Why does a multi-threaded process using a user level thread library get blocked when one of its threads waits for an I/O? This makes sense, but when I think more, a question pops up. Can the user level thread library not schedule another thread?
OS can schedule only the processes(or jobs) , it in no way knows about the threads within a program and cannot schedule them as it wants.
when a part of the process ( here the thread which got blocked due to i/o) gets blocked for i/o operation, the os suspends the entire process , since the os deals only with the processes (not threads within the process).
As in the many to one model , there is only a single kernel , the process whose thread was blocked cant be executed until the blocked thread resumes.
whereas in a many to many or one to one model, each kernel runs its piece of code and is unaware of the threads blocked in the other kernels.
There's two types of thread. OS threads, and green threads (which is what I think you're talking about).
OS threads are scheduled by the operating system, and one will not block another (at least not on any OS you're likely to come across these days) unless you deliberately introduce something to synchronise them (e.g. Semaphores).
Green threads, where a process schedules different paths of execution for itself, will block unless the scheduler is clever enough provide (and therefore catch) all potentially blocking function calls and use them as a scheduling opportunity. This is also closely related to cooperative multitasking.
So the answer is yes, but only if written that way. Threads in Python famously were not written this way, read up on the GIL, and so would cause no end of problems. Python may have fixed this now.
Related
I'm learning about threads and processes in an Operating Systems course, and I've come across an apparent contradiction in my textbook (Modern Operating Systems, 4th Ed. by Tanenbaum and Bos). I'm sure there's a something I'm misinterpreting here, it'd be great if someone could clear things up.
On page 106:
Another common thread call is thread_yield, which allows a thread to voluntarily give up the CPU to let another thread run. Such a call is important because there is no clock interrupt to actually enforce multiprogramming as there is with processes
Ok fine - so how I interpret that is that threads will never give up control unless they willingly cede it. Makes sense.
Then on page 116, in an example of threads mishandling shared information:
As an example, consider the errno variable maintained by UNIX. When a process (or a thread) makes a system call that fails, the error code is put into errno. In Fig. 2-19, thread 1 executes the system call access to find out if it has permission to access a certain file. The operating system returns the answer in the global variable errno. After control has returned to thread 1, but before it has a chance to read errno, the scheduler decides that thread 1 has had enough CPU time for the moment and decides to switch to thread 2.
But didn't thread 1 just get pulled from the CPU involuntarily? I thought there was no way to enforce thread switching as there is with process switching?
This makes sense if we're going about process-level threads instead of OS-level threads. The CPU can interrupt a process (regardless of what thread is running), but because the OS is not aware of process-level threads, it cannot interrupt them. If one thread inside the process wants to allow another thread to run, it has to specifically yield to the other thread.
However, most languages these days use OS-level threads, which the OS does know about and can pre-empt.
The confusion is that there are two different ways threads are implemented. In ye olde days there was no thread support at all. The DoD's mandate of the Ada programming language (in which tasks—aka threads—were is an integral part) forced the adoption of threads.
Run time libraries were created (largely to support Ada). That worked within a process. The process maintained a timer that would interrupt a threads and the library would switch among threads much like the operating system switches processes.
Note that this system only allows one thread of a process at a time to execute, even on a multiprocessor system.
Your first example is describing such a library but it is describing a very primitive thread library where thread scheduling is based upon cooperation among the various threads of the process.
Later, operating system started to develop support for threads. Rather than scheduling a process, the operating system schedules threads for execution. A process is then an address space with a collection of threads. Your second example is talking about this kind of thread.
I've been reading the dinosaur book and have been confused by this particular model.
The books says that for the one to many model "Thread management is done by the thread library in user space, so it is efficient; but the entire process will block if a thread makes a blocking system call. Also, because only one thread can access the kernel at a time, multiple threads are unable to run in parallel on multiprocessors"
What I'm confused about is what is meant by an entire process will block if a blocking system call is made? Does this mean if I have a multi-threaded program and one of it's threads blocks then all of its threads will have to wait, effectively stalling the program?
If a program undergoing execution causes a block with this model does it mean that another separate program can't be swapped in to be executed because the kernel thread is blocking? If that answer is YES another program(process) could be swapped in than why couldn't a multi-threaded program simply execute another one of its threads while the blocking thread is forced to wait?
If you manage your threads in user level, it means that the swapping is done by your application, not by OS scheduler. Each thread must reach some point where he surrenders (or loses) the control to the management mechanism, but that mechanism is also user-level, so if one of the threads is in the middle of doing a system call - your thread management system (and through that all the other threads) must wait until the kernel code is done.
The OS is still active all the time, and may still preempt the entire program, so other processes will not starve, only the internal "threads" you manage yourself. These threads can't get started during that block because the mechanism responsible of starting them is also blocked by the kernel.
I was wondering when .Net would most probably switch from a thread to another?
I understand we can't predict when this will happen exactly, but is there any intelligence in this? For example, when a thread is executed will it try to wait for a method to returns or a loop to finish before switching?
I'm not an expert on .NET, but in general scheduling is handled by the kernel.
Either your thread's timeslice has expired (threads/processes only get a certain amount of CPU time)
Your thread has blocked for IO.
Some other obscure reason, like waiting for an IPC message, a network packet or something.
Threads can be preempted at any point along their execution path, be it in a loop or returning from a function. This in general isn't handled by the underlying VM (.NET or JVM) but is controlled by the OS.
Of course there is 'intelligence', of a sort:). The set of running threads can only change upon an interrupt, either:
An actual hardware interrupt from a peripheral device, eg. disk, NIC, KB, mouse, timer.
A software interrupt, (ie. a system call), that can change the state of thread/s. This encompasses sleep calls and calls to wait/signal on inter-thread synchro objects, as well as I/O calls that request data that is not immediately available.
If there is no interrupt, the OS cannot change the set of running threads because it is not entered. The OS does not know or care about loops, function/methods calls, (except those that make system calls as above), gotos or any other user-level flow-control mechanisms.
I read your question now, it may not be rellevant anymore, but after reading the above answers, i want to just to make sure:
Threads are managed (or as i know) by the process they belong to. There is nothing to do with the Operation System(and that's is the main reason why working with multithreads is more faster than working with multiprocess, because there are data sharing between threads and the switching between them is occuring faster than the context switch wich occure between process by the Short-Term-Scheduler).
(NOTE: There are two types of threads: USER_MODE' threads and KERNEL_MODE' threadss, and each os can have both of them or just on of them. Anyway a thread that working in a user application environment is considered as a USER_MODE' thread and managed by the process it's belong to.)
Am I Write?
Thanks!!!
Here's what I understand; please correct/add to it:
In pure ULTs, the multithreaded process itself does the thread scheduling. So, the kernel essentially does not notice the difference and considers it a single-thread process. If one thread makes a blocking system call, the entire process is blocked. Even on a multicore processor, only one thread of the process would running at a time, unless the process is blocked. I'm not sure how ULTs are much help though.
In pure KLTs, even if a thread is blocked, the kernel schedules another (ready) thread of the same process. (In case of pure KLTs, I'm assuming the kernel creates all the threads of the process.)
Also, using a combination of ULTs and KLTs, how are ULTs mapped into KLTs?
Your analysis is correct. The OS kernel has no knowledge of user-level threads. From its perspective, a process is an opaque black box that occasionally makes system calls. Consequently, if that program has 100,000 user-level threads but only one kernel thread, then the process can only one run user-level thread at a time because there is only one kernel-level thread associated with it. On the other hand, if a process has multiple kernel-level threads, then it can execute multiple commands in parallel if there is a multicore machine.
A common compromise between these is to have a program request some fixed number of kernel-level threads, then have its own thread scheduler divvy up the user-level threads onto these kernel-level threads as appropriate. That way, multiple ULTs can execute in parallel, and the program can have fine-grained control over how threads execute.
As for how this mapping works - there are a bunch of different schemes. You could imagine that the user program uses any one of multiple different scheduling systems. In fact, if you do this substitution:
Kernel thread <---> Processor core
User thread <---> Kernel thread
Then any scheme the OS could use to map kernel threads onto cores could also be used to map user-level threads onto kernel-level threads.
Hope this helps!
Before anything else, templatetypedef's answer is beautiful; I simply wanted to extend his response a little.
There is one area which I felt the need for expanding a little: combinations of ULT's and KLT's. To understand the importance (what Wikipedia labels hybrid threading), consider the following examples:
Consider a multi-threaded program (multiple KLT's) where there are more KLT's than available logical cores. In order to efficiently use every core, as you mentioned, you want the scheduler to switch out KLT's that are blocking with ones that in a ready state and not blocking. This ensures the core is reducing its amount of idle time. Unfortunately, switching KLT's is expensive for the scheduler and it consumes a relatively large amount of CPU time.
This is one area where hybrid threading can be helpful. Consider a multi-threaded program with multiple KLT's and ULT's. Just as templatetypedef noted, only one ULT can be running at one time for each KLT. If a ULT is blocking, we still want to switch it out for one which is not blocking. Fortunately, ULT's are much more lightweight than KLT's, in the sense that there less resources assigned to a ULT and they require no interaction with the kernel scheduler. Essentially, it is almost always quicker to switch out ULT's than it is to switch out KLT's. As a result, we are able to significantly reduce a cores idle time relative to the first example.
Now, of course, all of this depends on the threading library being used for implementing ULT's. There are two ways (which I can come up with) for "mapping" ULT's to KLT's.
A collection of ULT's for all KLT's
This situation is ideal on a shared memory system. There is essentially a "pool" of ULT's to which each KLT has access. Ideally, the threading library scheduler would assign ULT's to each KLT upon request as opposed to the KLT's accessing the pool individually. The later could cause race conditions or deadlocks if not implemented with locks or something similar.
A collection of ULT's for each KLT (Qthreads)
This situation is ideal on a distributed memory system. Each KLT would have a collection of ULT's to run. The draw back is that the user (or the threading library) would have to divide the ULT's between the KLT's. This could result in load imbalance since it is not guaranteed that all ULT's will have the same amount of work to complete and complete roughly the same amount of time. The solution to this is allowing for ULT migration; that is, migrating ULT's between KLT's.
Can someone give me an easy to understand definition of kernel thread dispatching or just thread dispatching if there's no difference between the two?
From what I understand it's just doing a context switch while the currently active thread waits on a lock from another thread, so the CPU goes and does something else while this thread is in blocking mode.
I might however have misunderstood.
It's basically the process by which the operating system determines which of the many active threads is sent (dispatched) to the CPU for processing at any given point.
Each operating system has its own implementation, but the basic concept is to keep a sorted list of threads by priority, and dispatch them as needed to the CPU. Time slicing is added to allow multiple programs to run concurrently, etc.