There are several contributing factors: Erlang processes are not OS processes. They are implemented by the Erlang VM using a lightweight cooperative threading model (preemptive at the Erlang level, but under the control of a cooperatively scheduled runtime). This means that it is much cheaper to switch context, because they only switch at known, controlled … Read more
A lock occurs when multiple processes try to access the same resource at the same time. One process loses out and must wait for the other to finish. A deadlock occurs when the waiting process is still holding on to another resource that the first needs before it can finish. So, an example: Resource A … Read more
I have the choice in between either having a bunch of mutexes or a single one for an object. If you have many threads and the access to the object happens often, then multiple locks would increase parallelism. At the cost of maintainability, since more locking means more debugging of the locking. How efficient is … Read more
The difference between a recursive and non-recursive mutex has to do with ownership. In the case of a recursive mutex, the kernel has to keep track of the thread who actually obtained the mutex the first time around so that it can detect the difference between recursion vs. a different thread that should block instead. … Read more
Generally, the backtrace is used to get the stack of the current thread, but if there is a necessity to get the stack trace of all the threads, use the following command. thread apply all bt
In the most simple terms, threads are generally considered to be preemptive (although this may not always be true, depending on the operating system) while fibers are considered to be light-weight, cooperative threads. Both are separate execution paths for your application. With threads: the current execution path may be interrupted or preempted at any time … Read more
Well it depends on how you define concurrency. In server-side software, concurrency and parallelism are often considered as different concepts. In a server, supporting concurrent I/Os means the server is able to serve several clients by executing several flows corresponding to those clients with only one computation unit. In this context, parallelism would mean the … Read more
Ok, so having watched a little of the node.js presentation that @gawi pointed me at, I can say a bit more about how Haskell compares to node.js. In the presentation, Ryan describes some of the benefits of Green Threads, but then goes on to say that he doesn’t find the lack of a thread abstraction … Read more
A Monitor is an object designed to be accessed from multiple threads. The member functions or methods of a monitor object will enforce mutual exclusion, so only one thread may be performing any action on the object at a given time. If one thread is currently executing a member function of the object then any … Read more
Concurrent and parallel are effectively the same principle as you correctly surmise, both are related to tasks being executed simultaneously although I would say that parallel tasks should be truly multitasking, executed “at the same time” whereas concurrent could mean that the tasks are sharing the execution thread while still appearing to be executing in … Read more