在我最近的LINUX工作中，需要注意的一件事是库。如果您正在使用线程，请确保跨线程使用的所有库都是线程安全的。这让我疼了好几次。值得注意的是，libxml2并不是开箱即用的线程安全的。它可以用线程安全编译，但这不是你用aptitude install得到的。

更复杂的是，还有线程本地存储和Unix共享内存。

Thread-local storage allows each thread to have a separate instance of global objects. The only time I've used it was when constructing an emulation environment on linux/windows, for application code that ran in an RTOS. In the RTOS each task was a process with it's own address space, in the emulation environment, each task was a thread (with a shared address space). By using TLS for things like singletons, we were able to have a separate instance for each thread, just like under the 'real' RTOS environment.

共享内存(显然)可以为您带来让多个进程访问相同内存的性能优势，但代价是必须正确地同步进程。一种方法是让一个进程在共享内存中创建一个数据结构，然后通过传统的进程间通信(如命名管道)向该结构发送句柄。

I think everyone has done a great job responding to your question. I'm just adding more information about thread versus process in Linux to clarify and summarize some of the previous responses in context of kernel. So, my response is in regarding to kernel specific code in Linux. According to Linux Kernel documentation, there is no clear distinction between thread versus process except thread uses shared virtual address space unlike process. Also note, the Linux Kernel uses the term "task" to refer to process and thread in general.

没有实现进程或线程的内部结构，而是有一个结构体task_struct，它描述了一个称为task的抽象调度单元。

另外，根据Linus Torvalds的说法，你根本不应该考虑进程和线程，因为这太有限了，唯一的区别是COE或执行上下文在“从父地址空间分离”或共享地址空间方面的区别。事实上，他在这里用了一个web服务器的例子来说明他的观点(强烈推荐阅读)。

完全归功于linux内核文档

其他人讨论了这些考虑因素。

也许重要的区别是，在Windows中，与线程相比，进程是沉重和昂贵的，而在Linux中，差异要小得多，所以等式在不同的点上平衡。

多线程是为受虐狂准备的。：）

If you are concerned about an environment where you are constantly creating threads/forks, perhaps like a web server handling requests, you can pre-fork processes, hundreds if necessary. Since they are Copy on Write and use the same memory until a write occurs, it's very fast. They can all block, listening on the same socket and the first one to accept an incoming TCP connection gets to run with it. With g++ you can also assign functions and variables to be closely placed in memory (hot segments) to ensure when you do write to memory, and cause an entire page to be copied at least subsequent write activity will occur on the same page. You really have to use a profiler to verify that kind of stuff but if you are concerned about performance, you should be doing that anyway.

Development time of threaded apps is 3x to 10x times longer due to the subtle interaction on shared objects, threading "gotchas" you didn't think of, and very hard to debug because you cannot reproduce thread interaction problems at will. You may have to do all sort of performance killing checks like having invariants in all your classes that are checked before and after every function and you halt the process and load the debugger if something isn't right. Most often it's embarrassing crashes that occur during production and you have to pore through a core dump trying to figure out which threads did what. Frankly, it's not worth the headache when forking processes is just as fast and implicitly thread safe unless you explicitly share something. At least with explicit sharing you know exactly where to look if a threading style problem occurs.

如果性能如此重要，那就增加另一台计算机和负载平衡。对于开发人员调试一个多线程应用程序的成本，即使是由一个有经验的多线程程序编写的应用程序，你可能会买4块40核的英特尔主板，每块都有64g内存。

That being said, there are asymmetric cases where parallel processing isn't appropriate, like, you want a foreground thread to accept user input and show button presses immediately, without waiting for some clunky back end GUI to keep up. Sexy use of threads where multiprocessing isn't geometrically appropriate. Many things like that just variables or pointers. They aren't "handles" that can be shared in a fork. You have to use threads. Even if you did fork, you'd be sharing the same resource and subject to threading style issues.

你的任务有多紧密耦合?

如果它们可以彼此独立，那么就使用流程。如果它们相互依赖，则使用线程。这样，您就可以终止并重新启动坏进程，而不会影响其他任务的操作。