I/O Blocking in Green threads - multithreading

I was reading about green threads and was able to understand that these threads are created by the VM or during runtime and not by the os but I am not able to understand the following statement
When a green thread executes a blocking system call, not only is that thread blocked, but all of the threads within the process are blocked.
Can anyone please explain how is it possible ?

That's pretty simple actually.
"Green Threads" are implemented programmatically inside the VM, which schedules the CPU and memory among them, just like a real OS schedules those resources among OS-level processes and threads.
But from the OS point of view, there is just one thread - the VM itself, so when it makes a blocking system call (on behalf of one of the "Green Threads" it manages internally), this single thread is naturally blocked, and can not do anything, including scheduling the "Green Threads", so the "world stops" for them too.

Related

Why does a process get blocked if a thread waits for I/O in many to one mapping

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.

How does a process schedule its own threads

After the Kernel schedules a process that has threads, How does said process schedule its own threads during its time splice?
For most modern kernels, the kernel only schedules threads, and processes are mostly just a container for the threads to execute inside (e.g. a container that contains a virtual address space, however many threads, and a few other scraps like file handles).
For some kernels (mostly very old unix kernels that existed before threads were invented) the kernel schedules processes and then a user-space library emulates threads. For this to work properly all of the "blocking" system calls (e.g. write()) have to be replaced by asynchronous system calls (e.g. aio_write()) so that other threads in the process can be given CPU time; however I wouldn't want to assume it works properly (e.g. if any thread blocks, then maybe all threads in the process block).
Also it may not work when there's multiple CPUs (kernel gives a process one CPU, but then from the kernel's perspective that process is running and can't use a second CPU). There are sophisticated work-arounds for this (to support "M:N threading") but it's just easier and better to fix the scheduler so it works with threads. Fortunately/unfortunately this didn't matter much in the early days because very few computers had more than one CPU anyway.
Lastly; it doesn't work for thread priorities - e.g. one process might keep CPU busy executing an unimportant/low priority thread while another process doesn't get that CPU time when it desperately needs it for an important/high priority thread. This occurs because no process knows about threads belonging to other processes and the kernel only knows about processes and not threads.
Of course these are also the reasons why every kernel adopted "kernel schedules threads and not processes" (and those that didn't died).
It's down to jargon definitions, but threads are simply a bunch of processes sharing an address space. Older Unixes even called them Light Weight Processes.
With that classical understanding of threads, the answer is that, these days, it's the OS that does the scheduling and each thread gets its own timeslices.
Extras
Some OSes do things to "the whole process" - e.g. Windows will give the process that has mouse focus a priority boost (all it's threads get dynamically notched up a few priority places), to make that application appear to be more sprightly (this goes back to Windows 3).
Other operating systems will increase the priority of a thread dynamically, to solve priority inversion situations. This is where a low priority thread that has control of a resource (I/O, or perhaps a semaphore) is blocking a higher priority thread from running (because the resource is not available. This is the priority inversion, and it's solved by the OS boosting the priority of the blocking thread until it gives up the required resource.
Either the kernel schedules the threads or the kernel schedules processes simulates thread by scheduling it own threads.
Usually, the process schedules its own threads using a library that sets timers. When the timer handler saves the current "thread's" registers then loads a new set of registers from another "thread."

Do threads get its own timeslice in user processes?

I can explain the question better with an example so I am using it?
Suppose our system is Round-Robin scheduled system with each time interval for execution 10ms. If we create two threads in our program , will each thread be executing 10ms or both in combine will execute 10ms?
If they take combine 10ms then who manages context switching between threads?
Note: I am not talking about kernel threads here.
In Linux, the threads contend for CPU with every other thread in the system. In POSIX terms, the threads have system contention scope.
Thus, for your example, each thread will get 10ms.
You can check this by:
Trying to set (via pthread_attr_setscope) the contention scope attribute to PTHREAD_SCOPE_PROCESS - should result in an error.
Get a thread attrbutes via pthread_getattr_np and check via pthread_attr_getscope that
the contention scope is PTHREAD_SCOPE_SYSTEM
Yes they too do have a time-slice.
In linux, threads vye for the resources such as memory,CPU or are waiting for some I/O event to occur. These threads under go through various states like idle,active,ready depending on the avalaibity of the resources. This all working is taken care by "Process Management Subsystem" which consists of Process Schedulars and manages the processes execution and their states.
One can also manipulate the time-period that a process can hold a resource like CPU.
Or the priority of a process can be changed( For e.g "nice").
-Sumeet

Difference between user-level and kernel-supported threads?

I've been looking through a few notes based on this topic, and although I have an understanding of threads in general, I'm not really to sure about the differences between user-level and kernel-level threads.
I know that processes are basically made up of multiple threads or a single thread, but are these thread of the two prior mentioned types?
From what I understand, kernel-supported threads have access to the kernel for system calls and other uses not available to user-level threads.
So, are user-level threads simply threads created by the programmer when then utilise kernel-supported threads to perform operations that couldn't be normally performed due to its state?
Edit: The question was a little confusing, so I'm answering it two different ways.
OS-level threads vs Green Threads
For clarity, I usually say "OS-level threads" or "native threads" instead of "Kernel-level threads" (which I confused with "kernel threads" in my original answer below.) OS-level threads are created and managed by the OS. Most languages have support for them. (C, recent Java, etc) They are extremely hard to use because you are 100% responsible for preventing problems. In some languages, even the native data structures (such as Hashes or Dictionaries) will break without extra locking code.
The opposite of an OS-thread is a green thread that is managed by your language. These threads are given various names depending on the language (coroutines in C, goroutines in Go, fibers in Ruby, etc). These threads only exist inside your language and not in your OS. Because the language chooses context switches (i.e. at the end of a statement), it prevents TONS of subtle race conditions (such as seeing a partially-copied structure, or needing to lock most data structures). The programmer sees "blocking" calls (i.e. data = file.read() ), but the language translates it into async calls to the OS. The language then allows other green threads to run while waiting for the result.
Green threads are much simpler for the programmer, but their performance varies: If you have a LOT of threads, green threads can be better for both CPU and RAM. On the other hand, most green thread languages can't take advantage of multiple cores. (You can't even buy a single-core computer or phone anymore!). And a bad library can halt the entire language by doing a blocking OS call.
The best of both worlds is to have one OS thread per CPU, and many green threads that are magically moved around onto OS threads. Languages like Go and Erlang can do this.
system calls and other uses not available to user-level threads
This is only half true. Yes, you can easily cause problems if you call the OS yourself (i.e. do something that's blocking.) But the language usually has replacements, so you don't even notice. These replacements do call the kernel, just slightly differently than you think.
Kernel threads vs User Threads
Edit: This is my original answer, but it is about User space threads vs Kernel-only threads, which (in hindsight) probably wasn't the question.
User threads and Kernel threads are exactly the same. (You can see by looking in /proc/ and see that the kernel threads are there too.)
A User thread is one that executes user-space code. But it can call into kernel space at any time. It's still considered a "User" thread, even though it's executing kernel code at elevated security levels.
A Kernel thread is one that only runs kernel code and isn't associated with a user-space process. These are like "UNIX daemons", except they are kernel-only daemons. So you could say that the kernel is a multi-threaded program. For example, there is a kernel thread for swap. This forces all swap issues to get "serialized" into a single stream.
If a user thread needs something, it will call into the kernel, which marks that thread as sleeping. Later, the swap thread finds the data, so it marks the user thread as runnable. Later still, the "user thread" returns from the kernel back to userland as if nothing happened.
In fact, all threads start off in kernel space, because the clone() operation happens in kernel space. (And there's lots of kernel accounting to do before you can 'return' to a new process in user space.)
Before we go into comparison, let us first understand what a thread is. Threads are lightweight processes within the domain of independent processes. They are required because processes are heavy, consume a lot of resources and more importantly,
two separate processes cannot share a memory space.
Let's say you open a text editor. It's an independent process executing in the memory with a separate addressable location. You'll need many resources within this process, such as insert graphics, spell-checks etc. It's not feasible to create separate processes for each of these functionalities and maintain them independently in memory. To avoid this,
multiple threads can be created within a single process, which can
share a common memory space, existing independently within a process.
Now, coming back to your questions, one at a time.
I'm not really to sure about the differences between user-level and kernel-level threads.
Threads are broadly classified as user level threads and kernel level threads based on their domain of execution. There are also cases when one or many user thread maps to one or many kernel threads.
- User Level Threads
User level threads are mostly at the application level where an application creates these threads to sustain its execution in the main memory. Unless required, these thread work in isolation with kernel threads.
These are easier to create since they do not have to refer many registers and context switching is much faster than a kernel level thread.
User level thread, mostly can cause changes at the application level and the kernel level thread continues to execute at its own pace.
- Kernel Level Threads
These threads are mostly independent of the ongoing processes and are executed by the operating system.
These threads are required by the Operating System for tasks like memory management, process management etc.
Since these threads maintain, execute and report the processes required by the operating system; kernel level threads are more expensive to create and manage and context switching of these threads are slow.
Most of the kernel level threads can not be preempted by the user level threads.
MS DOS written for Intel 8088 didn't have dual mode of operation. Thus, a user level process had the ability to corrupt the entire operating system.
- User Level Threads mapped over Kernel Threads
This is perhaps the most interesting part. Many user level threads map over to kernel level thread, which in-turn communicate with the kernel.
Some of the prominent mappings are:
One to One
When one user level thread maps to only one kernel thread.
advantages: each user thread maps to one kernel thread. Even if one of the user thread issues a blocking system call, the other processes remain unaffected.
disadvantages: every user thread requires one kernel thread to interact and kernel threads are expensive to create and manage.
Many to One
When many user threads map to one kernel thread.
advantages: multiple kernel threads are not required since similar user threads can be mapped to one kernel thread.
disadvantage: even if one of the user thread issues a blocking system call, all the other user threads mapped to that kernel thread are blocked.
Also, a good level of concurrency cannot be achieved since the kernel will process only one kernel thread at a time.
Many to Many
When many user threads map to equal or lesser number of kernel threads. The programmer decides how many user threads will map to how many kernel threads. Some of the user threads might map to just one kernel thread.
advantages: a great level of concurrency is achieved. Programmer can decide some potentially dangerous threads which might issue a blocking system call and place them with the one-to-one mapping.
disadvantage: the number of kernel threads, if not decided cautiously can slow down the system.
The other part of your question:
kernel-supported threads have access to the kernel for system calls
and other uses not available to user-level threads.
So, are user-level threads simply threads created by the programmer
when then utilise kernel-supported threads to perform operations that
couldn't be normally performed due to its state?
Partially correct. Almost all the kernel thread have access to system calls and other critical interrupts since kernel threads are responsible for executing the processes of the OS. User thread will not have access to some of these critical features. e.g. a text editor can never shoot a thread which has the ability to change the physical address of the process. But if needed, a user thread can map to kernel thread and issue some of the system calls which it couldn't do as an independent entity. The kernel thread would then map this system call to the kernel and would execute actions, if deemed fit.
Quote from here :
Kernel-Level Threads
To make concurrency cheaper, the execution aspect of process is separated out into threads. As such, the OS now manages threads and processes. All thread operations are implemented in the kernel and the OS schedules all threads in the system. OS managed threads are called kernel-level threads or light weight processes.
NT: Threads
Solaris: Lightweight processes(LWP).
In this method, the kernel knows about and manages the threads. No runtime system is needed in this case. Instead of thread table in each process, the kernel has a thread table that keeps track of all threads in the system. In addition, the kernel also maintains the traditional process table to keep track of processes. Operating Systems kernel provides system call to create and manage threads.
Advantages:
Because kernel has full knowledge of all threads, Scheduler may decide to give more time to a process having large number of threads than process having small number of threads.
Kernel-level threads are especially good for applications that frequently block.
Disadvantages:
The kernel-level threads are slow and inefficient. For instance, threads operations are hundreds of times slower than that of user-level threads.
Since kernel must manage and schedule threads as well as processes. It require a full thread control block (TCB) for each thread to maintain information about threads. As a result there is significant overhead and increased in kernel complexity.
User-Level Threads
Kernel-Level threads make concurrency much cheaper than process because, much less state to allocate and initialize. However, for fine-grained concurrency, kernel-level threads still suffer from too much overhead. Thread operations still require system calls. Ideally, we require thread operations to be as fast as a procedure call. Kernel-Level threads have to be general to support the needs of all programmers, languages, runtimes, etc. For such fine grained concurrency we need still "cheaper" threads.
To make threads cheap and fast, they need to be implemented at user level. User-Level threads are managed entirely by the run-time system (user-level library).The kernel knows nothing about user-level threads and manages them as if they were single-threaded processes.User-Level threads are small and fast, each thread is represented by a PC,register,stack, and small thread control block. Creating a new thread, switiching between threads, and synchronizing threads are done via procedure call. i.e no kernel involvement. User-Level threads are hundred times faster than Kernel-Level threads.
Advantages:
The most obvious advantage of this technique is that a user-level threads package can be implemented on an Operating System that does not support threads.
User-level threads does not require modification to operating systems.
Simple Representation: Each thread is represented simply by a PC, registers, stack and a small control block, all stored in the user process address space.
Simple Management: This simply means that creating a thread, switching between threads and synchronization between threads can all be done without intervention of the kernel.
Fast and Efficient: Thread switching is not much more expensive than a procedure call.
Disadvantages:
User-Level threads are not a perfect solution as with everything else, they are a trade off. Since, User-Level threads are invisible to the OS they are not well integrated with the OS. As a result, Os can make poor decisions like scheduling a process with idle threads, blocking a process whose thread initiated an I/O even though the process has other threads that can run and unscheduling a process with a thread holding a lock. Solving this requires communication between between kernel and user-level thread manager.
There is a lack of coordination between threads and operating system kernel. Therefore, process as whole gets one time slice irrespect of whether process has one thread or 1000 threads within. It is up to each thread to relinquish control to other threads.
User-level threads requires non-blocking systems call i.e., a multithreaded kernel. Otherwise, entire process will blocked in the kernel, even if there are runable threads left in the processes. For example, if one thread causes a page fault, the process blocks.
User Threads
The library provides support for thread creation, scheduling and management with no support from the kernel.
The kernel unaware of user-level threads creation and scheduling are done in user space without kernel intervention.
User-level threads are generally fast to create and manage they have drawbacks however.
If the kernel is single-threaded, then any user-level thread performing a blocking system call will cause the entire process to block, even if other threads are available to run within the application.
User-thread libraries include POSIX Pthreads, Mach C-threads,
and Solaris 2 UI-threads.
Kernel threads
The kernel performs thread creation, scheduling, and management in kernel space.
kernel threads are generally slower to create and manage than are user threads.
the kernel is managing the threads, if a thread performs a blocking system call.
A multiprocessor environment, the kernel can schedule threads on different processors.
5.including Windows NT, Windows 2000, Solaris 2, BeOS, and Tru64 UNIX (formerlyDigital UN1X)-support kernel threads.
Some development environments or languages will add there own threads like feature, that is written to take advantage of some knowledge of the environment, for example a GUI environment could implement some thread functionality which switch between user threads on each event loop.
A game library could have some thread like behaviour for characters. Sometimes the user thread like behaviour can be implemented in a different way, for example I work with cocoa a lot, and it has a timer mechanism which executes your code every x number of seconds, use fraction of a seconds and it like a thread. Ruby has a yield feature which is like cooperative threads. The advantage of user threads is they can switch at more predictable times. With kernel thread every time a thread starts up again, it needs to load any data it was working on, this can take time, with user threads you can switch when you have finished working on some data, so it doesn't need to be reloaded.
I haven't come across user threads that look the same as kernel threads, only thread like mechanisms like the timer, though I have read about them in older text books so I wonder if they were something that was more popular in the past but with the rise of true multithreaded OS's (modern Windows and Mac OS X) and more powerful hardware I wonder if they have gone out of favour.

what is kernel thread dispatching?

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.

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