PTHREADS PROGRAMMING OREILLY PDF
PThreads Programming. 3 reviews. by Bradford Nichols, Dick Buttlar, Jacqueline Farrell. Publisher: O'Reilly Media, Inc. Release Date: September DOWNLOAD PDF . Preface Pthreads Programming Bradford Nichols, Dick Buttlar and Jacqueline Proulx Farrell . Guest login ok, access restrictions apply. ftp> cd /published/oreilly/nutshell/pthreads CWD command successful . ftp>. Pthreads. Bootcamp. Richard K. Wolf. Research Programmer. University of Illinois at Chicago kernel space by the pthreads library. . O'Reilly & Associates.
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like the way the blogger compose this pdf. (Pascale Bernhard). PTHREADS PROGRAMMING: A POSIX STANDARD FOR BETTER MULTIPROCESSING - To . Acknowledgments to the Pthreads Primer. does contrast them to the POSIX API in order to give the POSIX programmer a feeling for what kind XCreateEvent() in an X programming manual), or (b) to open a pipe down which the Java Threads, Scott Oaks and Henry Wong; O'Reilly, 97 ( pages, source on web). This is why we suggest you to always see this resource when you require such book Pthreads Programming: A POSIX Standard For Better Multiprocessing.
Free posix 4 programmers guide Pdf. PThreads Programming. Navigatie aanpassen. Author: Dick Buttlar.. I'm checking on the status of this book in PDF electronic format and will let you know if this. O'Reilly Media Inc.. This document is intended to be a short but useful tutorial on how.
Pthreads Programming - Pthreads Programming:. What are Pthreads? Historically, hardware vendors have implemented their own proprietary versions of.. Start reading. Book Description Computers are just as busy as the rest of us nowadays. Topics include: Basic design techniques Mutexes, conditions, and specialized synchronization techniques Scheduling, priorities, and other real-time issues Cancellation UNIX libraries and re-entrant routines Signals Debugging tips Measuring performance Special considerations for the Distributed Computing Environment DCE.
Why Threads? What Are Pthreads? Multiple Processes Creating a new process: Multiple Threads Creating a new thread: Who Are You? User-space Pthreads implementations Kernel thread—based Pthreads implementations Two-level scheduler Pthreads implementations: Pthreads Draft 4 vs.
We'll cover some smaller topics, such as thread attributes, including the one that governs the persistence of a thread's internal state. When you get to this chapter, we promise that you'll know what this means, and you may even value it! A running theme of this chapter are the various tools that, when combined, allow you to control thread scheduling policies and priorities.
You'll find these discussions especially important if your program includes one or more real-time threads. First, we'll examine the special challenges UNIX signals pose to multithreaded programs; we'll look at the types of signals threads must worry about and how you can direct certain signals to specific threads.
We'll then focus on the requirements the Pthreads library imposes on system calls and libraries to allow them to work correctly when multiple threads from the same process are using them at the same time.
Finally, we'll show you what the UNIX fork and exec calls do to threads. It isn't always pretty.
After we've dealt with the fundamentals of Pthreads programming in the earlier chapters, we turn to the more basic issues you'll face in deploying a multithreaded application in Chapter 6, Practical Considerations. The theme of this chapter is speed. We'll look at those performance concerns over which you have little control—those that are inherent in a given platform's Pthreads implementation.
Here, we'll profile the three major ways implementors design a Pthreads-compliant platform, listing the advantages and drawbacks of each.
We'll move on to a discussion of debugging threads, where we'll illustrate a number of debugging strategies using a thread-capable debugger. Finally, we'll look at various alternatives for improving our program's performance.
We'll run some tests on various versions of our ATM server to test their performance as contention and workload increase. The example programs in this book are available electronically by FTP. A sample session is shown, with what you should type in boldface. Name ftp. You must specify binary transfer for compressed files. It's also used to identify new terms and concepts when they are introduced.
He stuck with us through the long haul, and the book benefits from his attentive reviews, technical expertise, and sheer professionalism on this book beyond measure. Jeff, Greg Nichols, and Bernard Farrell read and commented on early drafts of the book. Thank you all! On the personal side, I'd like to acknowledge my grandmother, Natalie Bunker, for the desire to write a book, my wife Susan for supporting me through the long project, and my friend Paul Silva for modeling the determination needed to complete it.
Each can lay a claim to some flavor and vintage of threads information I filed away somewhere in my head just in case someone asked.
I want to especially thank Connie, my wife, for her love, patience, and permission to skip this year's spring cleanup. Another book for the snow-shovelling season, Brad and Jackie? Finally, love to my kids: Jenn who wants a giraffe on the cover , Maggie a doggie , and Tom a lobster Jackie: "I'd like to thank Bernard, who is not only a superb technical resource but an absolutely wonderful, supportive husband. I'd also like to thank Mark Sanders and Jonathan Swartz for my first introductions to threads concepts.
Thanks also to the whole DECthreads team, and Peter Portante in particular, for helping refine my understanding of the practical matters of programming with Pthreads. Chapter 1: Why Threads? Overview When describing how computers work to someone new to PCs, it's often easiest to haul out the old notion that a program is a very large collection of instructions that are performed from beginning to end. Our notion of a program can include certain eccentricities, like loops and jumps, that make a program more resemble a game of Chutes and Ladders than a piano roll.
If programming instructions were squares on a game board, we can see that our program has places where we stall, squares that we cross again and again, and spots we don't cross at all. But we have one way into our program, regardless of its spins and hops, and one way out. Not too many years ago, single instructions were how we delivered work to computers. Since then, computers have become more and more powerful and grown more efficient at performing the work that makes running our programs possible.
POSIX Threads Programming
Today's computers can do many things at once or very effectively make us believe so. When we package our work according to the traditional, serial notion of a program, we're asking the computer to execute it close to the humble performance of a computer of yesterday. If all of our programs run like this, we're very likely not using our computer to its fullest capabilities. One of those capabilities is a computing system's ability to perform multitasking. Today, it's frequently useful to look at our program our very big task as a collection of subtasks.
For instance, if our program is a marine navigation system, we could launch separate tasks to perform each sounding and maintain other tasks that calculate relative depth, correlate coordinates with depth measurements, and display charts on a screen.
If we can get the computer to execute some of these subtasks at the same time, with no change in our program's results, our overall task will continue to get as much processing as it needs, but it will complete in a shorter period of time.
On some systems, the execution of subtasks will be interleaved on a single processor; on others, they can run in parallel. Either way, we'll see a performance boost. Up until now, when we divided our program into multiple tasks, we had only one way of delivering them to the processor—processes.
Specifically, we started designing programs in which parent processes forked child processes to perform subtasks. In this model, each subtask must exist within its own process. Now, we've been given an alternative that's even more efficient and provides even better performance for our overall program—threads. In the threads model, multiple subtasks exist as individual streams of control within the same process. This part is still referred to as the process.
This part is referred to as a thread. To compare and contrast multitasking between cooperating processes and multitasking using threads, let's first look at how the simple C program in Example can be represented as a process Figure , a process with a single thread Figure , and, finally, as a process with multiple threads Figure Example A Simple C Program simple. Each of these procedure-specific areas is known as a stack frame, and one exists for each procedure in the program that remains active.
As far as the outside observer of the program is concerned, nothing much has changed. As a process with a single thread, this program executes in exactly the same way as it does when modeled as a nonthreaded process.
It is only when we design our program to take advantage of multiple threads in the same process that the thread model really takes off. Figure The simple program as a process with a thread Figure shows our program as it might execute if it were designed to operate in two threads in a single process.
Here, each thread has its own copy of the machine registers. It's certainly very handy for a thread to keep track of the instruction it is currently executing and where in the stack area it should be pushing and popping its procedure-context information.
This allows Thread 1 and Thread 2 to execute at different locations or exactly the same location in the program's text. Each thread can refer to global variables in the same data area. Both threads can refer to the same file descriptors and other resources the system maintains for the process.
Figure The simple program as a process with multiple threads Books24x7. What Are Pthreads?
How do you design a program so that it executes in multiple threads within a process? Well, for starters, you need a thread creation routine and a way of letting the new thread know where in the program it should begin executing.
But at this point, we've passed beyond the ability to generalize. Up to this point, we've discussed the basics of threads and thread creation at a level common to all thread models.
As we move on to discuss specifics as we will in the remainder of this book , we encounter differences among the popular thread packages. For instance, Pthreads specifies a thread's starting point as a procedure name; other thread packages differ in their specification of even this most elementary of concepts.
Pthreads is a standardized model for dividing a program into subtasks whose execution can be interleaved or run in parallel. There have been and still are a number of other threads models—Mach Threads and NT Threads, for example. Programmers experience Pthreads as a defined set of C language programming types and calls with a set of implied semantics.
Vendors usually supply Pthreads implementations in the form of a header file, which you include in your program, and a library, to which you link your program. Potential Parallelism If we return to the simple program in our examples, we see that it has three tasks to complete.
For instance, a program that retrieves blocks of data from a file on disk and then performs computations based on their contents is an eminent candidate for multitasking. When we run the program, it executes each routine serially, always completely finishing the first before starting the second, and completely finishing the second before starting the third. If we take a closer look at the program, we see that the order in which the first two routines execute doesn't affect the third, as long as the third runs after both of them have completed.
This property of a program—that statements can be executed in any order without changing the result—is called potential parallelism. To illustrate parallelism, Figure shows some possible sequences in which the program's routines could be executed.
The first sequence is that of the original program; the second is similar but with the first two routines exchanged. The third shows interleaved execution of the first routines; the last, their simultaneous execution. All sequences produce exactly the same result. Figure Possible sequences of the routines in the simple program An obvious reason for exploiting potential parallelism is to make our program run faster on a multiprocessor.
For example, a word processor could service print requests in one thread and process a user's editing commands in another. Asynchronous events If one or more tasks is subject to the indeterminate occurrence of events of unknown duration and unknown frequency, such as network communications, it may be more efficient to allow other tasks to proceed while the task subject to asynchronous events is in some unknown state of completion.
For example, a network-based server could process in-progress requests in one group of threads while another thread waits for the asynchronous arrival of new requests from clients through network connections. Real -time scheduling If one task is more important than another, but both should make progress whenever possible, you may wish to run them with independent scheduling priorities and policies.
For example, a stock information service application could use high priority threads to receive and update displays of online stock prices and low priority threads to display static data, manage background printing, and perform other less important chores.
Threads are a means to identify and utilize potential parallelism in a program. You can use them in your program design both to enhance its performance and to efficiently structure programs that do more than one thing at a time. Specifying Potential Parallelism in a Concurrent Programming Environment Now that we know the orderings that we desire or would allow in our program, how do we express potential parallelism at the programming level?
Those programming environments that allow us to express potential parallelism are known as concurrent programming environments. A concurrent programming environment lets us designate tasks that can run in parallel.
It also lets us specify how we would like to handle the communication and synchronization issues that result when concurrent tasks attempt to talk to each other and share data. Because most concurrent programming tools and languages have been the result of academic research or have been tailored to a particular vendor's products, they are often inflexible and hard to use.
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Pthreads, on the other hand, is designed to work across multiple vendors' platforms and is built on top of the familiar UNIX C programming interface. Pthreads gives you a simple and portable way of expressing multithreading in your programs. UNIX Concurrent Programming: Multiple Processes Before looking at threads further, let's examine the concurrent programming interface that UNIX already supports: allowing user programs to create multiple processes and providing services the processes can use to communicate with each other.
Example recasts our earlier single-process program as a program in which multiple processes execute its procedures concurrently. The main routine starts ina single process which we will refer to as the parent process. Figure shows a process as it forks.
Here, both parent and child are executing at the point in the program just following the fork call. Interestingly, the child begins executing as if it were returning from the fork call issued by its parent. It can do so because it starts out as a nearly identical copy of its parent. The initial values of all of its variables and the state of its system resources such as file descriptors are the same as those of its parent.
Figure A program before and after a fork If the fork call returns to both the parent and child, why don't the parent and child execute the same instructions following the fork? UNIX programmers specify different code paths for parent and child by examining the return value of the fork call.
The fork call always returns a value of 0 to the child and the child's PID to the parent. Because of this semantic we almost always see fork used as shown in Example Each process executes its own instructions serially, although the way in which the statements of each may be interwoven by concurrency is utterly unpredictable.
In fact, one process could completely finish before the other even starts or resumes, in the case in which the parent is the last to the finish line.
To see what we mean, let's look at the output from some test runs of our program in Example When looking for concurrency, then, why choose multiple threads over multiple processes? The overwhelming reason lies in the single largest benefit of multithreaded programming: threads require less program and system overhead to run than processes do.
The operating system performs less work on behalf of a multithreaded program than it does for a multiprocess program. This translates into a performance gain for the multithreaded program. Pthreads Concurrent Programming: Multiple Threads Now that we've seen how UNIX programmers traditionally add concurrency to a program, let's look at a way of doing so that employs threads.
Example shows how our singleprocess program would look if multiple threads execute its procedures concurrently. The program starts in a single thread, which, for reasons of clarity, we'll refer to as the main thread. For the most part, the operating system does not recognize any thread as being a parent or master thread—from its viewpoint, all threads in a process are equal. In the same way that the processes behave in our multiprocess version of the program, each thread executes independently unless you add explicit synchronization.
Because many of these types like int reveal quite a bit about the underlying architecture of a given platform such as whether its addresses are 16, 32, or 64 bits long , POSIX prefers to create new data types that conceal these fundamental differences. A thread attribute object specifies various characteristics for the new thread.
In the example program, we pass a value of NULL for this argument, indicating that we accept the default characteristics for the new thread. A zero value represents success, and a nonzero value indicates and identifies an error. In later examples, we redeclare the routine to the correct prototype where possible. Threads are peers In the multiprocess version of our example Example , we could refer to the caller of fork as the parent process and the process it creates as the child process.
We could do so because UNIX process management recognizes a special relationship between the two. It is this relationship that, for instance, allows a parent to issue a wait system call to implicitly wait for one of its children.
The Pthreads concurrent programming environment maintains no such special relationship between threads.But threads can synchronize by simply monitoring a variable—in other words, staying within the user address space of the program. Note that we do not use the term signals in the sense used in discussions of UNIX signaling mechanisms. An event can be something as simple as a counter's reaching a particular value or a flag being set or cleared; it may be something more complex, involving a specific coincidence of multiple events.
Finally, love to my kids: Whichever thread is the last to do so will succeed in inserting its node on the list; the other This document is be created with occupying trial version of CHM2PDF 2. Server programs—such as those written for database managers, file servers, or print servers—are ideal applications for threading. By the end of the chapter, we will have added synchronization to our ATM server example and presented most of what you'll need to know to write a working multithreaded program.
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