Download Threads in Operating Systems: Multicore Programming and Threading Models and more Lecture notes Operating Systems in PDF only on Docsity!
Operating System Concepts – 9th^ Edition Silberschatz, Galvin and Gagne ©
Chapter 4: Threads
Operating System Concepts – 9th^ Edition 4.2 Silberschatz, Galvin and Gagne ©
Chapter 4: Threads
(^) Overview (^) Multicore Programming (^) Multithreading Models (^) Thread Libraries (^) Implicit Threading (^) Threading Issues (^) Operating System Examples Operating System Concepts – 9th^ Edition 4.3 Silberschatz, Galvin and Gagne ©
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 4.4 Silberschatz, Galvin and Gagne ©
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 4.6 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 – 9th^ Edition 4.7 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 – 9th^ Edition 4.8 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 (Simalteneious Multi Threading SMT or Hypter Threading HT)
- Consider Oracle SPARC T4 with 8 cores, and 8 hardware threads per core (^) Analogy (^) Think of a core as a chef in a kitchen, capable of cooking a dish. (^) More cores = More chefs, each working on separate dishes. (^) More threads per core = Each chef has two hands (but still limited by overall resources in the kitchen).
Operating System Concepts – 9th^ Edition 4.13 Silberschatz, Galvin and Gagne ©
Multithreading Models
(^) Many-to-One (^) One-to-One (^) Many-to-Many
Operating System Concepts – 9th^ Edition 4.19 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
Operating System Concepts – 9th^ Edition 4.25 Silberschatz, Galvin and Gagne ©
Grand Central Dispatch
(^) A concurrency framework developed by Apple (macOS/iOS) that uses dispatch queues for managing multiple tasks efficiently. (^) Tasks are automatically scheduled on available CPU cores. (^) No need to create/join threads (^) Automatically balances workload (^) Example
- (^) Apple technology for Mac OS X and iOS operating systems
- (^) Extensions to C, C++ languages, API, and run-time library (^) Assigned to available thread in thread pool when removed from queue Operating System Concepts – 9th^ Edition 4.26 Silberschatz, Galvin and Gagne ©
Threading Issues
(^) When working with multithreading, several issues arise due to the complexity of managing multiple threads in a process. Below are some of the key challenges:
- Semantics of fork() and exec() in Multithreaded Programs
- Signal Handling in Multithreaded Programs
- (^) Thread Cancellation
- (^) Scheduler Activations
- Thread-Local Storage (TLS) Operating System Concepts – 9th^ Edition 4.27 Silberschatz, Galvin and Gagne ©
Semantics of fork() and exec()
(^) The behavior of fork() and exec() changes when multiple threads are present. The key question is: (^) If one thread calls fork(), should the new process copy all threads or just the calling thread? (^) UNIX Solutions: (^) UNIX systems provide two versions of fork(): (^) Fork Type Behavior (^) Full Process Fork Duplicates all threads of the parent process (^) Threaded Fork Only the calling thread is duplicated in the child process (^) Best Practice: In a multithreaded program, after fork(), call exec() to start a new process, avoiding inconsistencies caused by duplicated threads. Operating System Concepts – 9th^ Edition 4.28 Silberschatz, Galvin and Gagne ©
Signal Handling
(^) Signal is an asynchronous notification sent to a process (or thread) by the operating system or another process to inform it that a specific event has occurred. (^) In a single-threaded program, signals are delivered directly to the process, but in multithreading, handling becomes more complex. (^) Types of Signal Handlings (^) Synchronous Signals: Occur as a direct result of thread execution (e.g., division by zero, invalid memory access). These are delivered to the thread that caused them. (^) Asynchronous Signals: Sent externally (e.g., SIGTERM, SIGINT from the keyboard). These signals must be handled properly in multithreaded environments. (^) Handling Signals in Threads: Three common strategies for signal delivery:
- Deliver the signal to all threads in the process.
- Deliver the signal to a specific thread.
- Deliver the signal to a single designated thread (most common approach).
Operating System Concepts – 9th^ Edition 4.29 Silberschatz, Galvin and Gagne ©
Thread Cancellation
(^) Thread cancellation is the ability to terminate a thread before it completes execution. This is useful in tasks like timeout handling or stopping unnecessary background computations. (^) Two general approaches or types of Thread Cancellation: (^) Asynchronous cancellation Terminates the thread immediately (unsafe, may leave resources locked). (^) Deferred cancellation Thread periodically checks for a cancellation request and cleans up before exiting (preferred). Operating System Concepts – 9th^ Edition 4.31 Silberschatz, Galvin and Gagne ©
Thread-Local Storage
(^) What is Thread-local storage (TLS) (^) TLS allows each thread to have its own copy of data. (^) Unlike global variables (shared across threads), TLS is unique to each thread. (^) Useful when threads need private storage (e.g., per-thread caching, logs).
- (^) Why Use TLS? (^) Needed when using thread pools (no direct control over thread creation). (^) Different from local variables (TLS persists across function calls). (^) Similar to static data, but each thread gets its own instance.
- Example: (^) C (GCC): __thread int myVar; (^) C++ : thread_local int myVar; (^) POSIX Threads (Pthreads): pthread_key_create() Operating System Concepts – 9th^ Edition 4.32 Silberschatz, Galvin and Gagne ©
Operating System Examples
(^) Windows Threads (^) Linux Threads
- Operating System Concepts – 9th Edition Silberschatz, Galvin and Gagne ©
