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Chapter 4: Threads Operating System Concepts – 9th Edition Silberschatz, Galvin and Gagne ©2013 Chapter 4: Threads n Overview n Multicore Programming n Multithreading Models n Thread Libraries n Implicit Threading n Threading Issues n Operating System Examples Operating System Concepts – 9th Edition 4.2 Silberschatz, Galvin and Gagne ©2013 Objectives n To introduce the notion of a thread—a fundamental unit of CPU utilization that forms the basis of multithreaded computer systems n To discuss the APIs for the Pthreads, Windows, and Java thread libraries n To explore several strategies that provide implicit threading n To examine issues related to multithreaded programming n To cover operating system support for threads in Windows and Linux Operating System Concepts – 9th Edition 4.3 Silberschatz, Galvin and Gagne ©2013 Motivation n Most modern applications are multithreaded n Threads run within application – a process always has one or more threads n Multiple tasks within the application can be implemented by separate threads n l Update display l Fetch data l Spell checking l Answer a network request Process creation is heavy-weight while thread creation is light-weight l Threads are often referred to as light-weight processes n Threading can greatly simplify code and increase efficiency n Kernels are generally multithreaded Operating System Concepts – 9th Edition 4.4 Silberschatz, Galvin and Gagne ©2013 Single and Multithreaded Processes Operating System Concepts – 9th Edition 4.5 Silberschatz, Galvin and Gagne ©2013 Multithreaded Server Architecture Operating System Concepts – 9th Edition 4.6 Silberschatz, Galvin and Gagne ©2013 Benefits n Benefits of threading: l Responsiveness – threading may allow one thread to continue execution if another thread is blocked. This is especially important for user interfaces. l Resource Sharing – threads share the resources of process (heap, globals, etc.) making communication easier than with shared memory or message passing. l Economy – Creating a thread is cheaper (faster) than creating a process. Switching between threads is lower overhead than context switching between processes l Scalability – threaded processes can take advantage of multiprocessor architectures Operating System Concepts – 9th Edition 4.7 Silberschatz, Galvin and Gagne ©2013 Multicore Programming n Multicore or multiprocessor systems are putting pressure on programmers, challenges include: l Dividing activities l Balance l Data splitting l Data dependency l Testing and debugging n Parallelism implies a system can perform more than one task simultaneously n Concurrency supports more than one task making progress l A single single processor / core can use a scheduler to provide concurrency (multiprogramming / timesharing) without parallelism Operating System Concepts – 9th Edition 4.8 Silberschatz, Galvin and Gagne ©2013 Concurrency vs. Parallelism n Concurrent execution on single-core system: n Parallelism on a multi-core system: Operating System Concepts – 9th Edition 4.9 Silberschatz, Galvin and Gagne ©2013 Multicore Programming (Cont.) n n Types of parallelism l Data parallelism – distributes subsets of the same data across multiple cores, same operation on each l Task parallelism – distributing threads across cores, each thread performing unique operation As # of threads grows, so does architectural support for threading l CPUs have multiple cores Each core may be able to store the context of several threads concurrently to speed switching between threads These concurrently loaded threads are known as hardware threads – Consider Oracle SPARC T4 with 8 cores and 8 hardware threads per core (64 hardware threads) – Consider Intel i7 with 4 cores and 2 threads per core (8 hardware threads) (Hyper Threading) Operating System Concepts – 9th Edition 4.10 Silberschatz, Galvin and Gagne ©2013 Amdahl’s Law n Amdahl’s Law identifies the performance gains from adding additional cores to an application that has both serial and parallel components n S is serial portion n N processing cores n That is, if application is 75% parallel / 25% serial, moving from 1 to 2 cores results in speedup of 1.6 times n As N approaches infinity, speedup approaches 1 / S The serial portion of an application has disproportionate effect on performance gained by adding additional cores n But does the law take into account contemporary multicore systems? Operating System Concepts – 9th Edition 4.11 Silberschatz, Galvin and Gagne ©2013 User Threads and Kernel Threads n There are two different types of threads: n User threads - management done by user-level threads library l n Three primary thread libraries: POSIX Pthreads Windows threads Java threads Kernel threads - Supported by the Kernel l Examples – virtually all general purpose operating systems, including: Windows Solaris Linux Tru64 UNIX Mac OS X Operating System Concepts – 9th Edition 4.12 Silberschatz, Galvin and Gagne ©2013 Multithreading Models n Kernel threads are maintained by the operating system and are used to allocate processor time. l The short-term scheduler is actually switch between kernel threads. n User threads are managed without kernel support. n For the user threads to run there must be a relationship between kernel threads and user threads. l Many-to-One: Many user threads are attached to one kernel thread l One-to-One: Every user thread is attached to exactly one kernel thread l Many-to-Many: User threads are not attached to specific kernel threads but multiplexed between them Operating System Concepts – 9th Edition 4.13 Silberschatz, Galvin and Gagne ©2013 Many-to-One n Many user-level threads mapped to single kernel thread n One thread blocking causes all to block n Multiple threads may not run in parallel on muticore system because only one may be in kernel at a time n Few systems currently use this model n Examples: l Solaris Green Threads l GNU Portable Threads Operating System Concepts – 9th Edition 4.14 Silberschatz, Galvin and Gagne ©2013 One-to-One n Each user-level thread maps to kernel thread n Creating a user-level thread creates a kernel thread n More concurrency than many-to-one – one thread blocking does not cause others to block n Number of threads per process sometimes restricted due to overhead – the system may be limited on the number of kernel threads that can be supported. n Examples l Windows l Linux l Solaris 9 and later Operating System Concepts – 9th Edition 4.15 Silberschatz, Galvin and Gagne ©2013 Many-to-Many Model n Allows many user level threads to be mapped to many kernel threads n Allows concurrency without imposing a limit on the number of user threads n Examples: l Solaris prior to version 9 l Windows with the ThreadFiber package Operating System Concepts – 9th Edition 4.16 Silberschatz, Galvin and Gagne ©2013 Two-level Model n Similar to M:M, except that it allows a user thread to be bound to kernel thread n Examples: l IRIX l HP-UX l Tru64 UNIX l Solaris 8 and earlier Operating System Concepts – 9th Edition 4.17 Silberschatz, Galvin and Gagne ©2013 Thread Libraries n A Thread library provides the programmer with an API for creating and managing threads n There are two primary ways this is implemented: l Library entirely in user space l Kernel-level library supported by the OS Operating System Concepts – 9th Edition 4.18 Silberschatz, Galvin and Gagne ©2013 Pthreads n Pthreads is a POSIX standard (IEEE 1003.1c) API for thread creation and synchronization l May be provided either as user-level or kernel-level l Specification, not implementation – different systems may implement the threads in different ways, but the API is consistent l API specifies behavior of the thread library, implementation is up to development of the library l Common in UNIX operating systems (Solaris, Linux, Mac OS X) Operating System Concepts – 9th Edition 4.19 Silberschatz, Galvin and Gagne ©2013 Pthreads Example /* Note: In Linux link with option -pthread */ #include <stdio.h> #include <pthread.h> int sum; /* this data is shared by the thread(s) */ void *runner(void *param); /* threads call this function */ int main(int argc, char *argv[]) { pthread_t tid; /* the thread identifier */ pthread_attr_t attr; /* set of thread attributes */ if (argc != 2) { fprintf(stderr, "usage: a.out <integer value>\n"); return -1; } if (atoi(argv[1]) < 0) { fprintf(stderr, "%d must be >= 0\n", atoi(argv[1])); return -1; } Operating System Concepts – 9th Edition 4.20 Silberschatz, Galvin and Gagne ©2013 Pthreads Example pthread_attr_init(&attr); /*get the default attributes */ /* create the thread */ pthread_create(&tid, &attr, runner, argv[1]); pthread_join(tid, NULL); /*wait for the thread to exit */ printf("sum = %d\n", sum); return 0; } /* The thread will begin control in this function */ void *runner(void *param) { int i, upper = atoi(param); sum = 0; for(i = 1; i <= upper; i++) sum += i; pthread_exit(0); } Operating System Concepts – 9th Edition 4.21 Silberschatz, Galvin and Gagne ©2013 Pthreads Code for Joining 10 Threads n When programming for multicore systems, a programmer may need to create multiple threads. l It may be helpful to keep track of the threads using an array. l The following code shows how to join on an array of 10 threads using a for loop. Operating System Concepts – 9th Edition 4.22 Silberschatz, Galvin and Gagne ©2013 Windows Threads n Creating threads in Windows is similar in concept. l Global data is shared between threads. l When a thread is created it begins in a programmer defined function. A point to this function is passed as a parameter when creating the thread. This function can also be passed parameters l The thread is created using CreateThread(). l The parent waits for the thread using WaitForSingleObject(). l To wait for multiple threads Windows has the WaitForMultipleObjects() function. Operating System Concepts – 9th Edition 4.23 Silberschatz, Galvin and Gagne ©2013 Windows Multithreaded C Program Operating System Concepts – 9th Edition 4.24 Silberschatz, Galvin and Gagne ©2013 Windows Multithreaded C Program (Cont.) Operating System Concepts – 9th Edition 4.25 Silberschatz, Galvin and Gagne ©2013 Java Threads n Java threads are managed by the JVM n Typically implemented using the threads model provided by underlying OS n Java threads may be created by: l Extending Thread class l Implementing the Runnable interface Operating System Concepts – 9th Edition 4.26 Silberschatz, Galvin and Gagne ©2013 Java Multithreaded Program Operating System Concepts – 9th Edition 4.27 Silberschatz, Galvin and Gagne ©2013 Java Multithreaded Program (Cont.) Operating System Concepts – 9th Edition 4.28 Silberschatz, Galvin and Gagne ©2013 Implicit Threading n As the number of threads used increases, it can be difficult for the programmer to keep track. n One way to address this is to transfer the creation of threads to compilers and runtime libraries. n Threads and created and joined automatically by library functions and the compiler. n We will explore three methods: n l Thread Pools l OpenMP l Grand Central Dispatch Other methods include Microsoft Threading Building Blocks (TBB), java.util.concurrent package Operating System Concepts – 9th Edition 4.29 Silberschatz, Galvin and Gagne ©2013 Thread Pools n Create a number of threads in a pool where they await work n Advantages: l It is usually slightly faster to service a request with an existing thread than create a new thread l It allows the number of threads in the application(s) to be bound to the size of the pool l Separating the task to be performed from the mechanics of creating task allows us to use different strategies for running task n i.e. Tasks could be scheduled to run periodically Windows API supports thread pools: Operating System Concepts – 9th Edition 4.30 Silberschatz, Galvin and Gagne ©2013 OpenMP n Set of compiler directives and an API for C, C++, FORTRAN n Provides support for parallel programming in shared-memory environments n 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<N;i++) { c[i] = a[i] + b[i]; } Run for loop in parallel Operating System Concepts – 9th Edition 4.31 Silberschatz, Galvin and Gagne ©2013 Grand Central Dispatch n Apple technology for Mac OS X and iOS operating systems n Extensions to C, C++ languages, API, and run-time library n Allows identification of parallel sections n Manages most of the details of threading n Block is in “^{ }” - ˆ{ printf("I am a block"); } n Blocks placed in dispatch queue l Assigned to available thread in thread pool when removed from queue Operating System Concepts – 9th Edition 4.32 Silberschatz, Galvin and Gagne ©2013 Grand Central Dispatch n Two types of dispatch queues: l serial – blocks removed in FIFO order, queue is per process, called main queue l concurrent – removed in FIFO order but several may be removed at a time n Programmers can create additional serial queues within program Three system wide queues with priorities low, default, high The following code submits a block to the concurrent queue with default priority. Operating System Concepts – 9th Edition 4.33 Silberschatz, Galvin and Gagne ©2013 Threading Issues n There are several issues that need to be considered in implementing a multithreaded environment. l The semantics of fork() and exec() system calls must change l Process signals be handling l Synchronous and asynchronous Thread cancellation of target thread Asynchronous or deferred l Thread-local storage l Scheduler activations Operating System Concepts – 9th Edition 4.34 Silberschatz, Galvin and Gagne ©2013 Semantics of fork() and exec() n n In a multithreaded environment, does fork()duplicate only the calling thread or all threads? l Some UNIXes have two versions of fork, one duplicates all threads and the other duplicates only the one that invoked fork. l If exec will be called immediately after fork, then it is wasteful to create multiple threads. exec() usually works as normal – replace the running process including all threads Operating System Concepts – 9th Edition 4.35 Silberschatz, Galvin and Gagne ©2013 Signal Handling n Signals are used in UNIX systems to notify a process that a particular event has occurred. n A signal handler is used to process signals n 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 the kernel runs when handling signal l User-defined signal handler can override the default l For a single-threaded process, the signal is delivered to process Operating System Concepts – 9th Edition 4.36 Silberschatz, Galvin and Gagne ©2013 Signal Handling (Cont.) n Where should a signal be delivered for a multi-threaded process? n Possible answers: Deliver the signal to the thread to which the signal applies l n l Deliver the signal to every thread in the process l Deliver the signal to certain threads in the process l Assign a specific thread to receive all signals for the process Different types of signals may be delivered using different methods. l Synchronous signals need to be delivered to the thread generating the signal. l Asynchronous signals may be delivered in different ways Some should be delivered to all threads (e.g. <control><C> process termination). Operating System Concepts – 9th Edition 4.37 Silberschatz, Galvin and Gagne ©2013 Thread Cancellation n It is sometimes necessary to terminate a thread before it has finished n The thread to be canceled is the target thread n Two general approaches: n l Asynchronous cancellation terminates the target thread immediately l Deferred cancellation allows the target thread to periodically check if it should be cancelled The following is Pthread code to create and cancel a thread: Operating System Concepts – 9th Edition 4.38 Silberschatz, Galvin and Gagne ©2013 Thread Cancellation (Cont.) Invoking thread cancellation requests cancellation, but actual cancellation depends on thread state If thread has cancellation disabled, cancellation remains pending until thread enables it The default type is deferred Cancellation only occurs when the thread reaches a cancellation point i.e. the thread might call pthread_testcancel()to indicate a cancellation point If the thread has been cancelled, then a cleanup handler is invoked On Linux systems, thread cancellation is handled through signals. Operating System Concepts – 9th Edition 4.39 Silberschatz, Galvin and Gagne ©2013 Thread-Local Storage Thread-local storage (TLS) allows each thread to have its own copy of data Useful when you do not have control over the thread creation process (i.e., when using a thread pool) Different from local variables Local variables visible only during single function invocation TLS visible across function invocations within the thread Similar to static data TLS is unique to each thread Operating System Concepts – 9th Edition 4.40 Silberschatz, Galvin and Gagne ©2013 Scheduler Activations Both M:M and Two-level models require communication to maintain the appropriate number of kernel threads allocated to the application Many systems use an intermediate data structure between user and kernel threads – lightweight process (LWP) Appears to be a virtual processor on which process can schedule the user thread to run Each LWP is attached to a 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 – 9th Edition 4.41 Silberschatz, Galvin and Gagne ©2013 Operating System Examples Windows Threads Linux Threads Operating System Concepts – 9th Edition 4.42 Silberschatz, Galvin and Gagne ©2013 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 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 – 9th Edition 4.43 Silberschatz, Galvin and Gagne ©2013 Windows Threads (Cont.) The primary data structures of a thread include: ETHREAD (executive thread block) – includes pointer to process to which thread belongs and to KTHREAD, in kernel space KTHREAD (kernel thread block) – scheduling and synchronization info, kernel-mode stack, pointer to TEB, in kernel space TEB (thread environment block) – thread id, user-mode stack, thread-local storage, in user space Operating System Concepts – 9th Edition 4.44 Silberschatz, Galvin and Gagne ©2013 Windows Threads Data Structures Operating System Concepts – 9th Edition 4.45 Silberschatz, Galvin and Gagne ©2013 Linux Threads Linux refers to threads as tasks 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 struct task_struct points to process data structures (shared or unique) Operating System Concepts – 9th Edition 4.46 Silberschatz, Galvin and Gagne ©2013 End of Chapter 4 Operating System Concepts – 9th Edition Silberschatz, Galvin and Gagne ©2013 Homework Chapter 4, page 191 1, 3, 4, 6, 7, 8, 11, 13, 15, 17, 18, 21, 26 Operating System Concepts – 9th Edition 4.48 Silberschatz, Galvin and Gagne ©2013