互斥和协助举行ca88yzc

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找了一些资料,摘录部分内容如下:

2017/7/28 14:14:43

POSIX Threads Programming

  1. mutual exclusion

  2. semaphore

  3. mutex

  4. mutex vs binary semaphore

  5. synchronization

  6. condition variable

  7. condition variable vs semaphore


Blaise Barney, Lawrence Livermore National Laboratory

 

Synchronizing QThread

While the purpose of threads is to allow code to run in parallel, there
are times where threads must stop and wait for other threads. For
example, if two threads try to write to the same variable
simultaneously, the result is undefined. The principle of forcing
threads to wait for one another is called mutual exclusion. It is a
common technique for protecting shared resources such as data. Qt
provides low-level primitives as well as high-level mechanisms for
synchronizing threads.

  • QMutex
    • QMutex
    • QMutexLocker
  • QWaitCondition
  • QSemaphore
  • References

译文点此

mutual exclusion

QMutex

The purpose of a QMutex is to protect an object, data structure or
section of code so that only one thread can access it at a time (this is
similar to the Java synchronized keyword).

Table of Contents

  1. Abstract
  2. Pthreads
    Overview

    1. What is a
      Thread?
    2. What are
      Pthreads?
    3. Why
      Pthreads?
    4. Designing Threaded
      Programs
  3. The Pthreads
    API
  4. Compiling Threaded
    Programs
  5. Thread
    Management

    1. Creating and Terminating
      Threads
    2. Passing Arguments to
      Threads
    3. Joining and Detaching
      Threads
    4. Stack
      Management
    5. Miscellaneous
      Routines
  6. Mutex
    Variables

    1. Mutex Variables
      Overview
    2. Creating and Destroying
      Mutexes
    3. Locking and Unlocking
      Mutexes
  7. Condition
    Variables

    1. Condition Variables
      Overview
    2. Creating and Destroying Condition
      Variables
    3. Waiting and Signaling on Condition
      Variables
  8. Topics Not
    Covered
  9. Pthread Library Routines
    Reference
  10. References and More
    Information
Abstract

In shared memory multiprocessor architectures, such as SMPs, threads can
be used to implement parallelism. Historically, hardware vendors have
implemented their own proprietary versions of threads, making
portability a concern for software developers. For UNIX systems, a
standardized C language threads programming interface has been specified
by the IEEE POSIX 1003.1c standard. Implementations that adhere to this
standard are referred to as POSIX threads, or Pthreads.

The tutorial begins with an introduction to concepts, motivations, and
design considerations for using Pthreads. Each of the three major
classes of routines in the Pthreads API are then covered: Thread
Management, Mutex Variables, and Condition Variables. Example codes are
used throughout to demonstrate how to use most of the Pthreads routines
needed by a new Pthreads programmer. The tutorial concludes with a
discussion of LLNL specifics and how to mix MPI with pthreads. A lab
exercise, with numerous example codes (C Language) is also included.

Level/Prerequisites: Ideal for those who are new to parallel programming
with threads. A basic understanding of parallel programming in C is
assumed. For those who are unfamiliar with Parallel Programming in
general, the material covered in EC3500:
Introduction To Parallel
Computing
would be helpful.

Pthreads Overview

「it is the requirement that one thread of execution never enter its
critical section at the same time that another concurrent thread of
execution enters its own critical section.」@2

「The requirement of mutual exclusion was first identified and solved
by Edsger W. Dijkstra in his seminal 1965 paper titled Solution of a
problem in concurrent programming control.」@2

「Dijkstra’s famous “Cooperating Sequential Processes (EWD123) was
written in 1965, presented at a 1966 NATO Summer School, and published
in a 1968 book Programming Languages, edited by F. Genuys. See class=”invisible”>http://www. class=”visible”>cs.utexas.edu/users/EWD class=”invisible”>/ewd01xx/EWD123.PDF
.」@5

「Back in 1965, Edsger Dijkstra … introduced the concept of a binary
semaphore into modern programming to address possible race conditions
in concurrent programs. His very simple idea was to use a pair of
function calls to the operating system to indicate entering and
leaving a critical region.」@1

QMutex

QMutex is the basic method to protect the data access.

QMutex mutex;
class WorkerThread_1 : public QThread {
protected:
    void run() {
        mutex.lock();
        for ( int i = 0; i < 100000; ++i ) {
            value++;
        }
        qDebug() << "Thread 1:" << value;
        mutex.unlock();
    }
};

class WorkerThread_2 : public QThread {
protected:
    void run() {
        mutex.lock();
        for ( int i = 0; i < 200000; ++i ) {
            value++;
        }
        qDebug() << "Thread 2:" << value;
        mutex.unlock();
    }
};

What is a Thread?

  • Technically, a thread is defined as an independent stream of
    instructions that can be scheduled to run as such by the operating
    system. But what does this mean?
  • To the software developer, the concept of a “procedure” that runs
    independently from its main program may best describe a thread.
  • To go one step further, imagine a main program (a.out) that contains
    a number of procedures. Then imagine all of these procedures being
    able to be scheduled to run simultaneously and/or independently by
    the operating system. That would describe a “multi-threaded”
    program.
  • How is this accomplished?

  • Before understanding a thread, one first needs to understand a UNIX
    process. A process is created by the operating system, and requires
    a fair amount of “overhead”. Processes contain information about
    program resources and program execution state, including:

    • Process ID, process group ID, user ID, and group ID
    • Environment
    • Working directory.
    • Program instructions
    • Registers
    • Stack
    • Heap
    • File descriptors
    • Signal actions
    • Shared libraries
    • Inter-process communication tools (such as message queues,
      pipes, semaphores, or shared memory).
    UNIX PROCESS THREADS WITHIN A UNIX PROCESS
  • Threads use and exist within these process resources, yet are able
    to be scheduled by the operating system and run as independent
    entities largely because they duplicate only the bare essential
    resources that enable them to exist as executable code.

  • This independent flow of control is accomplished because a thread
    maintains its own:

    • Stack pointer
    • Registers
    • Scheduling properties (such as policy or priority)
    • Set of pending and blocked signals
    • Thread specific data.
  • So, in summary, in the UNIX environment a thread:
    • Exists within a process and uses the process resources
    • Has its own independent flow of control as long as its parent
      process exists and the OS supports it
    • Duplicates only the essential resources it needs to be
      independently schedulable
    • May share the process resources with other threads that act
      equally independently (and dependently)
    • Dies if the parent process dies – or something similar
    • Is “lightweight” because most of the overhead has already been
      accomplished through the creation of its process.
  • Because threads within the same process share resources:
    • Changes made by one thread to shared system resources (such as
      closing a file) will be seen by all other threads.
    • Two pointers having the same value point to the same data.
    • Reading and writing to the same memory locations is possible,
      and therefore requires explicit synchronization by the
      programmer.
Pthreads Overview

Dijkstra最初提出的semaphore是用于实现互斥。

QMutexLocker

The QMutexLocker class is a convenience class that simplifies locking
and unlocking mutexes. Locking and unlocking a QMutex in complex
functions and statements or in exception handling code is error-prone
and difficult to debug. If locked, the mutex will be unlocked when the
QMutexLocker is destroyed. The above code can be written as:

class WorkerThread_1 : public QThread {
protected:
    void run() {
        QMutexLocker locker( &mutex );
        for ( int i = 0; i < 100000; ++i ) {
            value++;
        }
        qDebug() << "Thread 1:" << value;
    }
};

class WorkerThread_2 : public QThread {
protected:
    void run() {
        QMutexLocker locker( &mutex );
        for ( int i = 0; i < 200000; ++i ) {
            value++;
        }
        qDebug() << "Thread 2:" << value;
    }
};

What are Pthreads?

  • Historically, hardware vendors have implemented their own
    proprietary versions of threads. These implementations differed
    substantially from each other making it difficult for programmers to
    develop portable threaded applications.
  • In order to take full advantage of the capabilities provided by
    threads, a standardized programming interface was required. For UNIX
    systems, this interface has been specified by the IEEE POSIX 1003.1c
    standard (1995). Implementations which adhere to this standard are
    referred to as POSIX threads, or Pthreads. Most hardware vendors now
    offer Pthreads in addition to their proprietary API’s.
  • Pthreads are defined as a set of C language programming types and
    procedure calls, implemented with a pthread.h header/include file
    and a thread library – though this library may be part of another
    library, such as libc.
Pthreads Overview

semaphore

QWaitCondition

The QWaitCondition class provides a condition variable for
synchronizing threads. QWaitCondition allows a thread to tell other
threads that some sort of condition has been met. One or many threads
can block waiting for a QWaitCondition to set a condition with
wakeOne() or wakeAll(). Use wakeOne() to wake one randomly
selected condition or wakeAll() to wake them all.

Key functions:
The thread that is woken up depends on the operating system’
scheduling policies, and cannot be controlled or predicted.

  • wakeAll(): Wakes all threads waiting on the wait condition.
  • wakeOne(): Wakes one thread waiting on the wait condition.
  • wait(QMutex *lockedMutex, unsigned long time = ULONG_MAX). Flows:

mutex.lock(); // Lock a mutex first.
if ( numUsedBytes == 0 ) {
    // Releases the locked Mutex and waits on the wait condition.
    BufferNotEmpty.wait( &mutex );
}
// The locked Mutex will be returned to the same locked state.
mutex.unlock(); 

Producer-consumer example:

// global variable
const int DATASIZE = 100000;
const int BUFFERSIZE = 8192;

char buffer[BUFFERSIZE];

// Wait Condition
QWaitCondition BufferNotEmpty;
QWaitCondition BufferNotFull;

QMutex mutex;
int numUsedBytes = 0;

// producer
class Producer : public QThread {
protected:
    void run() {
        qsrand(QTime(0,0,0).secsTo(QTime::currentTime()));
        for ( int i = 0; i < DATASIZE; ++i ) {
            mutex.lock();
            if ( numUsedBytes == BUFFERSIZE ) {
                BufferNotFull.wait( &mutex );
            }
            mutex.unlock();

            buffer[i%BUFFERSIZE] = "abcd"[(int)qrand() % 4];

            mutex.lock();
            ++numUsedBytes;
            BufferNotEmpty.wakeAll();
            mutex.unlock();
        }
    }
};

class Consumer : public QThread {
protected:
    void run() {
       for ( int i = 0; i < DATASIZE; ++i ) {
           mutex.lock();
           if ( numUsedBytes == 0 ) {
               BufferNotEmpty.wait( &mutex );
           }
           mutex.unlock();

           qDebug() << buffer[i%BUFFERSIZE];

           mutex.lock();
           --numUsedBytes;
           BufferNotFull.wakeAll();
           mutex.unlock();
       }
    }
};

If numUsedBytes == BUFFERSIZE, producer thread will wait until
consumer eats some sources(BufferNotFull.wakeAll()). If
numUsedBytes == 0, the consumer need to wait until producer produces
some sources(BufferNotEmpty.wakeAll()).

Why Pthreads?

  • The primary motivation for using Pthreads is to realize potential
    program performance gains.
  • When compared to the cost of creating and managing a process, a
    thread can be created with much less operating system overhead.
    Managing threads requires fewer system resources than managing
    processes.

    For example, the following table compares timing results for the
    fork() subroutine and the pthreads_create() subroutine. Timings
    reflect 50,000 process/thread creations, were performed with the
    time utility, and units are in seconds, no optimization flags.

    Note: don’t expect the sytem and user times to add up to real time,
    because these are SMP systems with multiple CPUs working on the
    problem at the same time. At best, these are approximations.

    Platform

  • All threads within a process share the same address space.
    Inter-thread communication is more efficient and in many cases,
    easier to use than inter-process communication.

  • Threaded applications offer potential performance gains and
    practical advantages over non-threaded applications in several other
    ways:

    • Overlapping CPU work with I/O: For example, a program may have
      sections where it is performing a long I/O operation. While one
      thread is waiting for an I/O system call to complete, CPU
      intensive work can be performed by other threads.
    • Priority/real-time scheduling: tasks which are more important
      can be scheduled to supersede or interrupt lower priority tasks.
    • Asynchronous event handling: tasks which service events of
      indeterminate frequency and duration can be interleaved. For
      example, a web server can both transfer data from previous
      requests and manage the arrival of new requests.
  • The primary motivation for considering the use of Pthreads on an SMP
    architecture is to achieve optimum performance. In particular, if an
    application is using MPI for on-node communications, there is a
    potential that performance could be greatly improved by using
    Pthreads for on-node data transfer instead.
  • For example:
    • MPI libraries usually implement on-node task communication via
      shared memory, which involves at least one memory copy operation
      (process to process).
    • For Pthreads there is no intermediate memory copy required
      because threads share the same address space within a single
      process. There is no data transfer, per se. It becomes more of a
      cache-to-CPU or memory-to-CPU bandwidth (worst case) situation.
      These speeds are much higher.
    • Some local comparisons are shown below:
      Platform MPI Shared Memory Bandwidth
      (GB/sec)
      Pthreads Worst Case
      Memory-to-CPU Bandwidth
      (GB/sec)
      AMD 2.4 GHz Opteron 1.2 5.3
      IBM 1.9 GHz POWER5 p5-575 4.1 16
      IBM 1.5 GHz POWER4 2.1 4
      Intel 1.4 GHz Xeon 0.3 4.3
      Intel 1.4 GHz Itanium 2 1.8 6.4
Pthreads Overview

「A variant of Dijkstra’s semaphore was put forward by another
Dutchman, Dr. Carel S. Scholten. In his proposal the semaphore can
have an initial value (or count) greater than one. This enables
building programs where more than one resource is being managed in
a given critical region.」@1

「Scholten’s semaphore is referred to as the General or Counting
Semaphore
, Dijkstra’s being known as the Binary Semaphore.」@1

QSemaphore

A semaphore is a generalization of a mutex. While a mutex can only be
locked once, it’s possible to acquire a semaphore multiple times.
Semaphores are typically used to protect a certain number of identical
resources.

Key functions:

  • QSemaphore::QSemaphore(int n = 0): Creates a new semaphore and
    initializes the number of resources it guards to n (by default, 0).
  • acquire(n): Tries to acquire n resources guarded by the semaphore.
    If n > available(), this call will block until enough resources
    are available.
  • release(n): Returns the number of resources currently available to
    the semaphore. This number can never be negative.

Same as QWaitCondition example, we rewrite producer-consumer example
as follows:

// global variable
const int DATASIZE = 100000;
const int BUFFERSIZE = 8192;
char buffer[BUFFERSIZE];

QSemaphore freeSema(BUFFERSIZE);
QSemaphore usedSema;

class Producer : public QThread {
protected:
    virtual void run() {
        qsrand(QTime(0,0,0).secsTo(QTime::currentTime()));

        for ( int i = 0; i < DATASIZE; ++i ) {
            freeSema.acquire();
            buffer[i%BUFFERSIZE] = "ABCD"[(int)qrand()%4];
            usedSema.release();
        }
    }
};

class Consumer : public QThread {
protected:
    virtual void run() {
        for ( int i = 0; i < DATASIZE; ++i ) {
            usedSema.acquire();
            qDebug() << buffer[i%BUFFERSIZE];
            freeSema.release();
        }
    }
};

Designing Threaded Programs

ca88yzc 1 Parallel Programming:

  • On modern, multi-cpu machines, pthreads are ideally suited for
    parallel programming, and whatever applies to parallel programming
    in general, applies to parallel pthreads programs.
  • There are many considerations for designing parallel programs, such
    as:

    • What type of parallel programming model to use?
    • Problem partitioning
    • Load balancing
    • Communications
    • Data dependencies
    • Synchronization and race conditions
    • Memory issues
    • I/O issues
    • Program complexity
    • Programmer effort/costs/time
  • Covering these topics is beyond the scope of this tutorial, however
    interested readers can obtain a quick overview in the Introduction to Parallel
    Computing
    tutorial.
  • In general though, in order for a program to take advantage of
    Pthreads, it must be able to be organized into discrete, independent
    tasks which can execute concurrently. For example, if routine1 and
    routine2 can be interchanged, interleaved and/or overlapped in real
    time, they are candidates for threading.
    ca88yzc 2
  • Programs having the following characteristics may be well suited for
    pthreads:

    • Work that can be executed, or data that can be operated on, by
      multiple tasks simultaneously
    • Block for potentially long I/O waits
    • Use many CPU cycles in some places but not others
    • Must respond to asynchronous events
    • Some work is more important than other work (priority
      interrupts)
  • Pthreads can also be used for serial applications, to emulate
    parallel execution. A perfect example is the typical web browser,
    which for most people, runs on a single cpu desktop/laptop machine.
    Many things can “appear” to be happening at the same time.
  • Several common models for threaded programs exist:
    • Manager/worker: a single thread, the manager assigns
      work to other threads, the workers. Typically, the manager
      handles all input and parcels out work to the other tasks. At
      least two forms of the manager/worker model are common: static
      worker pool and dynamic worker pool.
    • Pipeline: a task is broken into a series of suboperations,
      each of which is handled in series, but concurrently, by a
      different thread. An automobile assembly line best describes
      this model.
    • Peer: similar to the manager/worker model, but after the
      main thread creates other threads, it participates in the work.

ca88yzc 3 Shared Memory Model:

  • All threads have access to the same global, shared memory
  • Threads also have their own private data
  • Programmers are responsible for synchronizing access (protecting)
    globally shared data. ca88yzc 4

ca88yzc 5 Thread-safeness:

  • Thread-safeness: in a nutshell, refers an application’s ability to
    execute multiple threads simultaneously without “clobbering” shared
    data or creating “race” conditions.
  • For example, suppose that your application creates several threads,
    each of which makes a call to the same library routine:

    • This library routine accesses/modifies a global structure or
      location in memory.
    • As each thread calls this routine it is possible that they may
      try to modify this global structure/memory location at the same
      time.
    • If the routine does not employ some sort of synchronization
      constructs to prevent data corruption, then it is not
      thread-safe.

ca88yzc 6

  • The implication to users of external library routines is that if you
    aren’t 100% certain the routine is thread-safe, then you take your
    chances with problems that could arise.
  • Recommendation: Be careful if your application uses libraries or
    other objects that don’t explicitly guarantee thread-safeness. When
    in doubt, assume that they are not thread-safe until proven
    otherwise. This can be done by “serializing” the calls to the
    uncertain routine, etc.
The Pthreads API
  • The Pthreads API is defined in the ANSI/IEEE POSIX 1003.1 – 1995
    standard. Unlike MPI, this standard is not freely available on the
    Web – it must be purchased from IEEE.
  • The subroutines which comprise the Pthreads API can be informally
    grouped into three major classes:

    1. Thread management: The first class of functions work
      directly on threads – creating, detaching, joining, etc. They
      include functions to set/query thread attributes (joinable,
      scheduling etc.)
    2. Mutexes: The second class of functions deal with
      synchronization, called a “mutex”, which is an abbreviation for
      “mutual exclusion”. Mutex functions provide for creating,
      destroying, locking and unlocking mutexes. They are also
      supplemented by mutex attribute functions that set or modify
      attributes associated with mutexes.
    3. Condition variables: The third class of functions address
      communications between threads that share a mutex. They are
      based upon programmer specified conditions. This class includes
      functions to create, destroy, wait and signal based upon
      specified variable values. Functions to set/query condition
      variable attributes are also included.
  • Naming conventions: All identifiers in the threads library begin
    with pthread_

    Routine Prefix Functional Group
    pthread_ Threads themselves and miscellaneous subroutines
    pthread_attr_ Thread attributes objects
    pthread_mutex_ Mutexes
    pthread_mutexattr_ Mutex attributes objects.
    pthread_cond_ Condition variables
    pthread_condattr_ Condition attributes objects
    pthread_key_ Thread-specific data keys
  • The concept of opaque objects pervades the design of the API. The
    basic calls work to create or modify opaque objects – the opaque
    objects can be modified by calls to attribute functions, which deal
    with opaque attributes.

  • The Pthreads API contains over 60 subroutines. This tutorial will
    focus on a subset of these – specifically, those which are most
    likely to be immediately useful to the beginning Pthreads
    programmer.
  • For portability, the pthread.h header file should be included in
    each source file using the Pthreads library.
  • The current POSIX standard is defined only for the C language.
    Fortran programmers can use wrappers around C function calls. Some
    Fortran compilers (like IBM AIX Fortran) may provide a Fortram
    pthreads API.
  • A number of excellent books about Pthreads are available. Several of
    these are listed in the
    Referencessection
    of this tutorial.
Compiling Threaded Programs
  • Several examples of compile commands used for pthreads codes are
    listed in the table below.
    Compiler / Platform
Thread Management

最初提出的Counting
Semaphore用于临界区中有多份资源的情况。至于进入临界区后如何确定哪份资源可用,不是由Counting
Semaphore负责的,参考@5 bathroom的例子和@6 Adam Davis进一步的讨论「A
semaphore is the wrong tool to protect several of the essentially same
resource, but this is how many people think of it and use it. The
bouncer analogy is distinctly different – there aren’t several of the
same type of resource, instead there is one resource which can accept
multiple simultaneous users.」

References

  • Synchronizing
    Threads
  • QMutex
    Class
  • QMutexLocker
    Class
  • QWaitCondition
    Class
  • QWaitCondition
    Example
  • QSemaphore
    Class
  • Semaphores
    Example

Creating and Terminating Threads

ca88yzc 7 Routines:

ca88yzc 8 Creating Threads:

  • Initially, your main() program comprises a single, default thread.
    All other threads must be explicitly created by the programmer.
  • pthread_create creates a new thread and makes it executable. This
    routine can be called any number of times from anywhere within your
    code.
  • pthread_create arguments:
    • thread: An opaque, unique identifier for the new thread
      returned by the subroutine.
    • attr: An opaque attribute object that may be used to set
      thread attributes. You can specify a thread attributes object,
      or NULL for the default values.
    • start_routine: the C routine that the thread will execute once
      it is created.
    • arg: A single argument that may be passed to start_routine.
      It must be passed by reference as a pointer cast of type void.
      NULL may be used if no argument is to be passed.
  • The maximum number of threads that may be created by a process is
    implementation dependent.
  • Once created, threads are peers, and may create other threads. There
    is no implied hierarchy or dependency between threads.

    ca88yzc 9

  Question: After a thread has been created, how do you know when it will be scheduled to run by the operating system?

ca88yzc 10 Thread Attributes:

  • By default, a thread is created with certain attributes. Some of
    these attributes can be changed by the programmer via the thread
    attribute object.
  • pthread_attr_init and pthread_attr_destroy are used to
    initialize/destroy the thread attribute object.
  • Other routines are then used to query/set specific attributes in the
    thread attribute object.
  • Some of these attributes will be discussed later.

ca88yzc 11 Terminating Threads:

  • There are several ways in which a Pthread may be terminated:
    • The thread returns from its starting routine (the main routine
      for the initial thread).
    • The thread makes a call to the pthread_exit subroutine
      (covered below).
    • The thread is canceled by another thread via the
      pthread_cancel routine (not covered here).
    • The entire process is terminated due to a call to either the
      exec or exit subroutines.
  • pthread_exit is used to explicitly exit a thread. Typically, the
    pthread_exit() routine is called after a thread has completed its
    work and is no longer required to exist.
  • If main() finishes before the threads it has created, and exits
    with pthread_exit(), the other threads will continue to execute.
    Otherwise, they will be automatically terminated when main()
    finishes.
  • The programmer may optionally specify a termination status, which
    is stored as a void pointer for any thread that may join the calling
    thread.
  • Cleanup: the pthread_exit() routine does not close files; any
    files opened inside the thread will remain open after the thread is
    terminated.
  • Discussion: In subroutines that execute to completion normally, you
    can often dispense with calling pthread_exit() – unless, of
    course, you want to pass a return code back. However, in main(),
    there is a definite problem if main() completes before the threads
    it spawned. If you don’t call pthread_exit() explicitly, when
    main() completes, the process (and all threads) will be terminated.
    By calling pthread_exit() in main(), the process and all of its
    threads will be kept alive even though all of the code in main() has
    been executed.

「Counting semaphores are not used to enforce mutual exclusion because
they enable multiple threads of execution in the critical region at
once
. Instead, they are used to enforce limits in certain code.They
are not used much in the kernel.」@lkd chap.10

「”A semaphore restricts the number of simultaneous users of a
shared resource up to a maximum number.
Threads can request access
to the resource (decrementing the semaphore), and can signal that they
have finished using the resource (incrementing the semaphore).” Ref:
Symbian Developer Library」@http:// class=”visible”>niclasw.mbnet.fi/MutexS class=”invisible”>emaphore.html

Example: Pthread Creation and Termination

  • This simple example code creates 5 threads with the
    pthread_create() routine. Each thread prints a “Hello World!”
    message, and then terminates with a call to pthread_exit().

    Example Code – Pthread Creation and Termination

    #include <pthread.h>
    #include <stdio.h>
    #define NUM_THREADS 5
    
    void *PrintHello(void *threadid)
    {
     long tid;
     tid = (long)threadid;
     printf("Hello World! It's me, thread #%ld!\n", tid);
     pthread_exit(NULL);
    }
    
    int main (int argc, char *argv[])
    {
     pthread_t threads[NUM_THREADS];
     int rc;
     long t;
     for(t=0; t<NUM_THREADS; t++){
     printf("In main: creating thread %ld\n", t);
     rc = pthread_create(&threads[t], NULL, PrintHello, (void *)t);
     if (rc){
     printf("ERROR; return code from pthread_create() is %d\n", rc);
     exit(-1);
     }
     }
     pthread_exit(NULL);
    }
    

Thread Management

这两个使用情景中限制的是并发进入临界区的线程数量,临界资源只有一份。而最初提出的使用情景是临界区中有多份相同的临界资源。

Passing Arguments to Threads

  • The pthread_create() routine permits the programmer to pass one
    argument to the thread start routine. For cases where multiple
    arguments must be passed, this limitation is easily overcome by
    creating a structure which contains all of the arguments, and then
    passing a pointer to that structure in the pthread_create()
    routine.
  • All arguments must be passed by reference and cast to (void *).
  Question: How can you safely pass data to newly created threads, given their non-deterministic start-up and scheduling?
Example 1 – Thread Argument Passing


long *taskids[NUM_THREADS];

for(t=0; t<NUM_THREADS; t++)
{
 taskids[t] = (long *) malloc(sizeof(long));
 *taskids[t] = t;
 printf("Creating thread %ld\n", t);
 rc = pthread_create(&threads[t], NULL, PrintHello, (void *) taskids[t]);
 ...
}

Example 2 – Thread Argument Passing


struct thread_data{
 int thread_id;
 int sum;
 char *message;
};

struct thread_data thread_data_array[NUM_THREADS];

void *PrintHello(void *threadarg)
{
 struct thread_data *my_data;
 ...
 my_data = (struct thread_data *) threadarg;
 taskid = my_data->thread_id;
 sum = my_data->sum;
 hello_msg = my_data->message;
 ...
}

int main (int argc, char *argv[])
{
 ...
 thread_data_array[t].thread_id = t;
 thread_data_array[t].sum = sum;
 thread_data_array[t].message = messages[t];
 rc = pthread_create(&threads[t], NULL, PrintHello, 
 (void *) &thread_data_array[t]);
 ...
}

Example 3 – Thread Argument Passing (Incorrect)


int rc;
long t;

for(t=0; t<NUM_THREADS; t++) 
{
 printf("Creating thread %ld\n", t);
 rc = pthread_create(&threads[t], NULL, PrintHello, (void *) &t);
 ...
}

Thread Management

小结:

Joining and Detaching Threads

ca88yzc 12 Routines:

ca88yzc 13 Joining:

  • “Joining” is one way to accomplish synchronization between threads.
    For example:

    ca88yzc 14

  • The pthread_join() subroutine blocks the calling thread until the
    specified threadid thread terminates.

  • The programmer is able to obtain the target thread’s termination
    return status if it was specified in the target thread’s call to
    pthread_exit().
  • A joining thread can match one pthread_join() call. It is a
    logical error to attempt multiple joins on the same thread.
  • Two other synchronization methods, mutexes and condition variables,
    will be discussed later.

ca88yzc 15 Joinable or Not?

  • When a thread is created, one of its attributes defines whether it
    is joinable or detached. Only threads that are created as joinable
    can be joined. If a thread is created as detached, it can never be
    joined.
  • The final draft of the POSIX standard specifies that threads should
    be created as joinable. However, not all implementations may follow
    this.
  • To explicitly create a thread as joinable or detached, the attr
    argument in the pthread_create() routine is used. The typical 4
    step process is:

    1. Declare a pthread attribute variable of the pthread_attr_t
      data type
    2. Initialize the attribute variable with pthread_attr_init()
    3. Set the attribute detached status with
      pthread_attr_setdetachstate()
    4. When done, free library resources used by the attribute with
      pthread_attr_destroy()

ca88yzc 16 Detaching:

  • The pthread_detach() routine can be used to explicitly detach a
    thread even though it was created as joinable.
  • There is no converse routine.

ca88yzc 17 Recommendations:

  • If a thread requires joining, consider explicitly creating it as
    joinable. This provides portability as not all implementations may
    create threads as joinable by default.
  • If you know in advance that a thread will never need to join with
    another thread, consider creating it in a detached state. Some
    system resources may be able to be freed.

「user cases: (1) mutual exclusive like( mutex), (2) counting
semaphore to control access to a pool of a shared resources, (3)
scheduling constraint ( need wait(), and value can be negative, but
some implementations does not allow negative value). cause one thread
to wait for a specific action to be signaled from another thread (
execution order).」@http://www. class=”visible”>comrite.com/wp/mutex-se class=”invisible”>maphore-monitor-condition-variable/

Example: Pthread Joining

Example Code – Pthread Joining


#include <pthread.h>
#include <stdio.h>
#include <stdlib.h>
#define NUM_THREADS 4

void *BusyWork(void *t)
{
 int i;
 long tid;
 double result=0.0;
 tid = (long)t;
 printf("Thread %ld starting...\n",tid);
 for (i=0; i<1000000; i++)
 {
 result = result + sin(i) * tan(i);
 }
 printf("Thread %ld done. Result = %e\n",tid, result);
 pthread_exit((void*) t);
}

int main (int argc, char *argv[])
{
 pthread_t thread[NUM_THREADS];
 pthread_attr_t attr;
 int rc;
 long t;
 void *status;

 /* Initialize and set thread detached attribute */
 pthread_attr_init(&attr);
 pthread_attr_setdetachstate(&attr, PTHREAD_CREATE_JOINABLE);

 for(t=0; t<NUM_THREADS; t++) {
 printf("Main: creating thread %ld\n", t);
 rc = pthread_create(&thread[t], &attr, BusyWork, (void *)t); 
 if (rc) {
 printf("ERROR; return code from pthread_create() 
 is %d\n", rc);
 exit(-1);
 }
 }

 /* Free attribute and wait for the other threads */
 pthread_attr_destroy(&attr);
 for(t=0; t<NUM_THREADS; t++) {
 rc = pthread_join(thread[t], &status);
 if (rc) {
 printf("ERROR; return code from pthread_join() 
 is %d\n", rc);
 exit(-1);
 }
 printf("Main: completed join with thread %ld having a status 
 of %ld\n",t,(long)status);
 }

printf("Main: program completed. Exiting.\n");
pthread_exit(NULL);
}

Thread Management

+(2.5)限制并发进入临界区的线程数量

Stack Management

ca88yzc 18 Routines:

ca88yzc 19 Preventing Stack Problems:

  • The POSIX standard does not dictate the size of a thread’s stack.
    This is implementation dependent and varies.
  • Exceeding the default stack limit is often very easy to do, with the
    usual results: program termination and/or corrupted data.
  • Safe and portable programs do not depend upon the default stack
    limit, but instead, explicitly allocate enough stack for each thread
    by using the pthread_attr_setstacksize routine.
  • The pthread_attr_getstackaddr and pthread_attr_setstackaddr
    routines can be used by applications in an environment where the
    stack for a thread must be placed in some particular region of
    memory.

ca88yzc 20 Some Practical Examples at LC:

  • Default thread stack size varies greatly. The maximum size that can
    be obtained also varies greatly, and may depend upon the number of
    threads per node.

    Node
    Architecture
    #CPUs Memory (GB) Default Size
    (bytes)
    AMD Opteron 8 16 2,097,152
    Intel IA64 4 8 33,554,432
    Intel IA32 2 4 2,097,152
    IBM Power5 8 32 196,608
    IBM Power4 8 16 196,608
    IBM Power3 16 16 98,304

(1)、(2)和(2.5)的线程模型是thread(){take(); …;
give()}[N];(3)的线程模型是thread_give()[M]+thread_take()[N],后者semaphore用于同步,而不是互斥。

Example: Stack Management

Example Code – Stack Management


#include <pthread.h>
#include <stdio.h>
#define NTHREADS 4
#define N 1000
#define MEGEXTRA 1000000

pthread_attr_t attr;

void *dowork(void *threadid)
{
 double A[N][N];
 int i,j;
 long tid;
 size_t mystacksize;

 tid = (long)threadid;
 pthread_attr_getstacksize (&attr, &mystacksize);
 printf("Thread %ld: stack size = %li bytes \n", tid, mystacksize);
 for (i=0; i<N; i++)
 for (j=0; j<N; j++)
 A[i][j] = ((i*j)/3.452) + (N-i);
 pthread_exit(NULL);
}

int main(int argc, char *argv[])
{
 pthread_t threads[NTHREADS];
 size_t stacksize;
 int rc;
 long t;

 pthread_attr_init(&attr);
 pthread_attr_getstacksize (&attr, &stacksize);
 printf("Default stack size = %li\n", stacksize);
 stacksize = sizeof(double)*N*N+MEGEXTRA;
 printf("Amount of stack needed per thread = %li\n",stacksize);
 pthread_attr_setstacksize (&attr, stacksize);
 printf("Creating threads with stack size = %li bytes\n",stacksize);
 for(t=0; t<NTHREADS; t++){
 rc = pthread_create(&threads[t], &attr, dowork, (void *)t);
 if (rc){
 printf("ERROR; return code from pthread_create() is %d\n", rc);
 exit(-1);
 }
 }
 printf("Created %ld threads.\n", t);
 pthread_exit(NULL);
}
Thread Management

mutex

Miscellaneous Routines

Mutex Variables

「To address the problems associated with semaphore, a new concept was
developed during the late 1980’s. I have struggled to find it’s first
clear definition, but the major use of the term mutex (another
neologism based around MUTual EXclusion) appears to have been driven
through the development of the common programming specification for
UNIX based systems. In 1990 this was formalised by the IEEE as
standard IEEE Std 1003.1 commonly known as POSIX.」@3

「POSIX.1 defines four types: PTHREAD_MUTEX_NORMAL,
PTHREAD_MUTEX_ERRORCHECK, PTHREAD_MUTEX_RECURSIVE,
PTHREAD_MUTEX_DEFAULT」@APUE section 12.4.1 @TLPI section 30.1.7

Overview

  • Mutex is an abbreviation for “mutual exclusion”. Mutex variables are
    one of the primary means of implementing thread synchronization and
    for protecting shared data when multiple writes occur.
  • A mutex variable acts like a “lock” protecting access to a shared
    data resource. The basic concept of a mutex as used in Pthreads is
    that only one thread can lock (or own) a mutex variable at any given
    time. Thus, even if several threads try to lock a mutex only one
    thread will be successful. No other thread can own that mutex until
    the owning thread unlocks that mutex. Threads must “take turns”
    accessing protected data.
  • Mutexes can be used to prevent “race” conditions. An example of a
    race condition involving a bank transaction is shown below:

    Thread 1 Thread 2 Balance
    Read balance: $1000   $1000
      Read balance: $1000 $1000
      Deposit $200 $1000
    Deposit $200   $1000
    Update balance $1000+$200   $1200
      Update balance $1000+$200 $1200
  • In the above example, a mutex should be used to lock the “Balance”
    while a thread is using this shared data resource.

  • Very often the action performed by a thread owning a mutex is the
    updating of global variables. This is a safe way to ensure that when
    several threads update the same variable, the final value is the
    same as what it would be if only one thread performed the update.
    The variables being updated belong to a “critical section”.
  • A typical sequence in the use of a mutex is as follows:
    • Create and initialize a mutex variable
    • Several threads attempt to lock the mutex
    • Only one succeeds and that thread owns the mutex
    • The owner thread performs some set of actions
    • The owner unlocks the mutex
    • Another thread acquires the mutex and repeats the process
    • Finally the mutex is destroyed
  • When several threads compete for a mutex, the losers block at that
    call – an unblocking call is available with “trylock” instead of the
    “lock” call.
  • When protecting shared data, it is the programmer’s responsibility
    to make sure every thread that needs to use a mutex does so. For
    example, if 4 threads are updating the same data, but only one uses
    a mutex, the data can still be corrupted.
Mutex Variables

mutex vs binary semaphore

Creating and Destroying Mutexes

ca88yzc 21 Routines:

ca88yzc 22 Usage:

  • Mutex variables must be declared with type pthread_mutex_t, and
    must be initialized before they can be used. There are two ways to
    initialize a mutex variable:

    1. Statically, when it is declared. For example:
      pthread_mutex_t mymutex = PTHREAD_MUTEX_INITIALIZER;
    2. Dynamically, with the pthread_mutex_init() routine. This
      method permits setting mutex object attributes, attr.

    The mutex is initially unlocked.

  • The attr object is used to establish properties for the mutex
    object, and must be of type pthread_mutexattr_t if used (may be
    specified as NULL to accept defaults). The Pthreads standard defines
    three optional mutex attributes:

    • Protocol: Specifies the protocol used to prevent priority
      inversions for a mutex.
    • Prioceiling: Specifies the priority ceiling of a mutex.
    • Process-shared: Specifies the process sharing of a mutex.

    Note that not all implementations may provide the three optional
    mutex attributes.

  • The pthread_mutexattr_init() and pthread_mutexattr_destroy()
    routines are used to create and destroy mutex attribute objects
    respectively.

  • pthread_mutex_destroy() should be used to free a mutex object
    which is no longer needed.
Mutex Variables

「Dijkstra’s revolutionary, safe-and-scalable Semaphore was applied in
both critical section protection and signaling. And thus the
confusion began. However, it later became obvious to operating system
developers, after the appearance of the priority-based preemptive RTOS
(e.g., VRTX, ca. 1980), publication of academic papers establishing
RMA and the problems caused by priority inversion, and a paper on
priority inheritance protocols in 1990, 3 it became apparent that
mutexes must be more than just semaphores with a binary counter.」@5

Locking and Unlocking Mutexes

ca88yzc 23 Routines:

ca88yzc 24 Usage:

  • The pthread_mutex_lock() routine is used by a thread to acquire a
    lock on the specified mutex variable. If the mutex is already
    locked by another thread, this call will block the calling thread
    until the mutex is unlocked.
  • pthread_mutex_trylock() will attempt to lock a mutex. However, if
    the mutex is already locked, the routine will return immediately
    with a “busy” error code. This routine may be useful in preventing
    deadlock conditions, as in a priority-inversion situation.
  • pthread_mutex_unlock() will unlock a mutex if called by the owning
    thread. Calling this routine is required after a thread has
    completed its use of protected data if other threads are to acquire
    the mutex for their work with the protected data. An error will be
    returned if:

    • If the mutex was already unlocked
    • If the mutex is owned by another thread
  • There is nothing “magical” about mutexes…in fact they are akin to
    a “gentlemen’s agreement” between participating threads. It is up to
    the code writer to insure that the necessary threads all make the
    the mutex lock and unlock calls correctly. The following scenario
    demonstrates a logical error:

     Thread 1 Thread 2 Thread 3
     Lock Lock 
     A = 2 A = A+1 A = A*B
     Unlock Unlock 
    
  Question: When more than one thread is waiting for a locked mutex, which thread will be granted the lock first after it is released?

前面提到semaphore最初用于互斥

Example: Using Mutexes

Example Code – Using Mutexes


#include <pthread.h>
#include <stdio.h>
#include <stdlib.h>

/* 
The following structure contains the necessary information 
to allow the function "dotprod" to access its input data and 
place its output into the structure. 
*/

typedef struct 
 {
 double *a;
 double *b;
 double sum; 
 int veclen; 
 } DOTDATA;

/* Define globally accessible variables and a mutex */

#define NUMTHRDS 4
#define VECLEN 100
 DOTDATA dotstr; 
 pthread_t callThd[NUMTHRDS];
 pthread_mutex_t mutexsum;

/*
The function dotprod is activated when the thread is created.
All input to this routine is obtained from a structure 
of type DOTDATA and all output from this function is written into
this structure. The benefit of this approach is apparent for the 
multi-threaded program: when a thread is created we pass a single
argument to the activated function - typically this argument
is a thread number. All the other information required by the 
function is accessed from the globally accessible structure. 
*/

void *dotprod(void *arg)
{

 /* Define and use local variables for convenience */

 int i, start, end, len ;
 long offset;
 double mysum, *x, *y;
 offset = (long)arg;

 len = dotstr.veclen;
 start = offset*len;
 end = start + len;
 x = dotstr.a;
 y = dotstr.b;

 /*
 Perform the dot product and assign result
 to the appropriate variable in the structure. 
 */

 mysum = 0;
 for (i=start; i<end ; i++) 
 {
 mysum += (x[i] * y[i]);
 }

 /*
 Lock a mutex prior to updating the value in the shared
 structure, and unlock it upon updating.
 */
 pthread_mutex_lock (&mutexsum);
 dotstr.sum += mysum;
 pthread_mutex_unlock (&mutexsum);

 pthread_exit((void*) 0);
}

/* 
The main program creates threads which do all the work and then 
print out result upon completion. Before creating the threads,
the input data is created. Since all threads update a shared structure, 
we need a mutex for mutual exclusion. The main thread needs to wait for
all threads to complete, it waits for each one of the threads. We specify
a thread attribute value that allow the main thread to join with the
threads it creates. Note also that we free up handles when they are
no longer needed.
*/

int main (int argc, char *argv[])
{
 long i;
 double *a, *b;
 void *status;
 pthread_attr_t attr;

 /* Assign storage and initialize values */
 a = (double*) malloc (NUMTHRDS*VECLEN*sizeof(double));
 b = (double*) malloc (NUMTHRDS*VECLEN*sizeof(double));

 for (i=0; i<VECLEN*NUMTHRDS; i++)
 {
 a[i]=1.0;
 b[i]=a[i];
 }

 dotstr.veclen = VECLEN; 
 dotstr.a = a; 
 dotstr.b = b; 
 dotstr.sum=0;

 pthread_mutex_init(&mutexsum, NULL);

 /* Create threads to perform the dotproduct */
 pthread_attr_init(&attr);
 pthread_attr_setdetachstate(&attr, PTHREAD_CREATE_JOINABLE);

    for(i=0; i<NUMTHRDS; i++)
 {
    /* 
    Each thread works on a different set of data.
    The offset is specified by 'i'. The size of
    the data for each thread is indicated by VECLEN.
    */
    pthread_create(&callThd[i], &attr, dotprod, (void *)i);
    }

 pthread_attr_destroy(&attr);

 /* Wait on the other threads */
    for(i=0; i<NUMTHRDS; i++)
 {
    pthread_join(callThd[i], &status);
    }

 /* After joining, print out the results and cleanup */
 printf ("Sum = %f \n", dotstr.sum);
 free (a);
 free (b);
 pthread_mutex_destroy(&mutexsum);
 pthread_exit(NULL);
} 

Serial version
Pthreads version

Condition Variables

「Until recently, the only sleeping lock in the kernel was the
semaphore. Most users of semaphores instantiated a semaphore with a
count of one and treated them as a mutual exclusion lock—a sleeping
version of the spin lock. Unfortunately, semaphores are rather generic
and do not impose many usage constraints.This makes them useful for
managing exclusive access in obscure situations, such as complicated
dances between the kernel and userspace. But it also means that
simpler locking is harder to do, and the lack of enforced rules makes
any sort of automated debugging or constraint enforcement impossible.
Seeking a simpler sleeping lock, the kernel developers introduced the
mutex.Yes, as you are now accustomed to, that is a confusing name.
Let’s clarify.The term “mutex” is a generic name to refer to any
sleeping lock that enforces mutual exclusion, such as a semaphore with
a usage count of one. In recent Linux kernels, the proper noun “mutex”
is now also a specific type of sleeping lock that implements mutual
exclusion.That is, a mutex is a mutex.」@lkd chap.10

「Semaphores Versus Mutexes Mutexes and semaphores are similar. Having
both in the kernel is confusing.Thankfully, the formula dictating
which to use is quite simple: Unless one of mutex’s additional
constraints prevent you from using them, prefer the new mutex type to
semaphores.When writing new code, only specific, often low-level, uses
need a semaphore. Start with a mutex and move to a semaphore only if
you run into one of their constraints and have no other
alternative.」@lkd chap.10

Overview

Condition variables provide yet another way for threads to synchronize.
While mutexes implement synchronization by controlling thread access to
data, condition variables allow threads to synchronize based upon the
actual value of data.

Without condition variables, the programmer would need to have threads
continually polling (possibly in a critical section), to check if the
condition is met. This can be very resource consuming since the thread
would be continuously busy in this activity. A condition variable is a
way to achieve the same goal without polling.

A condition variable is always used in conjunction with a mutex lock.

A representative sequence for using condition variables is shown below.

Main Thread

  • Declare and initialize global data/variables which require
    synchronization (such as “count”)
  • Declare and initialize a condition variable object
  • Declare and initialize an associated mutex
  • Create threads A and B to do work

Thread A

  • Do work up to the point where a certain condition must occur (such
    as “count” must reach a specified value)
  • Lock associated mutex and check value of a global variable
  • Call pthread_cond_wait() to perform a blocking wait for signal
    from Thread-B. Note that a call to pthread_cond_wait()
    automatically and atomically unlocks the associated mutex variable
    so that it can be used by Thread-B.
  • When signalled, wake up. Mutex is automatically and atomically
    locked.
  • Explicitly unlock mutex
  • Continue

Thread B

  • Do work
  • Lock associated mutex
  • Change the value of the global variable that Thread-A is waiting
    upon.
  • Check value of the global Thread-A wait variable. If it fulfills the
    desired condition, signal Thread-A.
  • Unlock mutex.
  • Continue

Main Thread

Condition Variables

在linux上,一般在线程中使用mutex进行互斥,不使用semaphore;进程间互斥可以使用mutex进行互斥,「If
the process-shared mutex attribute is set to PTHREAD_PROCESS_SHARED,a
mutex allocated from a memory extent shared between multiple processes
may be used for synchronization by those processes.」@APUE section 12.4

Creating and Destroying Condition Variables

ca88yzc 25 Routines:

ca88yzc 26 Usage:

  • Condition variables must be declared with type pthread_cond_t, and
    must be initialized before they can be used. There are two ways to
    initialize a condition variable:

    1. Statically, when it is declared. For example:
      pthread_cond_t myconvar = PTHREAD_COND_INITIALIZER;
    2. Dynamically, with the pthread_cond_init() routine. The ID of
      the created condition variable is returned to the calling thread
      through the condition parameter. This method permits setting
      condition variable object attributes, attr.
  • The optional attr object is used to set condition variable
    attributes. There is only one attribute defined for condition
    variables: process-shared, which allows the condition variable to be
    seen by threads in other processes. The attribute object, if used,
    must be of type pthread_condattr_t (may be specified as NULL to
    accept defaults).

    Note that not all implementations may provide the process-shared
    attribute.

  • The pthread_condattr_init() and pthread_condattr_destroy()
    routines are used to create and destroy condition variable attribute
    objects.

  • pthread_cond_destroy() should be used to free a condition variable
    that is no longer needed.
Condition Variables

「A mutex is really a semaphore with value 1? No, no and no again.」@1

「The mutex is similar to the principles of the binary semaphore with
one significant difference: the principle of ownership. Ownership
is the simple concept that when a task locks (acquires) a mutex only
it can unlock (release) it.」@3

「The concept of ownership enables mutex implementations to address
the problems discussed in part 1:」@3

「the inherent dangers associated with using the semaphore: 1.
Accidental release (an inherent weakness of using the counting
semaphore as a binary semaphore) 2. Recursive deadlock 3. Task-Death
deadlock 4. Priority inversion 5. Semaphore as a signal (Due to
ownership a mutex cannot be used for synchronization due to
lock/unlock pairing. This makes the code cleaner by not confusing the
issues of mutual exclusion with synchronization)」@1

「In object terminology we can observe that : observation.1 Semaphore
contains mutex observation.2 Mutex is not semaphore and semaphore is
not mutex. There are some semaphores that will act as if they are
mutex, called binary semaphores, but they are freaking NOT mutex.
There is a special ingredient called Signaling (posix uses
condition_variable for that name), required to make a Semaphore out
of mutex. Think of it as a notification-source. If two or more threads
are subscribed to same notification-source, then it is possible to
send them message to either ONE or to ALL, to wakeup. There could be
one or more counters associated with semaphores, which are guarded by
mutex. The simple most scenario for semaphore, there is a single
counter which can be either 0 or 1. This is where confusion pours in
like monsoon rain. A semaphore with a counter that can be 0 or 1 is
NOT mutex. Mutex has two states (0,1) and one ownership(task).
Semaphore has a mutex, some counters and a condition variable. Now,
use your imagination, and every combination of usage of counter and
when to signal can make one kind-of-Semaphore. Single counter with
value 0 or 1 and signaling when value goes to 1 AND then unlocks one
of the guy waiting on the signal == Binary semaphore Single
counter with value 0 to N and signaling when value goes to less than
N, and locks/waits when values is N == Counting semaphore Single
counter with value 0 to N and signaling when value goes to N, and
locks/waits when values is less than N == Barrier semaphore (well
if they don‘t call it, then they should.) Now to your question, when
to use what. (OR rather correct question version.3 when to use mutex
and when to use binary-semaphore, since there is no comparison to
non-binary-semaphore.) Use mutex when 1. you want a customized
behavior, that is not provided by binary semaphore, such are spin-lock
or fast-lock or recursive-locks. You can usually customize mutexes
with attributes, but customizing semaphore is nothing but writing new
semaphore. 2. you want lightweight OR faster primitive Use semaphores,
when what you want is exactly provided by it. If you don‘t understand
what is being provided by your implementation of binary-semaphore,
then IMHO, use mutex.」@http:// class=”visible”>stackoverflow.com/quest class=”invisible”>ions/4039899/when-should-we-use-mutex-and-when-should-we-use-semaphore
Ajeet Ganga

「The correct use of a semaphore is for signaling from one task to
another. A mutex is meant to be taken and released, always in that
order, by each task that uses the shared resource it protects. By
contrast, tasks that use semaphores either signal or wait—not
both.」@5

「mutexes should be used to protect shared resources, while semaphores
should be used for signaling.」@6

「Mutual Exclusion semaphores are used to protect shared resources…A
Binary semaphore should be used for Synchronization」@ class=”invisible”>https:// class=”visible”>stackoverflow.com/quest class=”invisible”>ions/62814/difference-between-binary-semaphore-and-mutex
Benoit

「companies like Wind River Systems redefining a mutex as a
“Mutual-Exclusion Semaphore”」@1

「a mutex is locking mechanism used to synchronize access to a
resource. ..Semaphore is signaling mechanism.」@ class=”invisible”>http://www. class=”visible”>geeksforgeeks.org/mutex class=”invisible”>-vs-semaphore/
「a mutex cannot be used for synchronization」@3

Waiting and Signaling on Condition Variables

ca88yzc 27 Routines:

ca88yzc 28 Usage:

  • pthread_cond_wait() blocks the calling thread until the specified
    condition is signalled. This routine should be called while
    mutex is locked, and it will automatically release the mutex while
    it waits. After signal is received and thread is awakened, mutex
    will be automatically locked for use by the thread. The programmer
    is then responsible for unlocking mutex when the thread is
    finished with it.
  • The pthread_cond_signal() routine is used to signal (or wake up)
    another thread which is waiting on the condition variable. It should
    be called after mutex is locked, and must unlock mutex in order
    for pthread_cond_wait() routine to complete.
  • The pthread_cond_broadcast() routine should be used instead of
    pthread_cond_signal() if more than one thread is in a blocking
    wait state.
  • It is a logical error to call pthread_cond_signal() before calling
    pthread_cond_wait().
Proper locking and unlocking of the associated mutex variable is essential when using these routines. For example:

  • Failing to lock the mutex before calling pthread_cond_wait() may cause it NOT to block.
  • Failing to unlock the mutex after calling pthread_cond_signal() may not allow a matching pthread_cond_wait() routine to complete (it will remain blocked).

以上所说的signaling和synchronization是一个意思。

Example: Using Condition Variables

Example Code – Using Condition Variables


#include <pthread.h>
#include <stdio.h>
#include <stdlib.h>

#define NUM_THREADS 3
#define TCOUNT 10
#define COUNT_LIMIT 12

int count = 0;
int thread_ids[3] = {0,1,2};
pthread_mutex_t count_mutex;
pthread_cond_t count_threshold_cv;

void *inc_count(void *t) 
{
 int j,i;
 double result=0.0;
 long my_id = (long)t;

 for (i=0; i<TCOUNT; i++) {
 pthread_mutex_lock(&count_mutex);
 count++;

 /* 
 Check the value of count and signal waiting thread when condition is
 reached. Note that this occurs while mutex is locked. 
 */
 if (count == COUNT_LIMIT) {
 pthread_cond_signal(&count_threshold_cv);
 printf("inc_count(): thread %ld, count = %d Threshold reached.\n", 
 *my_id, count);
 }
 printf("inc_count(): thread %ld, count = %d, unlocking mutex\n", 
    *my_id, count);
 pthread_mutex_unlock(&count_mutex);

 /* Do some "work" so threads can alternate on mutex lock */
 sleep(1);
 }
 pthread_exit(NULL);
}

void *watch_count(void *t) 
{
 long my_id - (long)t;

 printf("Starting watch_count(): thread %ld\n", *my_id);

 /*
 Lock mutex and wait for signal. Note that the pthread_cond_wait 
 routine will automatically and atomically unlock mutex while it waits. 
 Also, note that if COUNT_LIMIT is reached before this routine is run by
 the waiting thread, the loop will be skipped to prevent pthread_cond_wait
 from never returning. 
 */
 pthread_mutex_lock(&count_mutex);
 if (count<COUNT_LIMIT) {
 pthread_cond_wait(&count_threshold_cv, &count_mutex);
 printf("watch_count(): thread %ld Condition signal received.\n", my_id);
 count += 125;
 printf("watch_count(): thread %ld count now = %d.\n", my_id, count);
 }
 pthread_mutex_unlock(&count_mutex);
 pthread_exit(NULL);
}

int main (int argc, char *argv[])
{
 int i, rc;
 long t1=1, t2=2, t3=3;
 pthread_t threads[3];
 pthread_attr_t attr;

 /* Initialize mutex and condition variable objects */
 pthread_mutex_init(&count_mutex, NULL);
 pthread_cond_init (&count_threshold_cv, NULL);

 /* For portability, explicitly create threads in a joinable state */
 pthread_attr_init(&attr);
 pthread_attr_setdetachstate(&attr, PTHREAD_CREATE_JOINABLE);
 pthread_create(&threads[0], &attr, watch_count, (void *)t1);
 pthread_create(&threads[1], &attr, inc_count, (void *)t2);
 pthread_create(&threads[2], &attr, inc_count, (void *)t3);

 /* Wait for all threads to complete */
 for (i=0; i<NUM_THREADS; i++) {
 pthread_join(threads[i], NULL);
 }
 printf ("Main(): Waited on %d threads. Done.\n", NUM_THREADS);

 /* Clean up and exit */
 pthread_attr_destroy(&attr);
 pthread_mutex_destroy(&count_mutex);
 pthread_cond_destroy(&count_threshold_cv);
 pthread_exit(NULL);

}

LLNL Specific Information and Recommendations

This section describes details specific to Livermore Computing’s
systems.

ca88yzc 29 Implementations:

  • All LC production systems include a Pthreads implementation that
    follows draft 10 (final) of the POSIX standard. This is the
    preferred implementation.
  • Implementations differ in the maximum number of threads that a
    process may create. They also differ in the default amount of thread
    stack space.

ca88yzc 30 Compiling:

  • LC maintains a number of compilers, and usually several different
    versions of each – see the LC’s Supported
    Compilers web page.
  • The compiler commands described in the Compiling Threaded
    Programs
    section apply to LC systems.
  • Additionally, all LC IBM compilers are aliased to their thread-safe
    command. For example, xlc really uses xlc_r. This is only true for
    LC IBM systems.

ca88yzc 31 Mixing MPI with Pthreads:

  • Programs that contain both MPI and Pthreads are common and easy to
    develop on all LC systems.
  • Design:
    • Each MPI process typically creates and then manages N threads,
      where N makes the best use of the available CPUs/node.
    • Finding the best value for N will vary with the platform and
      your application’s characteristics.
    • For IBM SP systems with two communication adapters per node, it
      may prove more efficient to use two (or more) MPI tasks per
      node.
    • In general, there may be problems if multiple threads make MPI
      calls. The program may fail or behave unexpectedly. If MPI calls
      must be made from within a thread, they should be made only by
      one thread.
  • Compiling:
    • Use the appropriate MPI compile command for the platform and
      language of choice
    • Be sure to include the required flag as in the table above
      (-pthread or -qnosave)
    • MPICH is not thread safe
  • An example code that uses both MPI and Pthreads is available below.
    The serial, threads-only, MPI-only and MPI-with-threads versions
    demonstrate one possible progression.

    • Serial
    • Pthreads
      only
    • MPI
      only
    • MPI with
      pthreads
    • makefile
      (for IBM SP)
Topics Not Covered

Several features of the Pthreads API are not covered in this tutorial.
These are listed below. See the Pthread Library Routines
Reference
section for more information.

  • Thread Scheduling
    • Implementations will differ on how threads are scheduled to run.
      In most cases, the default mechanism is adequate.
    • The Pthreads API provides routines to explicitly set thread
      scheduling policies and priorities which may override the
      default mechanisms.
    • The API does not require implementations to support these
      features.
  • Keys: Thread-Specific Data
    • As threads call and return from different routines, the local
      data on a thread’s stack comes and goes.
    • To preserve stack data you can usually pass it as an argument
      from one routine to the next, or else store the data in a global
      variable associated with a thread.
    • Pthreads provides another, possibly more convenient and
      versatile, way of accomplishing this through keys.
  • Mutex Protocol Attributes and Mutex Priority Management for the
    handling of “priority inversion” problems.
  • Condition Variable Sharing – across processes
  • Thread Cancellation
  • Threads and Signals
Pthread Library Routines Reference

References and More Information
  • Author: Blaise Barney, Livermore
    Computing.
  • “Pthreads Programming”. B. Nichols et al. O’Reilly and Associates.
  • “Threads Primer”. B. Lewis and D. Berg. Prentice Hall
  • “Programming With POSIX Threads”. D. Butenhof. Addison Wesley
    www.awl.com/cseng/titles/0-201-63392-2
  • “Programming With Threads”. S. Kleiman et al. Prentice Hall

synchronization

「the term synchronization is often misused in the context of mutual
exclusion」@1

「Synchronization is, by definition “To occur at the same time; be
simultaneous”. Synchronization between tasks is where, typically, one
task waits to be notified by another task before it can continue
execution (unilateral rendezvous). A variant of this is either task
may wait, called the bidirectional rendezvous.」@1

将synchronization和mutual
exclusion的概念分开来更易于理解和开发。打个比方,餐厅中,洗菜工之间以及厨师之间是互斥关系,洗菜工和厨师之间是同步关系。但很多地方将后者归入前者。

「进程互斥是指若干进程因相互争夺独占型资源而产生的竞争制约关系。」「进程同步是指为完成共同任务的并发进程基于某个条件来协调其活动,因为需要在某些位置上排定执行的先后次序而等待、传递信号或消息所产生的协作制约关系。」
「进程互斥关系是一种特殊的进程同步关系,即逐次使用互斥共享资源,也是对进程使用资源的次序的一种协调。」
@《操作系统教程/孙钟秀(第四版)》3.1.3节

「Process synchronization refers to the idea that multiple processes
are to join up or handshake at a certain point, in order to reach an
agreement or commit to a certain sequence of action……Processes’
access to critical section is controlled by using synchronization
techniques…Another synchronization requirement which needs to be
considered is the order in which particular processes or threads
should be executed.」@4

维基百科介绍的synchronization包含了mutual exclusion

APUE section 11.6 Thread Synchronization包含mutex,condition
variable,barrier等

lkd chap.10 Kernel Synchronization
Methods包含semaphore,mutex,completion
variable,barrier等。它比较了semaphore和mutex,但没有比较semaphore和completion
variable。completion variable用于“狭义”上的synchronization,「Using
completion variables is an easy way to synchronize between two tasks in
the kernel when one task needs to signal to the other that an event has
occurred.」

TLPI chap.10 THREADS: THREAD SYNCHRONIZATION主要介绍了Protecting
Accesses to Shared Variables: Mutexes和Signaling Changes of State:
Condition Variables。不妨理解为后者才是真正意义上的synchronization.

TLPI chap.40 INTERPROCESS COMMUNICATION OVERVIEW section 43.3
Synchronization Facilities包含了Semaphores,File locks,Mutexes and
condition
variables。值得注意的是,作者将IPC分为communication,synchronization,signal三类,将System
V IPC三件套中的semaphore和POSIX
semaphore一起归入synchronization中。这样划分更合理。

我认为应该把广义上的synchronization称为coordination,后者包含mutual
exclusion和synchronization。

condition variable

@TLPI section 30.2.2

condition variable vs semaphore

「What is important to understand is that the semaphore counter keeps
track of the number of tasks that do not have to block, i.e., they can
make progress. Tasks block, and add themselves to the semaphore’s list
only when the counter is zero.」@6 aspen100

「A condition variable holds no state information. It is simply a
mechanism for communicating information about the application’s state.
If no thread is waiting on the condition variable at the time that it
is signaled, then the signal is lost. A thread that later waits on the
condition variable will unblock only when the variable is signaled
once more.」@TLPI section 30.2.2

https://stackoverflow.com/questions/3513045/conditional-variable-vs-semaphore
:

「Condition variable is essentially a wait-queue…Semaphore is
essentially a counter + a mutex + a wait queue…semaphore can be
treated as a more sophisticated structure than condition variable,
while the latter is more lightweight and flexible.」@cucufrog

「Semaphores can be used to implement exclusive access to variables,
however they are meant to be used for synchronization. Mutexes, on the
other hand, have a semantics which is strictly related to mutual
exclusion: only the process which locked the resource is allowed to
unlock it. Unfortunately you cannot implement synchronization with
mutexes, that’s why we have condition variables. Also notice that with
condition variables you can unlock all the waiting threads in the
same instant
by using the broadcast unlocking. This cannot be done
with semaphores.」@Dacav

「to implement barrier synchronization you would not be able to
use a semaphore.But a condition variable is ideal.」@Danielle

参考前面Ajeet Ganga提到的barrier semaphore

「Semaphore is used to control the number of threads executing. There
will be fixed set of resources. 」@berkay

这种情景使用semaphore很贴切。

「Semaphores vs. Condition Variables 1. Up differs from Signal in
that: –Signal has no effect if no thread is waiting on the condition.
—-Condition variables are not variables! They have no value! –Up
has the same effect whether or not a thread is waiting. —-Semaphores
retains a “memory” of calls to Up. 2. Down differs from Wait in that:
–Down checks the condition and blocks only if necessary. —-no need
to recheck the condition after returning from Down —-wait condition
is defined internally, but is limited to a counter –Wait is explicit:
it does not check the condition, ever. —-condition is defined
externally and protected by integrated mutex」@ class=”invisible”>http://www. class=”visible”>cs.duke.edu/courses/spr class=”invisible”>ing01/cps110/slides/syncprog/sld006.htm

「Semaphores using Condition Variables. This constitutes a proof that
mutexes and condition variables are at least as powerful as
semaphores.」 @http://www. class=”visible”>cs.duke.edu/courses/spr class=”invisible”>ing01/cps110/slides/syncprog/sld007.htm

来源:

1.
https://blog.feabhas.com/2009/09/mutex-vs-semaphores-%e2%80%93-part-1-semaphores/

  1. https://en.m.wikipedia.org/wiki/Mutual\_exclusion

3.
https://blog.feabhas.com/2009/09/mutex-vs-semaphores-%e2%80%93-part-2-the-mutex/

  1. https://en.m.wikipedia.org/wiki/Synchronization\_(computer\_science)

  2. https://barrgroup.com/Embedded-Systems/How-To/RTOS-Mutex-Semaphore

  3. http://stackoverflow.com/questions/34519/what-is-a-semaphore

  4. APUE(Advanced Programming in the Unix Environment) 3ed

  5. TLPI(The Linux Programming Interface)

  6. lkd(linux kernel development)3ed

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