POSIX Threads Programming

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https://computing.llnl.gov/tutorials/pthreads/

Abstract
Pthreads Overview
1. What is a Thread?
2. What are Pthreads?
3. Why Pthreads?
4. Designing Threaded Programs
The Pthreads API
Compiling Threaded Programs
Thread Management
1. Creating and Terminating Threads
2. Passing Arguments to Threads
3. Joining and Detaching Threads
4. Stack Management
5. Miscellaneous Routines
Exercise 1
Mutex Variables
1. Mutex Variables Overview
2. Creating and Destroying Mutexes
3. Locking and Unlocking Mutexes
Condition Variables
1. Condition Variables Overview
2. Creating and Destroying Condition Variables
3. Waiting and Signaling on Condition Variables
Monitoring, Debugging and Performance Analysis Tools for Pthreads
LLNL Specific Information and Recommendations
Topics Not Covered
Exercise 2
References and More Information
Appendix A: Pthread Library Routines Reference

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: This tutorial is one of the eight tutorials in the 4+ day "Using LLNL's Supercomputers" workshop. It is deal for those who are new to parallel programming with threads. A basic understanding of parallel programming in C is required. For those who are unfamiliar with Parallel Programming in general, the material covered inEC3500: Introduction To Parallel Computing would be helpful.

Pthreads Overview

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 PROCESSTHREADS 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

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 adhering to this standard are referred to as POSIX threads, or Pthreads.
- Most hardware vendors now offer Pthreads in addition to their proprietary API's.
The POSIX standard has continued to evolve and undergo revisions, including the Pthreads specification.
Some useful links:
- standards.ieee.org/findstds/standard/1003.1-2008.html
- www.opengroup.org/austin/papers/posix_faq.html
- www.unix.org/version3/ieee_std.html
Pthreads are defined as a set of C language programming types and procedure calls, implemented with apthread.h header/include file and a thread library - though this library may be part of another library, such aslibc, in some implementations.

Pthreads Overview
Why Pthreads?
- In the world of high performance computing, 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 thepthread_create() subroutine. Timings reflect 50,000 process/thread creations, were performed with thetime 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 run on local machines, past and present.
  Platformfork()pthread_create()realusersysrealusersysIntel 2.6 GHz Xeon E5-2670 (16 cores/node)8.10.12.90.90.20.3Intel 2.8 GHz Xeon 5660 (12 cores/node)4.40.44.30.70.20.5AMD 2.3 GHz Opteron (16 cores/node)12.51.012.51.20.21.3AMD 2.4 GHz Opteron (8 cores/node)17.62.215.71.40.31.3IBM 4.0 GHz POWER6 (8 cpus/node)9.50.68.81.60.10.4IBM 1.9 GHz POWER5 p5-575 (8 cpus/node)64.230.727.61.70.61.1IBM 1.5 GHz POWER4 (8 cpus/node)104.548.647.22.11.01.5INTEL 2.4 GHz Xeon (2 cpus/node)54.91.520.81.60.70.9INTEL 1.4 GHz Itanium2 (4 cpus/node)54.51.122.22.01.20.6 fork_vs_thread.txt
- 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:
    PlatformMPI Shared Memory Bandwidth
    (GB/sec)Pthreads Worst Case
    Memory-to-CPU Bandwidth
    (GB/sec)Intel 2.6 GHz Xeon E5-26704.551.2Intel 2.8 GHz Xeon 56605.632AMD 2.3 GHz Opteron1.85.3AMD 2.4 GHz Opteron1.25.3IBM 1.9 GHz POWER5 p5-5754.116IBM 1.5 GHz POWER42.14Intel 2.4 GHz Xeon0.34.3Intel 1.4 GHz Itanium 21.86.4
- Pthreads can also be used for serial applications, to emulate parallel execution and/or take advantage of spare cycles.
- 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.
- Many other common serial applications and operating systems use threads. An example of the MS Windows OS and applications using threads is shown below.
  
  Click on image for a larger version
Pthreads Overview
Designing Threaded Programs
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 theIntroduction 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.
- 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)
- Several common models for threaded programs exist:
  - Manager/worker: a single thread, the manager assigns work to other threads, theworkers. 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.
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.
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.
- 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.
Thread Limits:
- Although the Pthreads API is an ANSI/IEEE standard, implementations can, and usually do, vary in ways not specified by the standard.
- Because of this, a program that runs fine on one platform, may fail or produce wrong results on another platform.
- For example, the maximum number of threads permitted, and the default thread stack size are two important limits to consider when designing your program.
- Several thread limits are discussed in more detail later in this tutorial.
The Pthreads API
- The original Pthreads API was defined in the ANSI/IEEE POSIX 1003.1 - 1995 standard. The POSIX standard has continued to evolve and undergo revisions, including the Pthreads specification.
- Copies of the standard can be purchased from IEEE or downloaded for free from other sites online.
- The subroutines which comprise the Pthreads API can be informally grouped into four major groups:
  1. Thread management: Routines that work directly on threads - creating, detaching, joining, etc. They also include functions to set/query thread attributes (joinable, scheduling etc.)
  2. Mutexes: Routines that deal with synchronization, called a "mutex", which is an abbreviation for "mutual exclusion". Mutex functions provide for creating, destroying, locking and unlocking mutexes. These are supplemented by mutex attribute functions that set or modify attributes associated with mutexes.
  3. Condition variables: Routines that address communications between threads that share a mutex. Based upon programmer specified conditions. This group includes functions to create, destroy, wait and signal based upon specified variable values. Functions to set/query condition variable attributes are also included.
  4. Synchronization: Routines that manage read/write locks and barriers.
- Naming conventions: All identifiers in the threads library begin with pthread_. Some examples are shown below.
  Routine PrefixFunctional Grouppthread_Threads themselves and miscellaneous subroutinespthread_attr_Thread attributes objectspthread_mutex_Mutexespthread_mutexattr_Mutex attributes objects.pthread_cond_Condition variablespthread_condattr_Condition attributes objectspthread_key_Thread-specific data keyspthread_rwlock_Read/write lockspthread_barrier_Synchronization barriers
- 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 around 100 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 theReferencessection of this tutorial.
Compiling Threaded Programs
- Several examples of compile commands used for pthreads codes are listed in the table below.
  Compiler / PlatformCompiler CommandDescriptionINTEL
  Linuxicc -pthreadCicpc -pthreadC++PGI
  Linuxpgcc -lpthreadCpgCC -lpthreadC++GNU
  Linux, Blue Genegcc -pthreadGNU Cg++ -pthreadGNU C++IBM
  Blue Genebgxlc_r / bgcc_rC (ANSI / non-ANSI)bgxlC_r, bgxlc++_rC++
Thread Management
Creating and Terminating Threads
Routines:
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. Programs that attempt to exceed the limit can fail or produce wrong results.
- Querying and setting your implementation's thread limit - Linux example shown. Demonstrates querying the default (soft) limits and then setting the maximum number of processes (including threads) to the hard limit. Then verifying that the limit has been overridden.
  bash / ksh / shtcsh / csh
```
$ ulimit -acore file size          (blocks, -c) 16data seg size           (kbytes, -d) unlimitedscheduling priority             (-e) 0file size               (blocks, -f) unlimitedpending signals                 (-i) 255956max locked memory       (kbytes, -l) 64max memory size         (kbytes, -m) unlimitedopen files                      (-n) 1024pipe size            (512 bytes, -p) 8POSIX message queues     (bytes, -q) 819200real-time priority              (-r) 0stack size              (kbytes, -s) unlimitedcpu time               (seconds, -t) unlimitedmax user processes              (-u) 1024virtual memory          (kbytes, -v) unlimitedfile locks                      (-x) unlimited$ ulimit -Hu7168$ ulimit -u 7168$ ulimit -acore file size          (blocks, -c) 16data seg size           (kbytes, -d) unlimitedscheduling priority             (-e) 0file size               (blocks, -f) unlimitedpending signals                 (-i) 255956max locked memory       (kbytes, -l) 64max memory size         (kbytes, -m) unlimitedopen files                      (-n) 1024pipe size            (512 bytes, -p) 8POSIX message queues     (bytes, -q) 819200real-time priority              (-r) 0stack size              (kbytes, -s) unlimitedcpu time               (seconds, -t) unlimitedmax user processes              (-u) 7168virtual memory          (kbytes, -v) unlimitedfile locks                      (-x) unlimited
```
```
% limit cputime      unlimitedfilesize     unlimiteddatasize     unlimitedstacksize    unlimitedcoredumpsize 16 kbytesmemoryuse    unlimitedvmemoryuse   unlimiteddescriptors  1024 memorylocked 64 kbytesmaxproc      1024% limit maxproc unlimited% limitcputime      unlimitedfilesize     unlimiteddatasize     unlimitedstacksize    unlimitedcoredumpsize 16 kbytesmemoryuse    unlimitedvmemoryuse   unlimiteddescriptors  1024 memorylocked 64 kbytesmaxproc      7168
```
- Once created, threads are peers, and may create other threads. There is no implied hierarchy or dependency between threads.
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. Attributes include:
  - Detached or joinable state
  - Scheduling inheritance
  - Scheduling policy
  - Scheduling parameters
  - Scheduling contention scope
  - Stack size
  - Stack address
  - Stack guard (overflow) size
- Some of these attributes will be discussed later.
Thread Binding and Scheduling:
Question: After a thread has been created, how do you know a)when it will be scheduled to run by the operating system, and b)which processor/core it will run on?
- The Pthreads API provides several routines that may be used to specify how threads are scheduled for execution. For example, threads can be scheduled to run FIFO (first-in first-out), RR (round-robin) or OTHER (operating system determines). It also provides the ability to set a thread's scheduling priority value.
- These topics are not covered here, however a good overview of "how things work" under Linux can be found in thesched_setscheduler man page.
- The Pthreads API does not provide routines for binding threads to specific cpus/cores. However, local implementations may include this functionality - such as providing the non-standardpthread_setaffinity_np routine. Note that "_np" in the name stands for "non-portable".
- Also, the local operating system may provide a way to do this. For example, Linux provides thesched_setaffinity routine.
Terminating Threads &pthread_exit():
- There are several ways in which a thread may be terminated:
  - The thread returns normally from its starting routine. It's work is done.
  - The thread makes a call to the pthread_exit subroutine - whether its work is done or not.
  - The thread is canceled by another thread via the pthread_cancel routine.
  - The entire process is terminated due to making a call to either the exec() orexit()
  - If main() finishes first, without calling pthread_exit explicitly itself
- The pthread_exit() routine allows the programmer to specify an optional terminationstatus parameter. This optional parameter is typically returned to threads "joining" the terminated thread (covered later).
- In subroutines that execute to completion normally, you can often dispense with callingpthread_exit() - unless, of course, you want to pass the optional status code back.
- Cleanup: the pthread_exit() routine does not close files; any files opened inside the thread will remain open after the thread is terminated.
- Discussion on calling pthread_exit() from main():
  - There is a definite problem if main() finishes before the threads it spawned if you don't callpthread_exit() explicitly. All of the threads it created will terminate because main() is done and no longer exists to support the threads.
  - By having main() explicitly call pthread_exit() as the last thing it does, main() will block and be kept alive to support the threads it created until they are done.
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 topthread_exit().
  Example Code - Pthread Creation and Termination
```
#include <pthread.h>#include <stdio.h>#define NUM_THREADS     5void *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);      }   }   /* Last thing that main() should do */   pthread_exit(NULL);}
```
Thread Management
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?
Thread Management
Joining and Detaching Threads
Routines:
Joining:
- "Joining" is one way to accomplish synchronization between threads. For example:
- The pthread_join() subroutine blocks the calling thread until the specifiedthreadid 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 topthread_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.
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.
- To explicitly create a thread as joinable or detached, the attr argument in thepthread_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()
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.
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.
Example: Pthread Joining
Thread Management
Stack Management
Routines:
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 thepthread_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.
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.
- Both past and present architectures are shown to demonstrate the wide variation in default thread stack size.
  Node
  Architecture#CPUsMemory (GB)Default Size
  (bytes)Intel Xeon E5-267016322,097,152Intel Xeon 566012242,097,152AMD Opteron8162,097,152Intel IA644833,554,432Intel IA32242,097,152IBM Power5832196,608IBM Power4816196,608IBM Power3161698,304
Example: Stack Management
Thread Management
Miscellaneous Routines
- pthread_self returns the unique, system assigned thread ID of the calling thread.
- pthread_equal compares two thread IDs. If the two IDs are different 0 is returned, otherwise a non-zero value is returned.
- Note that for both of these routines, the thread identifier objects are opaque and can not be easily inspected. Because thread IDs are opaque objects, the C language equivalence operator== should not be used to compare two thread IDs against each other, or to compare a single thread ID against another value.
  pthread_once (once_control, init_routine)
- pthread_once executes the init_routine exactly once in a process. The first call to this routine by any thread in the process executes the giveninit_routine, without parameters. Any subsequent call will have no effect.
- The init_routine routine is typically an initialization routine.
- The once_control parameter is a synchronization control structure that requires initialization prior to callingpthread_once. For example:
  pthread_once_t once_control = PTHREAD_ONCE_INIT;
Pthread Exercise 1
Getting Started and Thread Management Routines
Overview:
- Login to an LC cluster using your workshop username and OTP token
- Copy the exercise files to your home directory
- Familiarize yourself with LC's Pthreads environment
- Write a simple "Hello World" Pthreads program
- Successfully compile your program
- Successfully run your program - several different ways
- Review, compile, run and/or debug some related Pthreads programs (provided)
Go to the exercise now

Mutex Variables
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 1Thread 2BalanceRead balance: $1000 $1000 Read balance: $1000$1000 Deposit $200$1000Deposit $200 $1000Update 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
Creating and Destroying Mutexes
Routines:
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 typepthread_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
Locking and Unlocking Mutexes
Routines:
Usage:
- The pthread_mutex_lock() routine is used by a thread to acquire a lock on the specifiedmutex 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?
Example: Using Mutexes
Condition Variables
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 topthread_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
Creating and Destroying Condition Variables
Routines:
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 thecondition 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
Waiting and Signaling on Condition Variables
Routines:
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 unlockingmutex 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 aftermutex is locked, and must unlockmutex 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 matchingpthread_cond_wait() routine to complete (it will remain blocked).
Example: Using Condition Variables
Monitoring, Debugging and Performance Analysis Tools for Pthreads

Monitoring and Debugging Pthreads:
- Debuggers vary in their ability to handle Pthreads. The TotalView debugger is LC's recommended debugger for parallel programs. It is well suited for both monitoring and debugging threaded programs.
- An example screenshot from a TotalView session using a threaded code is shown below.
  1. Stack Trace Pane: Displays the call stack of routines that the selected thread is executing.
  2. Status Bars: Show status information for the selected thread and its associated process.
  3. Stack Frame Pane: Shows a selected thread's stack variables, registers, etc.
  4. Source Pane: Shows the source code for the selected thread.
  5. Root Window showing all threads
  6. Threads Pane: Shows threads associated with the selected process
- See the TotalView Debugger tutorial for details.
- The Linux ps command provides several flags for viewing thread information. Some examples are shown below. See theman page for details.
```
% ps -Lf UID        PID  PPID   LWP  C NLWP STIME TTY          TIME CMDblaise   22529 28240 22529  0    5 11:31 pts/53   00:00:00 a.outblaise   22529 28240 22530 99    5 11:31 pts/53   00:01:24 a.outblaise   22529 28240 22531 99    5 11:31 pts/53   00:01:24 a.outblaise   22529 28240 22532 99    5 11:31 pts/53   00:01:24 a.outblaise   22529 28240 22533 99    5 11:31 pts/53   00:01:24 a.out% ps -T   PID  SPID TTY          TIME CMD22529 22529 pts/53   00:00:00 a.out22529 22530 pts/53   00:01:49 a.out22529 22531 pts/53   00:01:49 a.out22529 22532 pts/53   00:01:49 a.out22529 22533 pts/53   00:01:49 a.out% ps -Lm   PID   LWP TTY          TIME CMD22529     - pts/53   00:18:56 a.out    - 22529 -        00:00:00 -    - 22530 -        00:04:44 -    - 22531 -        00:04:44 -    - 22532 -        00:04:44 -    - 22533 -        00:04:44 -
```
- LC's Linux clusters also provide the top command to monitor processes on a node. If used with the-H flag, the threads contained within a process will be visible. An example of thetop -H command is shown below. The parent process is PID 18010 which spawned three threads, shown as PIDs 18012, 18013 and 18014.
Performance Analysis Tools:
- There are a variety of performance analysis tools that can be used with threaded programs. Searching the web will turn up a wealth of information.
- At LC, the list of supported computing tools can be found at: computing.llnl.gov/code/content/software_tools.php.
- These tools vary significantly in their complexity, functionality and learning curve. Covering them in detail is beyond the scope of this tutorial.
- Some tools worth investigating, specifically for threaded codes, include:
  - Open|SpeedShop
  - TAU
  - PAPI
  - Intel VTune Amplifier
  - ThreadSpotter
LLNL Specific Information and Recommendations

This section describes details specific to Livermore Computing's systems.
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.
Compiling:
- LC maintains a number of compilers, and usually several different versions of each - see theLC's Supported Compilers web page.
- The compiler commands described in the Compiling Threaded Programs section apply to LC systems.
Mixing MPI with Pthreads:
- This is the primary motivation for using Pthreads at LC.
- Design:
  - Each MPI process typically creates and then manages N threads, where N makes the best use of the available cores/node.
  - Finding the best value for N will vary with the platform and your application's characteristics.
  - 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 Pthreads flag as shown in the Compiling Threaded Programs section.
- 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
Topics Not Covered

Several features of the Pthreads API are not covered in this tutorial. These are listed below. See thePthread 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 throughkeys.
- Mutex Protocol Attributes and Mutex Priority Management for the handling of "priority inversion" problems.
- Condition Variable Sharing - across processes
- Thread Cancellation
- Threads and Signals
- Synchronization constructs - barriers and locks
Pthread Exercise 2
Mutexes, Condition Variables and Hybrid MPI with Pthreads
Overview:
- Login to the LC workshop cluster, if you are not already logged in
- Mutexes: review and run the provided example codes
- Condition variables: review and run the provided example codes
- Hybrid MPI with Pthreads: review and run the provided example codes
Go to the exercise now
This completes the tutorial.
Please complete the online evaluation form - unless you are doing the exercise, in which case please complete it at the end of the exercise.
Where would you like to go now?
- Exercise
- Agenda
- Back to the top
References and More Information
- Author: Blaise Barney, Livermore Computing.
- POSIX Standard: www.unix.org/version3/ieee_std.html
- "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
Appendix A: Pthread Library Routines Reference