Chapter 4: Threads

1. Chapter 4: Threads

2. Chapter 4: Threads • Overview • Multithreading Models • Threading Issues • Pthreads • Windows XP Threads • Linux Threads • Java Threads

3. Threads • A thread comprises a thread ID, a program counter, a register set, and a stack. • It shares with other threads belonging to same process its code section, data section and other OS resources (open files,...) • A web browser “process” might have one thread display images or text while another thread retrieves data from the network • A single application may be required to perform several similar tasks (e.g. a web server) • Server may create several processes. Process creation is time consuming. So multiple threads are used. • Typically RPC servers are multithreaded. RMI work similarly. • Many OS kernels are now multithreaded, each thread performs a specific task, such as interrupt handling.

4. Single and Multithreaded Processes

5. Benefits • Responsiveness • Resource Sharing • Economy • Utilization of multiprocessorarchitectures

6. User Threads • Thread management done by user-level threads library • Three primary thread libraries: • POSIX Pthreads • Win32 threads • Java threads

7. Kernel Threads • Supported by the Kernel • Examples • Windows XP/2000 • Solaris • Linux • Tru64 UNIX • Mac OS X

8. Multithreading Models • Many-to-One • One-to-One • Many-to-Many

9. Many-to-One • Many user-level threads mapped to single kernel thread • Thread management is done by the thread library in user space • Efficient, but the entire process will block if a thread makes a blocking system call • True concurrency is not gained because the kernel can schedule only one thread at a time • Because only one thread can access the kernel at a time, multiple threads are unable to run in parallel on multiprocessors • Examples: • Solaris Green Threads • GNU Portable Threads

10. Many-to-One Model

11. One-to-One • Each user-level thread maps to kernel thread • More concurrency than the many-to-one model by allowing another thread to run when a thread makes a blocking system call • Allows multiple threads to run in parallel on multiprocessors • Creating a user thread requires creating a kernel thread,...costly. • The developer has to be careful not to create too many threads • Examples • Windows NT/XP/2000 • Linux • Solaris 9 and later

12. One-to-one Model

13. 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 • As many user threads as necessary can be created and the corresponding kernel threads can run in parallel on a multiprocessor • When a thread performs a blocking system call, the kernel can schedule another thread for execution. • Solaris prior to version 9 • Windows NT/2000 with the ThreadFiber package

14. Many-to-Many Model

15. Two-level Model • Similar to M:M, still multiplexes many user-level threads to a smaller or equal number of kernel threads except that it allows a user thread to be bound to kernel thread • Examples • IRIX • HP-UX • Tru64 UNIX • Solaris 8 and earlier

16. Two-level Model

17. Thread Libraries • A thread library provides the programmer an API for creating and managing threads • Ways of implementing a thread library: • Provide a library entirely in user space with no kernel support • All code and data structures for the library exist in user space • Invoking a function in the library results in a local function call in user space and not a system call • Implement a kernel-level library supported directly by the OS • Code and data structures exist in the kernel space • Invoking a function in the API results in a system call

18. Thread Libraries • POSIX Pthreads library may be provided as either a user-or kernel-level library • The Win32 thread library is a kernel level library available on Windows • Java thread API allows thread creation and management directly in Java programs, but since JVM is running on top of a host OS, the Java thread API is implemented using a thread library on the host (e.g. Win32) • We will examine these three thread libraries. We design a multithreaded program that performs the summation of a non-negative integer in a separate thread using the summation function: sum =

19. Multithreaded C program using Pthreads API #include <pthread.h> #include <stdio.h> int sum; /* this data is shared by the thread(s) */ void *runner(void *param); /* the thread */ 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; }

20. Multithreaded C program using Pthreads API /* get the default attributes */ pthread_attr_init(&attr); /* create the thread */ pthread_create(&tid, &attr, runner, argv[1]); /* wait for the thread to exit */ pthread_join(tid, NULL); printf(“sum = %d\n”, sum); } /* 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); }

21. Multithreaded C program using the Win32 API #include <windows.h> #include <stdio.h> DWORD Sum; /* data is shared by the thread(s) */ /* the thread runs in this separate function */ DWORD WINAPI Summation(LPVOID Param) { DWORD Upper = *(DWORD*)Param; for (DWORD i = 0; i <= Upper; i++) Sum += i; return 0; } int main(int argc, char * argv[]) { DWORD ThreadId; HANDLE ThreadHandle; int Param; /* perform some basic error checking */ if (argc != 2) { fprintf(stderr, “An integer parameter is required\n”); return -1; } Param = atoi(argv[1];

22. Multithreaded C program using the Win32 API // create the thread ThreadHandle = CreateThread( NULL, // default security attributes 0, // default stack size Summation, // thread function &Param, // parameter to thread function 0, // default creation flags &ThreadId); // returns the thread identifier if (ThreadHandle != NULL) { // now wait for the thread to finish WaitForSingleObject(ThreadHandle, INFINITE); // close the thread handle CloseHandle(ThreadHandle); printf(“Sum = %d\n”, Sum); } }

23. Java program for the summation example class Sum { private int sum; public int getSum() { return sum; } public void setSum(int sum) { this.sum = sum; } } class Summation implements Runnable { private int upper; private Sum sumValue; public Summation(int upper, Sum sumValue) { this.upper = upper; this.sumValue = sumValue; } public void run() { int sum = 0; for (int i = 0; i <= upper; i++) sum += i; sumValue.setSum(sum); } }

24. Java program for the summation example Public class Driver { public static void main(String[] args) { if (arg.length > 0) { if (Integer.parseInt(args[0]) < 0) System.err.println(args[0] + “ must be >= 0.”); else { // create the object to be shared Sum sumObject = new Sum(); int upper = Integer.parseInt(args[0]); Thread thrd = new Thread(new Summation(upper, sumObject)); thrd.start(); try { thrd.join(); System.out.println (“The sum of “+upper+” is “+sumObject.getSum()); } catch (InterruptedException ie) { } } } else System.err.println(“Usage: Summation < integer value>”); } }

25. Java • There are two techniques for creating threads in a Java program • Create a new class that is derived from the Thread class and to override its run() method. • Define a class that implements the Runnable interface. public interface Runnable { public abstract void run(); } The code implementing the run() method is what runs as a thread • The specification for the JVM does not indicate how Java threads are to be mapped to the underlying OS. • Windows XP uses the one-to-one model. • There may be a relationship between the Java thread library and the thread library on the host OS. • For windows Win32 API can be used when creating Java threads. • Linux and Solaris systems might use Pthreads API.

26. Sharing of Data • Occurs easily in Win32 and Pthreads, as shared data are simply declared globally. • As a pure object-oriented language, Java has no such notion of global data; if two or more threads are to share data in a Java program, the sharing occurs by passing reference to the shared object to the appropriate threads. • In the example program, the main thread and the summation thread share the object instance of the Sum class which is referenced through the appropriate getSum() and setSum() methods.

27. Threading Issues • Semantics of fork() and exec() system calls • Thread cancellation • Signal handling • Thread pools • Thread specific data • Scheduler activations

28. Semantics of fork() and exec() • Does fork() duplicate only the calling thread or all threads? • Some UNIX systems have chosen to have two versions • If a thread invokes the exec() system call, the program specified in the parameter to exec() will replace the entire process—including all threads • Which of the two versions of fork() to use depends on the application • If exec() is called immediately after forking, then duplicating all threads is unnecessary, as the program specified in the parameters to exec() will replace the process. Duplicating only the calling thread is appropriate. • If the separate process does not call exec() after forking, the separate process should duplicate all threads.

29. Thread Cancellation • Terminating a thread before it has finished • E.g. When a user presses the stop button on a web browser, all threads loading the page are cancelled. • Two general approaches: • Asynchronous cancellation terminates the target thread immediately. • Troublesome. The OS will reclaim system resources from a canceled thread but will not reclaim all resources. So, canceling may not free a system-wide resource • Deferred cancellation allows the target thread to periodically check if it should be cancelled • Allows a thread to check whether it should be canceled at a point when it can be canceled safely (“cancellation points” in Pthreads).

30. Signal Handling • Signals are used in UNIX systems to notify a process that a particular event has occurred. May be received synchronously or asynchronously. • A signal handler is used to process signals • Signal is generated by particular event • Signal is delivered to a process • Signal is handled • Options in multithreaded programs: • 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

31. Signal Handling • Synchronous signals are delivered to the same process that performed the operation that caused the signal. Examples of synchronous signals include illegal memory access, division by 0. • When a signal is generated by an event external to a running process, that process receives the signal asynchronously (e.g. <control><C>). • Every signal may be handled by one of two possible handlers: • A default signal handler • A user-defined signal handler • When signal handling, some signals may simply be ignored, others may be handled by terminating the program. • The standard UNIX function for delivering a signal is: • kill(aid_t aid, int signal) • Windows does not explicitly provide support for signals. They can be emulated using asynchronous procedure calls (APCs) which allow a user thread to specify a function that is to be called when the user thread receives notification of a particular event.

32. Thread Pools • A multithreaded server has potential problems • The amount of time required to create the thread (together with the fact that this thread will be discarded once finished) • If we allow all concurrent requests to be serviced in a new thread, we have not placed a bound on the number of threads which may exhaust system resources • Create a number of threads in a pool where they await work • Threads from the pool are awakened and when finished returned to pool. • 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 • The number of threads in the pool • can be set heuristically based on factors such as the amount of memory • can be dynamically adjusted according to usage patterns • Consuming less memory with a small pool for low loads

33. Win32 Thread Pools DWORD WINAPI PoolFunction(AVOID Param) { /* This function runs as a separate thread */ } • A pointer to PoolFunction() is passed to one of the functions in the thread pool API, and a thread from the pool executes this function. One such member in the thread pool API is the QueueUserWorkItem which has three parameters LPTHREAD_START_ROUTINE Function – a pointer to the function that is to run as a separate thread PVOID Param – the parameter passed to Function ULONG Flags – flags indicating how the thread pool is to create and manage execution of the thread. An example call QueueUserWorkItem(&PoolFunction, NULL, 0); Which causes a thread from the thread pool to invoke PoolFunction() on behalf of the programmer.

34. Thread Specific Data • Threads belonging to a process share the data of the process • But thread-specific data 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)

35. Scheduler Activations • Communication between the kernel and the thread library • Both M:M and Two-level models require communication to maintain the appropriate number of kernel threads allocated to the application. They place an intermediate data structure between the user and kernel threads known as lightweight process (LWP) which appears to the user-thread library to be a virtual processor on which the application can schedule a user thread to run. Each LWP is attached to a kernel thread. Typically, an LWP is required for each concurrent blocking system call for I/O intensive applications • The kernel provides an application with a set of virtual processors (LWPs), and the application can schedule user threads onto an available virtual processor • Scheduler activations provide upcalls - a communication mechanism from the kernel to the thread library which handles them with upcall handlers. • This communication allows an application to maintain the correct number kernel threads

36. Scheduler Activations • One event that triggers an upcall occurs when an application thread is about to block. • Kernel makes an upcall to the application informing it that a thread is about to block. • The kernel then allocates a new LWP to the application. The application runs an upcall handler on this new virtual processor which relinquishes the LWP on which the blocking thread is running. • The upcall handler then schedules another thread that is eligible to run on the new LWP. • When the event that the blocking thread was waiting occurs, the kernel makes another upcall to the thread library informing it that the previously blocked thread is now eligible to run. The upcall handler for this event also requires an LWP.

37. Pthreads • A POSIX standard (IEEE 1003.1c) API for thread creation and synchronization • 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)

38. Windows XP Threads • Win32 API • Implements the one-to-one mapping • Each thread contains • A thread id • Register set • Separate user and kernel stacks • Private data storage area for run-time libraries and DLLs. • The register set, stacks, and private storage area are known as the context of the threads • The primary data structures of a thread include: • ETHREAD (executive thread block) • Contains thread start adress, pointer to parent process, pointer to KTHREAD • KTHREAD (kernel thread block) • Contains scheduling and synchronization info, kernel stack, pointer to TEB • TEB (thread environment block) • Contains thread identifier, user stack, thread-local storage (thread specific data)

39. 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) • File-system info may be shared • The same memory space may be shared • Signal handlers may be shared • The set of open files may be shared • Rather then copying all data structures, the new task points to the data structures of the parent task • A unique kernel data structure (struct task_struct) exist for each task in the system. It contains pointers to other data structures where these data are stored • When fork() is invoked, a new task is created, along with a copy of all the associated data structures of the parent process

40. Java Threads • Java threads are managed by the JVM • Java threads may be created by: • Extending Thread class • Implementing the Runnable interface

41. Java Thread States

42. End of Chapter 4