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

• Meeting Multithreading Standards

• Benefiting From Multithreading

• Understanding Basic Multithreading Concepts

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 MicrosystemsTM 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.

User-Level Threads

Threads are the primary programming interface in multithreaded programming. [User-level threads are so named to distinguish them from kernel-level threads, which are the concern of systems programmers only. Because this book is for application programmers, kernel-level threads are not discussed.] Threads are visible only from within the process, where they share all process resources like address space, open files, and so on. The following state is unique to each thread.

• Thread ID

• Register state (including PC and stack pointer)

• Stack

• Signal mask

• Priority

• Thread-private storage

Because threads share the process instructions and most of the process data, a change in shared data by one thread can be seen by the other threads in the process. When a thread needs to interact with other threads in the same process, it can do so without involving the operating environment.

By default, threads are lightweight. But, to get more control over a thread (for instance, to control scheduling policy more), the application can bind the thread. When an application binds threads to execution resources, the threads become kernel resources (see System Scope (Bound Threads)for more information).

To summarize, user-level threads are:

• Inexpensive to create because they do not need to create their own address space.

• Fast to synchronize because synchronization is done at the application level, not at the kernel level.

• Managed by the threads library; either libpthread or libthread.

Lightweight Processes

The threads library uses underlying threads of control called lightweight processes that are supported by the kernel. You can think of an LWP as a virtual CPU that executes code or system calls.

You usually do not need to concern yourself with LWPs to program with threads. The information here about LWPs is provided as background, so you can understand the differences in scheduling scope, described on Process Scope (Unbound Threads).

Much as the stdio library routines such as fopen() and fread() use the open() and read() functions, the threads interface uses the LWP interface, and for many of the same reasons.

Lightweight processes (LWPs) bridge the user level and the kernel level. Each process contains one or more LWP, each of which runs one or more user threads. (See Figure 1–1.)

Figure 1–1 User-level Threads and Lightweight Processes

Each LWP is a kernel resource in a kernel pool, and is allocated and de-allocated to a thread on a per thread basis.

Scheduling

POSIX specifies three scheduling policies: first-in-first-out (SCHED_FIFO), round-robin (SCHED_RR), and custom (SCHED_OTHER). SCHED_FIFO is a queue-based scheduler with different queues for each priority level. SCHED_RR is like FIFO except that each thread has an execution time quota.

Both SCHED_FIFO and SCHED_RR are POSIX Realtime extensions. SCHED_OTHER is the default scheduling policy.

See LWPs and Scheduling Classesfor information about the SCHED_OTHER policy.

Two scheduling scopes are available: process scope for unbound threads and system scope for bound threads. Threads with differing scope states can coexist on the same system and even in the same process. In general, the scope sets the range in which the threads scheduling policy is in effect.

Process Scope (Unbound Threads)

PTHREAD_SCOPE_PROCESS threads are created as unbound threads. The association of these threads with LWPs is managed by the threads library.

In most cases, threads should be PTHREAD_SCOPE_PROCESS. These threads have no restriction to execute on a particular LWP, and are equivalent to Solaris thread created without the THR_BOUND flag. The threads library decides the association between individual threads and LWPs.

System Scope (Bound Threads)

PTHREAD_SCOPE_SYSTEM threads are created as bound threads. A bound thread is permanently attached to an LWP.

Each bound thread is bound to an LWP for the lifetime of the thread. This is equivalent to creating a Solaris thread in the THR_BOUND state. You can bind a thread to use special scheduling attributes with Realtime scheduling.

---

Note –

In neither case, bound or unbound, can a thread be directly accessed by or moved to another process.

---

Cancellation

Thread cancellation allows a thread to terminate the execution of any other thread in the process. The target thread (the one being cancelled) can keep cancellation requests pending and can perform application-specific cleanup when it acts upon the cancellation notice.

The pthreads cancellation feature permits either asynchronous or deferred termination of a thread. Asynchronous cancellation can occur at any time; deferred cancellation can occur only at defined points. Deferred cancellation is the default type.

Synchronization

Synchronization allows you to control program flow and access to shared data for concurrently executing threads.

The four synchronization models are mutex locks, read/write locks, condition variables, and semaphores.

• Mutex locks allow only one thread at a time to execute a specific section of code, or to access specific data.

• Read/write locks permit concurrent reads and exclusive writes to a protected shared resource. To modify a resource, a thread must first acquire the exclusive write lock. An exclusive write lock is not permitted until all read locks have been released.

• Condition variables block threads until a particular condition is true.

• Counting semaphores typically coordinate access to resources. The count is the limit on how many threads can have access to a semaphore. When the count is reached, the semaphore blocks.

Using the 64–bit Architecture

For application developers, the major difference between the Solaris 64–bit and 32–bit operating environments is the C–language data type model used. The 64–bit data type uses the LP64 model where longs and pointers are 64–bits wide. All other fundamental data types remain the same as those of the 32–bit implementation. The 32–bit data type uses the ILP32 model where ints, longs, and pointers are 32–bits.

The following summary briefly describes the major features and considerations for using the 64–bit environment:

• Large Virtual Address Space

  In the 64-bit environment, a process can have up to 64 bits of virtual address space, or 18 exabytes. This is 4 billion times the current 4 Gbyte maximum of a 32-bit process. Because of hardware restrictions, however, some platforms might not support the full 64 bits of address space.

  Large address space increases the number of threads that can be created with the default stack size (1 megabyte on 32 bits, 2 megabytes on 64 bits). The number of threads with the default stack size is approximately 2000 threads on a 32–bit system and 8000 billion on a 64–bit system.

• Kernel Memory Readers

  Because the kernel is an LP64 object that uses 64-bit data structures internally, existing 32-bit applications that use libkvm, /dev/mem, or /dev/kmem do not work properly and must be converted to 64-bit programs.

• /proc Restrictions

  A 32-bit program that uses /proc is able to look at 32-bit processes, but is unable to understand a 64-bit process; the existing interfaces and data structures that describe the process are not large enough to contain the 64-bit quantities involved. Such programs must be recompiled as 64-bit programs to work for both 32-bit and 64-bit processes.

• 64–bit Libraries

  32–bit applications are required to link with 32–bit libraries, and 64–bit applications are required to link with 64–bit libraries. With the exception of those libraries that have become obsolete, all of the system libraries are provided in both 32–bit and 64–bit versions. However, no 64–libraries are provided in static form.

• 64–bit Arithmetic

  Though 64–bit arithmetic has long been available in previous 32–bit Solaris releases, the 64–bit implementation now provides full 64–bit machine registers for integer operations and parameter passing.

• Large Files

  If an application requires only large file support, then it can remain 32-bit and use the Large Files interface. It is, however, recommended that the application be converted to 64-bit to take full advantage of 64-bit capabilities.