Thread (computer science)
Many Nextel ringtones programming languages, Abbey Diaz operating systems, and other Free ringtones software development environments support what are called "'''threads'''" of Majo Mills execution (computers)/execution. Threads are similar to Mosquito ringtone computer process/processes, in that both represent a single Sabrina Martins sequence of Nextel ringtones instructions executed in parallel with other sequences, either by Abbey Diaz Computer multitasking/time slicing or Free ringtones multiprocessing. Threads are a way for a Majo Mills computer program/program to split itself into two or more simultaneously running Cingular Ringtones tasks. (The name "thread" is by analogy with the way that a number of approved pinnacle yarn/threads are interwoven to make a piece of fabric).
A common use of threads is having one thread paying attention to the has decried graphical user interface, while others do a long calculation not function Background (computer software)/in the background.
As a result, the election his application more readily responds to user's interaction.
An unrelated use of the term '''thread''' is for eyes toward threaded code, which is a form of code consisting entirely of are accelerating subroutine calls, written without the subroutine call instruction, and processed by an weary hearing interpreter (computing)/interpreter or the banner issue CPU. Two threaded code languages are said pacheco Forth programming language/Forth and early angles violate B programming languages.
Threads compared with processes
Threads are distinguished from traditional multi-tasking decadence set computer process/operating system processes in that processes are typically independent, carry considerable familiar argument state information, have separate better objection address spaces, and interact only through system-provided favoritism was inter-process communication mechanisms. Multiple threads, on the other hand, typically share the state information of a single process, share her drink Computer storage/memory and other of urban resource (computer science)/resources directly. Context switching between threads in the same process is typically faster than context switching between processes. Systems like merriment the Windows NT and buyer a OS/2 are said to have "cheap" threads and "expensive" processes, while in other operating systems there is not so big a difference.
An advantage of a multi-threaded program is that it can operate faster on ambivalent role computer systems that have multiple through english Central processing unit/CPUs, or across a computer cluster/cluster of machines. This is because the threads of the program naturally lend themselves for truly concurrent programming/concurrent execution (computers)/execution. In such a case, the programmer needs to be careful to avoid race conditions, and other non-intuitive behaviors. In order for data to be correctly manipulated, threads will often need to rendezvous in time in order to process the data in the correct order. Threads may also require atomic (computer science)/atomic operations (often implemented using semaphore (programming)/semaphores) in order to prevent common data from being simultaneously modified, or read while in the process of being modified. Careless use of such primitive (computer science)/primitives can lead to deadlocks.
Use of threads in programming often causes a state inconsistency. A common anti-pattern is to set a global variable, then invoke subprograms that depend on its value. This is known as accumulate and fire.
Operating systems generally implement threads in one of two ways: Pre-emptive multitasking/preemptive multithreading, or Co-operative multitasking/cooperative multithreading. Preemptive multithreading is generally considered the superior implementation, as it allows the operating system to determine when a context switch should occur. Cooperative multithreading, on the other hand, relies on the threads themselves to relinquish control once they are at a stopping point. This can create problems if a thread is waiting for a resource to become available. The disadvantage to preemptive multithreading is that the system may make a context switch at an inappropriate time, causing priority inversion or other bad effects which may be avoided by cooperative multithreading.
Traditional mainstream computing hardware did not have much support for multithreading as switching between threads was generally already quicker than full process context switches. Processors in embedded systems, which have higher requirements for real-time behaviors, might support multithreading by decreasing the thread switch time, perhaps by allocating a dedicated register file for each thread instead of saving/restoring a common register file. In the late 1990s, the idea of executing instructions from multiple threads simultaneously has become known as simultaneous multithreading. This feature was introduced in Intel's Pentium 4 processor, with the name ''Hyper-threading''.
Processes, threads, and fibers
The concept of a ''process'', ''thread'', and ''fiber'' are interrelated by a sense of "ownership" and of containment.
A ''process'' is the "heaviest" unit of kernel scheduling. Processes own resources allocated by the operating system. Resources include memory, file handles, sockets, device handles, and windows. Processes do not share address spaces or file resources except through explicit methods such as inheriting file handles or shared memory segments, or mapping the same file in a shared way. Processes are typically pre-emptively multitasked. However, Windows 3.1 and older versions of Mac OS used co-operative or non-preemptive multitasking.
A ''thread'' is the "lightest" unit of kernel scheduling. At least one thread exists within each process. If multiple threads can exist within a process, then they share the same memory and file resources. Threads are pre-emptively multitasked if the operating system's process scheduler is pre-emptive. Threads do not own resources except for a stack and a copy of registers including the program counter.
In some situations, there is a distinction between "kernel threads" and "user threads" the former are managed and scheduled by the kernel, whereas the latter are managed and scheduled by thread tools and scheduling in userspace. In this article, the term "thread" is used to refer to kernel threads, whereas "fiber" is used to refer to user threads.
A ''fiber'', also known as a coroutine, is a user-level thread. Fibers are co-operative multitasking/co-operatively scheduled: a running fiber must explicitly "yield" to allow another fiber to run. A fiber can be scheduled to run in any thread in the same process.
= Thread and fiber issues =
Typically fibers are implemented entirely in userspace. As a result, context switching between fibers in a process is extremely efficient: because the kernel is oblivious to the existence of fibers, a context switch does not require a system call. Instead, a context switch can be performed by saving the CPU registers used by the currently executing fiber, and loading the registers required by the fiber to be executed. Since scheduling occurs in userspace, specific scheduling mechanisms can be tailored for a certain task, by the userlevel program.
However, the use of blocking system calls (such as are commonly used to implement synchronous I/O) in fibers can be problematic. If a fiber performs a system call that blocks (perhaps to wait for an I/O operation to complete), the other fibers in the process are unable to run until the system call returns.
A common solution to this problem is providing an I/O API that implements a synchronous interface by using non-blocking I/O internally, and scheduling another fiber while the I/O operation is in progress. Win32 supplies a fiber API. SunOS 4.x implemented "light-weight processes" or LWPs as fibers known as "green threads". SunOS 5.x and later, NetBSD 2.x, and DragonFly BSD implement LWPs as threads as well.
Alternatively, a system call such as select under Unix and Unix-like operating systems can be used to check whether certain system calls will block, but this adds complexity to the runtime system.
The use of kernel threads brings simplicity; the program doesn't need to know how to manage threads, as the kernel handles all aspects of thread management. There are no blocking issues since if a thread blocks, the kernel can reschedule another thread from within the process or from another, nor are extra system calls needed.
However, there are obvious issues with managing threads through the kernel, since on creation and removal, a context switch between kernel and usermode needs to occur, so programs that rely on using a lot of threads for short periods may suffer performance hits.
Hybrid schemes are available which gains a tradeoff between the two.
=Relationships between processes, threads, and fibers=
The operating system creates a process for the purpose of running a program. Every process has at least one thread. On some operating systems, processes can have more than one thread. A thread can use fibers to implement cooperative multitasking to divide the thread's CPU time for multiple tasks. Generally, this is not done because threads are cheap, easy, and well implemented in modern operating systems.
Processes are used to run an instance of a program. Some programs like word processors are designed to have only one instance of themselves running at the same time. Sometimes, such programs just open up more windows to accommodate multiple simultaneous use. After all, you can go back and forth between five documents, but you can edit one of them at a given instance.
Other programs like operating system shell/command shells maintain a state that you want to keep separate. Each time you open a command shell in Windows, the operating system creates a process for that shell window. The shell windows do not affect each other. Some operating systems support multiple users being logged in simultaneously. It is typical for dozens or even hundreds of people to be logged into some Unix systems. Other than the sluggishness of the computer, the individual users are (usually) blissfully unaware of each other. If Bob runs a program, the operating system creates a process for it. If Alice then runs the same program, the operating system creates another process to run Alice's instance of that program. So if Bob's instance of the program crashes, Alice's instance does not. In this way, processes protect users from failures being experienced by other users.
However, there are times when a single process, instance of a program, needs to do multiple things asynchronously. The quintessential example is a program with a graphical user interface (GUI). The program must repaint its GUI and respond to user interaction even if it is currently spell-checking a document or playing a song. For situations like these, threads are used.
Threads allow a program to do multiple things concurrently. Since the threads a program spawns share the same address space, one thread can modify data that is used by another thread. This is both a good and a bad thing. It is good because it facilitates easy communication between threads. It can be bad because a poorly written program may cause one thread to inadvertently overwrite another data being used by another thread. The sharing of a single address space between multiple threads is one of the reasons that multithreaded programming is usually considered to be more difficult and error-prone that programming a single-threaded application.
There are other potential problems as well such as deadlocks, livelocks, and race conditions. However, all of these problems are concurrency issues and as such affect multi-process and multi-fiber models as well.
Threads are also used by web servers. When a user visits a web site, a web server will use a thread to serve the page to that user. If another user visits the site while the previous user is still being served, the web server can serve the second visitor by using a different thread. Thus, the second user does not have to wait for the first visitor to be served. This is very important because not all users have the same speed Internet connection. A slow user should not delay all other visitors from downloading a web page. For better performance, threads used by web servers and other Internet services are typically pooled and reused to eliminate even the small overhead associated with creating a thread.
Fibers were popular before threads were implemented by the kernels of operating systems. Historically, fibers can be thought of as a trial run at implementing the functionality of threads. There is little point in using fibers today because threads can do everything that fibers can do and threads are implemented well in modern operating systems.
Implementations
There are many different and incompatible implementations of threading. These can either be kernel-level or user-level implementations. For example, the Linux kernel does not treat threads differently from processes, but the C library implements threading and emulates it using processes. (NB: Linux has CoW fork(), so this is efficient.)
= Kernel-level =
* LWKT in various BSDs.
* M:N threading ?? (in BSDs)
= User-level =
* NPTL Native Posix Threading Library for Linux from Red Hat. (What makes it "native"? Buzzword?)
* Pthread ??
* Java threads Java emulates threading for multi-threaded applications
* Python threads Similar to Java's approach (??)
Comparison between models
The spin lock article includes a C programming language/C program using two threads that communicate through a global integer.
See also
*List of multi-threading libraries
*clone (function)/clone()
*Communicating sequential processes
*completion port
*fork (computing)/fork()
*Hyperthreading™
*Lock-free and wait-free algorithms
*Message passing
*priority inversion
*synchronization
*Thread-safety/Thread safety
*Threading model
*worker
*SEDA
References
*David R. Butenhof: ''Programming with POSIX Threads'', Addison-Wesley, ISBN 0-201-63392-2
*Bradford Nichols, Dick Buttlar, Jacqueline Proulx Farell: ''Pthreads Programming'', O'Reilly & Associates, ISBN 1-56592-115-1
*Charles J. Northrup: ''Programming with UNIX Threads'', John Wiley & Sons, ISBN 0-471-13751-0
*Mark Walmsley: ''Multi-Threaded Programming in C++'', Springer, ISBN 1-85233-146-1
*Paul Hyde: ''Java Thread Programming'', Sams, ISBN 0-672-31585-8
*Bill Lewis: ''Threads Primer: A Guide to Multithreaded Programming'', Prentice Hall, ISBN 0-1-3443698-9
*Steve Kleiman, Devang Shah, Bart Smaalders: ''Programming With Threads'', SunSoft Press, ISBN 0-13-172389-8
*Pat Villani: ''Advanced WIN32 Programming: Files, Threads, and Process Synchronization'', Harpercollins Publishers, ISBN 0-87930-563-0
*Jim Beveridge, Robert Wiener: ''Multithreading Applications in Win32'', Addison-Wesley, ISBN 0-201-44234-5
*Thuan Q. Pham, Pankaj K. Garg: ''Multithreaded Programming with Windows NT'', Prentice Hall, ISBN 0-131-20643-5
*Len Dorfman, Marc J. Neuberger: ''Effective Multithreading in OS/2'', McGraw-Hill Osborne Media, ISBN 0070178410
*Alan Burns, Andy Wellings: ''Concurrency in ADA'', Cambridge University Press, ISBN 0-521-62911-X
*Uresh Vahalia: ''Unix Internals: the New Frontiers'', Prentice Hall, ISBN 0-13-101908-2
External links
*http://www.realworldtech.com/page.cfm?ArticleID=RWT122600000000 - Explaining different types of multithreading, hardware implementation requirements and the impact on software.
*http://arstechnica.com/paedia/h/hyperthreading/hyperthreading-1.html
*http://www.ece.utexas.edu/~valvano/EE345M/view04.pdf & http://www.ece.utexas.edu/~valvano/EE345M/view05.pdf, a preemptive multithreaded implementation described
*[news:comp.programming.threads Forum]
*http://www.serpentine.com/~bos/threads-faq/
*http://lambdacs.com/cpt/FAQ.html, http://lambdacs.com/cpt/MFAQ.html
*http://groups.google.com/groups?group=comp.programming.threads&threadm=580fae16.0312210310.1410bf2b%40posting.google.com
*http://www.kegel.com/c10k.html
*http://www.jetbyte.com/portfolio-showarticle.asp?articleId=38&catId=1&subcatId=2
*http://www.cs.rice.edu/CS/Systems/ScalaServer/
*http://citeseer.nj.nec.com/larus02using.html
*Article "http://www.niccolai.ws/works/articoli/art-multithreading-en-1a.html" by Giancarlo Niccolai
*Article "http://gotw.ca/publications/concurrency-ddj.htm" by Herb Sutter
*http://web.mit.edu/nathanw/www/usenix/
*http://www.dragonflybsd.org/goals/threads.cgi
*http://java.sun.com/docs/hotspot/threads/threads.html
de:Thread
es:Hilo (informática)
fr:Processus léger
ko:스레드
ja:スレッド (コンピュータプログラミング)
pl:Wątek (informatyka)
ru:Многопоточность
sv:Tråd (dator)
zh:线程
Tag: Computer terminology
A common use of threads is having one thread paying attention to the has decried graphical user interface, while others do a long calculation not function Background (computer software)/in the background.
As a result, the election his application more readily responds to user's interaction.
An unrelated use of the term '''thread''' is for eyes toward threaded code, which is a form of code consisting entirely of are accelerating subroutine calls, written without the subroutine call instruction, and processed by an weary hearing interpreter (computing)/interpreter or the banner issue CPU. Two threaded code languages are said pacheco Forth programming language/Forth and early angles violate B programming languages.
Threads compared with processes
Threads are distinguished from traditional multi-tasking decadence set computer process/operating system processes in that processes are typically independent, carry considerable familiar argument state information, have separate better objection address spaces, and interact only through system-provided favoritism was inter-process communication mechanisms. Multiple threads, on the other hand, typically share the state information of a single process, share her drink Computer storage/memory and other of urban resource (computer science)/resources directly. Context switching between threads in the same process is typically faster than context switching between processes. Systems like merriment the Windows NT and buyer a OS/2 are said to have "cheap" threads and "expensive" processes, while in other operating systems there is not so big a difference.
An advantage of a multi-threaded program is that it can operate faster on ambivalent role computer systems that have multiple through english Central processing unit/CPUs, or across a computer cluster/cluster of machines. This is because the threads of the program naturally lend themselves for truly concurrent programming/concurrent execution (computers)/execution. In such a case, the programmer needs to be careful to avoid race conditions, and other non-intuitive behaviors. In order for data to be correctly manipulated, threads will often need to rendezvous in time in order to process the data in the correct order. Threads may also require atomic (computer science)/atomic operations (often implemented using semaphore (programming)/semaphores) in order to prevent common data from being simultaneously modified, or read while in the process of being modified. Careless use of such primitive (computer science)/primitives can lead to deadlocks.
Use of threads in programming often causes a state inconsistency. A common anti-pattern is to set a global variable, then invoke subprograms that depend on its value. This is known as accumulate and fire.
Operating systems generally implement threads in one of two ways: Pre-emptive multitasking/preemptive multithreading, or Co-operative multitasking/cooperative multithreading. Preemptive multithreading is generally considered the superior implementation, as it allows the operating system to determine when a context switch should occur. Cooperative multithreading, on the other hand, relies on the threads themselves to relinquish control once they are at a stopping point. This can create problems if a thread is waiting for a resource to become available. The disadvantage to preemptive multithreading is that the system may make a context switch at an inappropriate time, causing priority inversion or other bad effects which may be avoided by cooperative multithreading.
Traditional mainstream computing hardware did not have much support for multithreading as switching between threads was generally already quicker than full process context switches. Processors in embedded systems, which have higher requirements for real-time behaviors, might support multithreading by decreasing the thread switch time, perhaps by allocating a dedicated register file for each thread instead of saving/restoring a common register file. In the late 1990s, the idea of executing instructions from multiple threads simultaneously has become known as simultaneous multithreading. This feature was introduced in Intel's Pentium 4 processor, with the name ''Hyper-threading''.
Processes, threads, and fibers
The concept of a ''process'', ''thread'', and ''fiber'' are interrelated by a sense of "ownership" and of containment.
A ''process'' is the "heaviest" unit of kernel scheduling. Processes own resources allocated by the operating system. Resources include memory, file handles, sockets, device handles, and windows. Processes do not share address spaces or file resources except through explicit methods such as inheriting file handles or shared memory segments, or mapping the same file in a shared way. Processes are typically pre-emptively multitasked. However, Windows 3.1 and older versions of Mac OS used co-operative or non-preemptive multitasking.
A ''thread'' is the "lightest" unit of kernel scheduling. At least one thread exists within each process. If multiple threads can exist within a process, then they share the same memory and file resources. Threads are pre-emptively multitasked if the operating system's process scheduler is pre-emptive. Threads do not own resources except for a stack and a copy of registers including the program counter.
In some situations, there is a distinction between "kernel threads" and "user threads" the former are managed and scheduled by the kernel, whereas the latter are managed and scheduled by thread tools and scheduling in userspace. In this article, the term "thread" is used to refer to kernel threads, whereas "fiber" is used to refer to user threads.
A ''fiber'', also known as a coroutine, is a user-level thread. Fibers are co-operative multitasking/co-operatively scheduled: a running fiber must explicitly "yield" to allow another fiber to run. A fiber can be scheduled to run in any thread in the same process.
= Thread and fiber issues =
Typically fibers are implemented entirely in userspace. As a result, context switching between fibers in a process is extremely efficient: because the kernel is oblivious to the existence of fibers, a context switch does not require a system call. Instead, a context switch can be performed by saving the CPU registers used by the currently executing fiber, and loading the registers required by the fiber to be executed. Since scheduling occurs in userspace, specific scheduling mechanisms can be tailored for a certain task, by the userlevel program.
However, the use of blocking system calls (such as are commonly used to implement synchronous I/O) in fibers can be problematic. If a fiber performs a system call that blocks (perhaps to wait for an I/O operation to complete), the other fibers in the process are unable to run until the system call returns.
A common solution to this problem is providing an I/O API that implements a synchronous interface by using non-blocking I/O internally, and scheduling another fiber while the I/O operation is in progress. Win32 supplies a fiber API. SunOS 4.x implemented "light-weight processes" or LWPs as fibers known as "green threads". SunOS 5.x and later, NetBSD 2.x, and DragonFly BSD implement LWPs as threads as well.
Alternatively, a system call such as select under Unix and Unix-like operating systems can be used to check whether certain system calls will block, but this adds complexity to the runtime system.
The use of kernel threads brings simplicity; the program doesn't need to know how to manage threads, as the kernel handles all aspects of thread management. There are no blocking issues since if a thread blocks, the kernel can reschedule another thread from within the process or from another, nor are extra system calls needed.
However, there are obvious issues with managing threads through the kernel, since on creation and removal, a context switch between kernel and usermode needs to occur, so programs that rely on using a lot of threads for short periods may suffer performance hits.
Hybrid schemes are available which gains a tradeoff between the two.
=Relationships between processes, threads, and fibers=
The operating system creates a process for the purpose of running a program. Every process has at least one thread. On some operating systems, processes can have more than one thread. A thread can use fibers to implement cooperative multitasking to divide the thread's CPU time for multiple tasks. Generally, this is not done because threads are cheap, easy, and well implemented in modern operating systems.
Processes are used to run an instance of a program. Some programs like word processors are designed to have only one instance of themselves running at the same time. Sometimes, such programs just open up more windows to accommodate multiple simultaneous use. After all, you can go back and forth between five documents, but you can edit one of them at a given instance.
Other programs like operating system shell/command shells maintain a state that you want to keep separate. Each time you open a command shell in Windows, the operating system creates a process for that shell window. The shell windows do not affect each other. Some operating systems support multiple users being logged in simultaneously. It is typical for dozens or even hundreds of people to be logged into some Unix systems. Other than the sluggishness of the computer, the individual users are (usually) blissfully unaware of each other. If Bob runs a program, the operating system creates a process for it. If Alice then runs the same program, the operating system creates another process to run Alice's instance of that program. So if Bob's instance of the program crashes, Alice's instance does not. In this way, processes protect users from failures being experienced by other users.
However, there are times when a single process, instance of a program, needs to do multiple things asynchronously. The quintessential example is a program with a graphical user interface (GUI). The program must repaint its GUI and respond to user interaction even if it is currently spell-checking a document or playing a song. For situations like these, threads are used.
Threads allow a program to do multiple things concurrently. Since the threads a program spawns share the same address space, one thread can modify data that is used by another thread. This is both a good and a bad thing. It is good because it facilitates easy communication between threads. It can be bad because a poorly written program may cause one thread to inadvertently overwrite another data being used by another thread. The sharing of a single address space between multiple threads is one of the reasons that multithreaded programming is usually considered to be more difficult and error-prone that programming a single-threaded application.
There are other potential problems as well such as deadlocks, livelocks, and race conditions. However, all of these problems are concurrency issues and as such affect multi-process and multi-fiber models as well.
Threads are also used by web servers. When a user visits a web site, a web server will use a thread to serve the page to that user. If another user visits the site while the previous user is still being served, the web server can serve the second visitor by using a different thread. Thus, the second user does not have to wait for the first visitor to be served. This is very important because not all users have the same speed Internet connection. A slow user should not delay all other visitors from downloading a web page. For better performance, threads used by web servers and other Internet services are typically pooled and reused to eliminate even the small overhead associated with creating a thread.
Fibers were popular before threads were implemented by the kernels of operating systems. Historically, fibers can be thought of as a trial run at implementing the functionality of threads. There is little point in using fibers today because threads can do everything that fibers can do and threads are implemented well in modern operating systems.
Implementations
There are many different and incompatible implementations of threading. These can either be kernel-level or user-level implementations. For example, the Linux kernel does not treat threads differently from processes, but the C library implements threading and emulates it using processes. (NB: Linux has CoW fork(), so this is efficient.)
= Kernel-level =
* LWKT in various BSDs.
* M:N threading ?? (in BSDs)
= User-level =
* NPTL Native Posix Threading Library for Linux from Red Hat. (What makes it "native"? Buzzword?)
* Pthread ??
* Java threads Java emulates threading for multi-threaded applications
* Python threads Similar to Java's approach (??)
Comparison between models
The spin lock article includes a C programming language/C program using two threads that communicate through a global integer.
See also
*List of multi-threading libraries
*clone (function)/clone()
*Communicating sequential processes
*completion port
*fork (computing)/fork()
*Hyperthreading™
*Lock-free and wait-free algorithms
*Message passing
*priority inversion
*synchronization
*Thread-safety/Thread safety
*Threading model
*worker
*SEDA
References
*David R. Butenhof: ''Programming with POSIX Threads'', Addison-Wesley, ISBN 0-201-63392-2
*Bradford Nichols, Dick Buttlar, Jacqueline Proulx Farell: ''Pthreads Programming'', O'Reilly & Associates, ISBN 1-56592-115-1
*Charles J. Northrup: ''Programming with UNIX Threads'', John Wiley & Sons, ISBN 0-471-13751-0
*Mark Walmsley: ''Multi-Threaded Programming in C++'', Springer, ISBN 1-85233-146-1
*Paul Hyde: ''Java Thread Programming'', Sams, ISBN 0-672-31585-8
*Bill Lewis: ''Threads Primer: A Guide to Multithreaded Programming'', Prentice Hall, ISBN 0-1-3443698-9
*Steve Kleiman, Devang Shah, Bart Smaalders: ''Programming With Threads'', SunSoft Press, ISBN 0-13-172389-8
*Pat Villani: ''Advanced WIN32 Programming: Files, Threads, and Process Synchronization'', Harpercollins Publishers, ISBN 0-87930-563-0
*Jim Beveridge, Robert Wiener: ''Multithreading Applications in Win32'', Addison-Wesley, ISBN 0-201-44234-5
*Thuan Q. Pham, Pankaj K. Garg: ''Multithreaded Programming with Windows NT'', Prentice Hall, ISBN 0-131-20643-5
*Len Dorfman, Marc J. Neuberger: ''Effective Multithreading in OS/2'', McGraw-Hill Osborne Media, ISBN 0070178410
*Alan Burns, Andy Wellings: ''Concurrency in ADA'', Cambridge University Press, ISBN 0-521-62911-X
*Uresh Vahalia: ''Unix Internals: the New Frontiers'', Prentice Hall, ISBN 0-13-101908-2
External links
*http://www.realworldtech.com/page.cfm?ArticleID=RWT122600000000 - Explaining different types of multithreading, hardware implementation requirements and the impact on software.
*http://arstechnica.com/paedia/h/hyperthreading/hyperthreading-1.html
*http://www.ece.utexas.edu/~valvano/EE345M/view04.pdf & http://www.ece.utexas.edu/~valvano/EE345M/view05.pdf, a preemptive multithreaded implementation described
*[news:comp.programming.threads Forum]
*http://www.serpentine.com/~bos/threads-faq/
*http://lambdacs.com/cpt/FAQ.html, http://lambdacs.com/cpt/MFAQ.html
*http://groups.google.com/groups?group=comp.programming.threads&threadm=580fae16.0312210310.1410bf2b%40posting.google.com
*http://www.kegel.com/c10k.html
*http://www.jetbyte.com/portfolio-showarticle.asp?articleId=38&catId=1&subcatId=2
*http://www.cs.rice.edu/CS/Systems/ScalaServer/
*http://citeseer.nj.nec.com/larus02using.html
*Article "http://www.niccolai.ws/works/articoli/art-multithreading-en-1a.html" by Giancarlo Niccolai
*Article "http://gotw.ca/publications/concurrency-ddj.htm" by Herb Sutter
*http://web.mit.edu/nathanw/www/usenix/
*http://www.dragonflybsd.org/goals/threads.cgi
*http://java.sun.com/docs/hotspot/threads/threads.html
de:Thread
es:Hilo (informática)
fr:Processus léger
ko:스레드
ja:スレッド (コンピュータプログラミング)
pl:Wątek (informatyka)
ru:Многопоточность
sv:Tråd (dator)
zh:线程
Tag: Computer terminology
posted @ 5:37 PM
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