  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 Pthreads May be provided either as user-level or kernel-level A POSIX standard (IEEE 1003.1c) API for thread creation and synchronization It is 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 3.44 Silberschatz, Galvin and Gagne  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 3.45 Silberschatz, Galvin and Gagne  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 Two methods are explored  Thread Pools  Grand Central Dispatch Operating System Concepts 3.46 Silberschatz, Galvin and Gagne  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 3.47 Silberschatz, Galvin and Gagne  Grand Central Dispatch Apple technology for Mac OS X and iOS operating systems Extensions to C, C++ languages, API, and run-time library Allows identification of parallel sections Manages most of the details of threading Blocks placed in dispatch queue  Assigned to available thread in thread pool when removed from queue Operating System Concepts 3.48 Silberschatz, Galvin and Gagne  Threading Issues Semantics of fork() and exec() system calls Signal handling  Synchronous and asynchronous Thread cancellation of target thread  Asynchronous or deferred Thread-local storage Scheduler Activations Operating System Concepts 3.49 Silberschatz, Galvin and Gagne  Signal Handling  Signals are used in UNIX systems to notify a process that a particular event has occurred.  A signal handler is used to process signals 1. Signal is generated by particular event 2. Signal is delivered to a process 3. Signal is handled by one of two signal handlers: 1. default 2. user-defined  Every signal has default handler that kernel runs when handling signal  User-defined signal handler can override default  For single-threaded, signal delivered to process Operating System Concepts 3.50 Silberschatz, Galvin and Gagne  Signal Handling (Cont.) Where should a signal be delivered for multi-threaded?  Deliver the signal to the thread to which the signal applies  Deliver the signal to every thread in the process  Deliver the signal to certain threads in the process  Assign a specific thread to receive all signals for the process Operating System Concepts 3.51 Silberschatz, Galvin and Gagne  Thread Cancellation Terminating a thread before it has finished Thread to be canceled is target thread Two general approaches:  Asynchronous cancellation terminates the target thread immediately  Deferred cancellation allows the target thread to periodically check if it should be cancelled Operating System Concepts 3.52 Silberschatz, Galvin and Gagne  Scheduler Activations Both M:M and Two-level models require communication to maintain the appropriate number of kernel threads allocated to the application Typically use an intermediate data structure between user and kernel threads – lightweight process (LWP)  Appears to be a virtual processor on which process can schedule user thread to run  Each LWP attached to kernel thread  How many LWPs to create? Scheduler activations provide upcalls - a communication mechanism from the kernel to the upcall handler in the thread library This communication allows an application to maintain the correct number kernel threads Operating System Concepts 3.53 Silberschatz, Galvin and Gagne  Example 1: Windows Threads Windows implements the Windows API – primary API for Win 98, Win NT, Win 2000, Win XP, and Win 7 Implements the one-to-one mapping, kernel-level Each thread contains  A thread id  Register set representing state of processor  Separate user and kernel stacks for when thread runs in user mode or kernel mode  Private data storage area used by run-time libraries and dynamic link libraries (DLLs) The register set, stacks, and private storage area are known as the context of the thread Operating System Concepts 3.54 Silberschatz, Galvin and Gagne  Example 2: Linux Threads Linux refers to them as tasks rather than threads Thread creation is done through clone() system call clone() allows a child task to share the address space of the parent task (process)  Flags control behavior Operating System Concepts 3.55 Silberschatz, Galvin and Gagne