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Chapter 1

Covering Multithreading Basics

The word multithreading can be translated as multiple threads of control or multiple flows of control. While a traditional UNIX process always has contained and still does contain a single thread of control, multithreading (MT) separates a process into many execution threads, each of which runs independently.

Multithreading your code can

  • Improve application responsiveness

  • Use multiprocessors more efficiently

  • Improve program structure

  • Use fewer system resources

This chapter explains some multithreading terms, benefits, and concepts. If you are ready to start using multithreading, skip to Chapter 2, Basic Threads Programming.

Defining Multithreading Terms

Table 1-1 introduces some of the terms used in this book.

Table 1-1 Multithreading Terms

Term

Definition

Process

The UNIX environment (such as file descriptors, user ID, and so on) created with the fork(2) system call, which is set up to run a program.

Thread

A sequence of instructions executed within the context of a process.

pthreads (POSIX threads)

A POSIX 1003.1c compliant threads interface.

Solaris threads

A Sun Microsystems™ threads interface that is not POSIX compliant. A predecessor of pthreads.

Single-threaded

Restricting access to a single thread.

Multithreaded

Allowing access to two or more threads.

User- or Application-level threads

Threads managed by the threads library routines in user (as opposed to kernel) space.

Lightweight processes

Threads in the kernel that execute kernel code and system calls (also called LWPs).

Bound thread

A user-level thread that is permanently bound to one LWP.

Unbound thread

A user-level thread that is not necessarily bound to one LWP.

Attribute object

Contains opaque data types and related manipulation functions used to standardize some of the configurable aspects of POSIX threads, mutual exclusion locks (mutexes), and condition variables.

Mutual exclusion locks

Functions that lock and unlock access to shared data.

Condition variables

Functions that block threads until a change of state.

Read-write locks

Functions that allow multiple read-only access to shared data, but exclusive access for modification of that data.

Counting semaphore

A memory-based synchronization mechanism.

Parallelism

A condition that arises when at least two threads are executing simultaneously.

Concurrency

A condition that exists when at least two threads are making progress. A more generalized form of parallelism that can include time-slicing as a form of virtual parallelism.

Meeting Multithreading Standards

The concept of multithreaded programming goes back to at least the 1960s. Its development on UNIX systems began in the mid-1980s. While there is agreement about what multithreading is and the features necessary to support it, the interfaces used to implement multithreading have varied greatly.

For several years a group called POSIX (Portable Operating System Interface) 1003.4a has been working on standards for multithreaded programming. The standard has now been ratified. This Multithreaded Programming Guide is based on the POSIX standards: P1003.1b final draft 14 (realtime), and P1003.1c final draft 10 (multithreading).

This guide covers both POSIX threads (also called pthreads) and Solaris threads. Solaris threads were available in the Solaris 2.4 release, and are not functionally different from POSIX threads. However, because POSIX threads are more portable than Solaris threads, this guide covers multithreading from the POSIX perspective. Subjects specific to Solaris threads only are covered in the Chapter 8, Programming With Solaris Threads.

Benefiting From Multithreading

Improving Application Responsiveness

Any program in which many activities are not dependent upon each other can be redesigned so that each activity is defined as a thread. For example, the user of a multithreaded GUI does not have to wait for one activity to complete before starting another.

Using Multiprocessors Efficiently

Typically, applications that express concurrency requirements with threads need not take into account the number of available processors. The performance of the application improves transparently with additional processors.

Numerical algorithms and applications with a high degree of parallelism, such as matrix multiplications, can run much faster when implemented with threads on a multiprocessor.

Improving Program Structure

Many programs are more efficiently structured as multiple independent or semi-independent units of execution instead of as a single, monolithic thread. Multithreaded programs can be more adaptive to variations in user demands than single-threaded programs.

Using Fewer System Resources

Programs that use two or more processes that access common data through shared memory are applying more than one thread of control.

However, each process has a full address space and operating environment state. The cost of creating and maintaining this large amount of state information makes each process much more expensive than a thread in both time and space.

In addition, the inherent separation between processes can require a major effort by the programmer to communicate between the threads in different processes, or to synchronize their actions.

Combining Threads and RPC

By combining threads and a remote procedure call (RPC) package, you can exploit nonshared-memory multiprocessors (such as a collection of workstations). This combination distributes your application relatively easily and treats the collection of workstations as a multiprocessor.

For example, one thread might create child threads. Each of these children could then place a remote procedure call, invoking a procedure on another workstation. Although the original thread has merely created threads that are now running in parallel, this parallelism involves other computers.

Understanding Basic Multithreading Concepts

Concurrency and Parallelism

In a multithreaded process on a single processor, the processor can switch execution resources between threads, resulting in concurrent execution.

In the same multithreaded process in a shared-memory multiprocessor environment, each thread in the process can run on a separate processor at the same time, resulting in parallel execution.

When the process has fewer or as many threads as there are processors, the threads support system in conjunction with the operating environment ensure that each thread runs on a different processor.

For example, in a matrix multiplication that has the same number of threads and processors, each thread (and each processor) computes a row of the result.

Looking at Multithreading Structure

Traditional UNIX already supports the concept of threads--each process contains a single thread, so programming with multiple processes is programming with multiple threads. But a process is also an address space, and creating a process involves creating a new address space.

Creating a thread is less expensive when compared to creating a new process, because the newly created thread uses the current process address space. The time it takes to switch between threads is less than the time it takes to switch between processes, partly because switching between threads does not involve switching between address spaces.

Communicating between the threads of one process is simple because the threads share everything--address space, in particular. So, data produced by one thread is immediately available to all the other threads.

The interface to multithreading support is through a subroutine library, libpthread for POSIX threads, and libthread for Solaris threads. Multithreading provides flexibility by decoupling kernel-level and user-level resources.

 
 
 
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