How is process-based multitasking achieved by using multi-threading in each process?
For example, consider when an operating system is running with two background process. Each process supports internally multi-threading features. Now, how does time slicing happen between and inside these processes, and how does time slicing happen between threads?
The scheduler typically works at the thread level. In simplest terms the scheduler gives each runnable thread its timeslice in turn.
So a process with two threads will get twice as much CPU time as a process with one thread.
From:
http://msdn.microsoft.com/en-us/library/ms684259(VS.85).aspx
"A multitasking operating system divides the available processor time among the processes or threads that need it. The system is designed for preemptive multitasking; it allocates a processor time slice to each thread it executes. The currently executing thread is suspended when its time slice elapses, allowing another thread to run. When the system switches from one thread to another, it saves the context of the preempted thread and restores the saved context of the next thread in the queue.
The length of the time slice depends on the operating system and the processor. Because each time slice is small (approximately 20 milliseconds), multiple threads appear to be executing at the same time. This is actually the case on multiprocessor systems, where the executable threads are distributed among the available processors. However, you must use caution when using multiple threads in an application, because system performance can decrease if there are too many threads."
Also check out This link for when to use multi-tasking
The operating system decides when and for how long each thread exectues. For Microsoft operating systems, there is no way to determine or predict which thread in which process will execute next. Each thread also has a priority that it runs at. Higher priority threads tend to get more time than lower This priority can be changed by the user or by a program. See this link for more info.
"Now, how does time slicing happen between and inside these processes, and how does time slicing happen between threads?"
That's entirely up to the operating system to decide, really. A really basic OS might not do time-slicing at all, and just let each process run through to completion on a first-come, first-serve basis.
However, most modern operating systems will use some flavor of scheduling algorithm to decide which thread gets to execute on which core and for how long, and perform the context-switching necessary to save and restore per-thread state when swapping out one thread for another.
Related
Having just finished a book on comp. architecture, I find myself not completely clarified on where the scheduler is running.
What I'm looking to have clarified is where the scheduler is running - does it have it's own core assigned to run that and nothing else, or is the "scheduler" in fact just a more ambiguous algorithm, that it implemented in every thread being executed - ex. upon preemption of thread, a swithToFrom() command is run?
I don't need specifics according to windows x/linux x/mac os x, just in general.
No the scheduler is not run in it's own core. In fact multi-threading was common long before multi-core CPUs were common.
The best way to see how scheduler code interacts with thread code is to start with a simple, cooperative, single-core example.
Suppose thread A is running and thread B is waiting on an event. thread A posts that event, which causes thread B to become runnable. The event logic has to call the scheduler, and, for the purposes of this example, we assume that it decides to switch to thread B. At this point in time the call stack will look something like this:
thread_A_main()
post_event(...)
scheduler(...)
switch_threads(threadA, threadB)
switch_threads will save the CPU state on the stack, save thread A's stack pointer, and load the CPU stack pointer with the value of thread B's stack pointer. It will then load the rest of the CPU state from the stack, where the stack is now stack B. At this point, the call stack has become
thread_B_main()
wait_on_event(...)
scheduler(...)
switch_threads(threadB, threadC)
In other words, thread B has now woken up in the state it was in when it previously yielded control to thread C. When switch_threads() returns, it returns control to thread B.
These kind of manipulations of the stack pointer usually require some hand-coded assembler.
Add Interrupts
Thread B is running and a timer interrupts occurs. The call stack is now
thread_B_main()
foo() //something thread B was up to
interrupt_shell
timer_isr()
interrupt_shell is a special function. It is not called. It is preemptively invoked by the hardware. foo() did not call interrupt_shell, so when interrupt_shell returns control to foo(), it must restore the CPU state exactly. This is different from a normal function, which returns leaving the CPU state according to calling conventions. Since interrupt_shell follows different rules to those stated by the calling conventions, it too must be written in assembler.
The main job of interrupt_shell is to identify the source of the interrupt and call the appropriate interrupt service routine (ISR) which in this case is timer_isr(), then control is returned to the running thread.
Add preemptive thread switches
Suppose the timer_isr() decides that it's time for a time-slice. Thread D is to be given some CPU time
thread_B_main()
foo() //something thread B was up to
interrupt_shell
timer_isr()
scheduler()
Now, scheduler() can't call switch_threads() at this point because we are in interrupt context. However, it can be called soon after, usually as the last thing interrupt_shell does. This leaves the thread B stack saved in this state
thread_B_main()
foo() //something thread B was up to
interrupt_shell
switch_threads(threadB, threadD)
Add Deferred Service Routines
Some OSses do not allow you to do complex logic like scheduling from within ISRs. One solution is to use a deferred service routine (DSR) which runs as higher priority than threads but lower than interrupts. These are used so that while scheduler() still needs to be protected from being preempted by DSRs, ISRs can be executed without a problem. This reduces the number of places a kernel has to mask (switch off) interrupts to keep it's logic consistent.
I once ported some software from an OS that had DSRs to one that didn't. The simple solution to this was to create a "DSR thread" that ran higher priority than all other threads. The "DSR thread" simply replaces the DSR dispatcher that the other OS used.
Add traps
You may have observed in the examples I've given so far, we are calling the scheduler from both thread and interrupt contexts. There are two ways in and two ways out. It looks a bit weird but it does work. However, moving forward, we may want to isolate our thread code from our Kernel code, and we do this with traps. Here is the event posting redone with traps
thread_A_main()
post_event(...)
user_space_scheduler(...)
trap()
interrupt_shell
kernel_space_scheduler(...)
switch_threads(threadA, threadB)
A trap causes an interrupt or an interrupt-like event. On the ARM CPU they are known as "software interrupts" and this is a good description.
Now all calls to switch_threads() begin and end in interrupt context, which, incidentally usually happens in a special CPU mode. This is a step towards privilege separation.
As you can see, scheduling wasn't built in a day. You could go on:
Add a memory mapper
Add processes
Add multiple Cores
Add hyperthreading
Add virtualization
Happy reading!
Each core is separately running the kernel, and cooperates with other cores by reading / writing shared memory. One of the shared data structures maintained by the kernel is the list of tasks that are ready to run, and are just waiting for a timeslice to run in.
The kernel's process / thread scheduler runs on the core that needs to figure out what to do next. It's a distributed algorithm with no single decision-making thread.
Scheduling doesn't work by figuring out what task should run on which other CPU. It works by figuring out what this CPU should do now, based on which tasks are ready to run. This happens whenever a thread uses up its timeslice, or makes a system call that blocks. In Linux, even the kernel itself is pre-emptible, so a high-priority task can be run even in the middle of a system call that takes a lot of CPU time to handle. (e.g. checking the permissions on all the parent directories in an open("/a/b/c/d/e/f/g/h/file", ...), if they're hot in VFS cache so it doesn't block, just uses a lot of CPU time).
I'm not sure if this is done by having the directory-walking loop in (a function called by) open() "manually" call schedule() to see if the current thread should be pre-empted or not. Or maybe just that tasks waking up will have set some kind of hardware time to fire an interrupt, and the kernel in general is pre-emptible if compiled with CONFIG_PREEMPT.
There's an inter-processor interrupt mechanism to ask another core to schedule something on itself, so the above description is an over-simplification. (e.g. for Linux run_on to support RCU sync points, and TLB shootdowns when a thread on another core uses munmap). But it's true that there isn't one "master control program"; generally the kernel on each core decides what that core should be running. (By running the same schedule() function on a shared data-structure of tasks that are ready to run.)
The scheduler's decision-making is not always as simple as taking the task at the front of the queue: a good scheduler will try to avoid bouncing a thread from one core to another (because its data will be hot in the caches of the core it was last running on, if that was recent). So to avoid cache thrashing, a scheduler algorithm might choose not to run a ready task on the current core if it was just running on a different core, instead leaving it for that other core to get to later. That way a brief interrupt-handler or blocking system call wouldn't result in a CPU migration.
This is especially important in a NUMA system, where running on the "wrong" core will be slower long-term, even once the caches populate.
There are three types of general schedulers:
Job scheduler also known as the Long term scheduler.
Short term scheduler also known as the CPU scheduler.
Medium term scheduler, mostly used to swap jobs so there can be non-blocking calls. This is usually for not having too many I/O jobs or to little.
In an operating systems book it shows a nice automata of the states these schedulers go to and from. Job scheduler puts things from job queue to ready queue, the CPU scheduler takes things from ready queue to running state. The algorithm is just like any other software, it must be run on a cpu/core, it is most likely probably part of the kernel somewhere.
It doesn't make sense the scheduler can be preempted. The jobs inside the queue can be preempted when running, for I/O, etc. No the kernel does not have to schedule itself to allocate the task, it just gets cpu time without scheduling itself. And yes, most likely the data is in probably in ram, not sure if it is worth storing in the cpu cache.
I am working with time-critical applications where the microsecond counts. I am interested to a more convenient way to develop my applications using a non bare-metal approach (some kind of framework or base foundation common to all my projects).
A considered real-time operating system such as RTX, Xenomai, Micrium or VXWorks are not really real-time under my terms (or under the terms of electronic engineers). So I prefer to talk about soft-real-time and hard-real-time applications. An hard-real-time application has an acceptable jitter less than 100 ns and a heat-beat of 100..500 microseconds (tick timer).
After lots of readings about operating systems I realized that typical tick-time is 1 to 10 milliseconds and only one task can be executed each tick. Therefore the tasks take usually much more than one tick to complete and this is the case of most available operating systems or micro kernels.
For my applications a typical task has a duration of 10..100 microseconds, with few exceptions that can last for more than one tick. So any real-time operating system cannot not fulfill my requirements. That is the reason why other engineers still not consider operating system, micro or nano kernels because the way they work is too far from their needs. I still want to struggle a bit and in my case I now realize I have to consider a new category of operating system that I never heard about (and that may not exist yet). Let's call this category nano-kernel or subtick-scheduler
In such dreamed kernels I would find:
2 types of tasks:
Preemptive tasks (that run in their own memory space)
Non-preemptive tasks (that run in the kernel space and must complete in less than one tick.
Deterministic kernel scheduler (fixed duration after the ISR to reach the theoretical zero second jitter)
Ability to run multiple tasks per tick
For a better understanding of what I am looking for I made this figure below that represents the two types or kernels. The first representation is the traditional kernel. A task executes at each tick and it may interrupt the kernel with a system call that invoke a full context switch.
The second diagram shows a sub-tick kernel scheduler where multiple tasks may share the same tick interrupt. Task 1 was summoned with a maximum execution time value so it needs 2 ticks to complete. Task 2 is set with low priority, so it consumes the remaining time of each tick upon completion. Task 3 is non-preemptive so it operates on the kernel space which save some precious context switch time.
Available operating systems such as RTOS, RTAI, VxWorks or µC/OS are not fully real-time and are not suitable for embedded hard real-time applications such as motion-control where a typical cycle would last no more than 50 to 500 microseconds. By analyzing my needs I land on different topology for my scheduler were multiple tasks can be executed under the same tick interrupt. Obviously I am not the only one with this kind of need and my problem might simply be a kind of X-Y problem. So said differently I am not really looking at what I am really looking for.
After this (pretty) long introduction I can formulate my question:
What could be a good existing architecture or framework that can fulfill my requirements other than a naive bare-metal approach where everything is written sequentially around one master interrupt? If this kind of framework/design pattern exists what would it be called?
Sorry, but first of all, let me say that your entire post is completely wrong and shows complete lack of understanding how preemptive RTOS works.
After lots of readings about operating systems I realized that typical tick-time is 1 to 10 milliseconds and only one task can be executed each tick.
This is completely wrong.
In reality, a tick frequency in RTOS determines only two things:
resolution of timeouts, sleeps and so on,
context switch due to round-robin scheduling (where two or more threads with the same priority are "runnable" at the same time for a long period of time.
During a single tick - which typically lasts 1-10ms, but you can usually configure that to be whatever you like - scheduler can do hundreds or thousands of context switches. Or none. When an event arrives and wakes up a thread with sufficiently high priority, context switch will happen immediately, not with the next tick. An event can be originated by the thread (posting a semaphore, sending a message to another thread, ...), interrupt (posting a semaphore, sending a message to a queue, ...) or by the scheduler (expired timeout or things like that).
There are also RTOSes with no system ticks - these are called "tickless". There you can have resolution of timeouts in the range of nanoseconds.
That is the reason why other engineers still not consider operating system, micro or nano kernels because the way they work is too far from their needs.
Actually this is a reason why these "engineers" should read something instead of pretending to know everything and seeking "innovative" solutions to non-existing problems. This is completely wrong.
The first representation is the traditional kernel. A task executes at each tick and it may interrupt the kernel with a system call that invoke a full context switch.
This is not a feature of a RTOS, but the way you wrote your application - if a high priority task is constantly doing something, then lower priority tasks will NOT get any chance to run. But this is just because you assigned wrong priorities.
Unless you use cooperative RTOS, but if you have such high requirements, why would you do that?
The second diagram shows a sub-tick kernel scheduler where multiple tasks may share the same tick interrupt.
This is exactly how EVERY preemptive RTOS works.
Available operating systems such as RTOS, RTAI, VxWorks or µC/OS are not fully real-time and are not suitable for embedded hard real-time applications such as motion-control where a typical cycle would last no more than 50 to 500 microseconds.
Completely wrong. In every known RTOS it is not a problem to get a response time down to single microseconds (1-3us) with a chip that has clock in the range of 100MHz. So you actually can run "jobs" which are as short as 10us without too much overhead. You can even have "jobs" as short as 10ns, but then the overhead will be pretty high...
What could be a good existing architecture or framework that can fulfill my requirements other than a naive bare-metal approach where everything is written sequentially around one master interrupt? If this kind of framework/design pattern exists what would it be called?
This pattern is called preemptive RTOS. Do note that threads in RTOS are NOT executed in "tick interrupt". They are executed in standard "thread" context, and tick interrupt is only used to switch context of one thread to another.
What you described in your post is a "cooperative" RTOS, which does NOT preempt threads. You use that in systems with extremely limited resources and with low timing requirements. In every other case you use preemptive RTOS, which is capable of handling the events immediately.
I'm reading about scheduling, but I can't figure out how a scheduler regains control after it invokes code in the user space.
E.g. the scheduler passes the control to some app in the user space which does some infinite loop and no other hardware interrupt occurs on an one core chip. All documents talk about the scheduler regaining control and preemptivly interrupting the user process, but how does that work if the control is never passed back to the OS?
Question: Does the scheduler register with some clock in the CPU to be given control again after X msecs? Or is there some other trick? If no, what is the C function called to register for regular (or one time?) control regains?
On Windows the Sleep(0) "causes the thread to relinquish the remainder of its time slice to any other thread of equal priority that is ready to run". This forces the scheduler to gain control.
On Linux the sched_yield "causes the calling thread to relinquish the CPU". This also forces the scheduler to gain control.
And the scheduler also gains control by interrupts too. When a thread has consumed its quantum of CPU usage the scheduler reschedules.
Windows CE for example allows to customize the thread quantum.
You may also read Thread Scheduling: quanta, switching and scheduling algorithms.
There is no single scheduler in Windows. Event based scheduling code is spread across the kernel. The kernels dispatcher routines are triggered by these events:
Thread ready for execution
Thread quantum expired
Thread priority change
Thread processor affinity change
Wait functions and Sleep functions
This Microsoft presentation is summarizing some of the scheduler principles.
If no other interrupt occured, a preemptive O/S wouldn't despatch, and the user application would loop for ever.
This won't happen, though. Typically, a preemptive scheduler will despatch on every system call, every interrupt, and every tick of the system clock. The system clock will always interrupt, so your infinite loop simply won't occur.
The Pick operating system (after its developer Dick Pick) used a non-preemptive scheduler. Software developed for this system was required to make a system call periodically to allow the kernel to despatch other processes. In this environment the kernel would otherwise lose control completely until the process terminated.
The argument used in its justification was that considerable time was spent saving and restoring the processor state during a despatch. Forcing the application to take responsibility for this would allow a faster despatch process.
ThreadX is considered a RTOS.
I know general definitions and requirements of an RTOS, however, could anyone help to shed some light on why ThreadX can be called an RTOS, or, what features of the OS make it realtime capable?
Thanks~
When programmers talk about real-time operating systems they often mention features that relate to managing multiple processes or threads: mutexes, semaphores and interprocess (or interthread) communications etc.
However the true definition is that the system must guarantee that some given operations will always happen within a known, deterministic time (i.e. time in seconds, not in relative terms). Neither Linux or Windows are truly real time. A Linux or Windows computer can be so blazing fast that whatever you want done will almost always happen fast enough - but there is no guarantee that it will always be within a maximum time. If you are building a software system to control a medical device or a huge piece of factory equipment, then you need to stop or start something in x-milliseconds, not "soon", or "usually fast enough".
Now in practice, to provide this guarantee in a useful, non-trivial system one often needs pre-emptive multitasking, multiple threads and all the features usually mentioned, so you would be hard pressed to find an RTOS without them. However, the defining characteristic of an RTOS is right in the name: things can be known to happen in a real amount of time.
As to your specific question, from the ThreadX web site:
ThreadX is deteriminstic. A high priority thread starts responding to
an external event on the order of the time it takes to perform a
highly optimized ThreadX context switch.
- Boot time: 300 cycles
- Context switch time: <100 cycles
- Semaphore get: 30 cycles
What it all means is that your response time is deterministic.
This is one of the most important things you want in an RTOS.
In threadx your threads have a priority. The operating system is driven by a hardware interrupt timer and the scheduler ensures that the threads are scheduled correctly according to their priority.
For example, if thread A (high priority) is waiting on a semaphore and thread B (low priority) is running, then as as soon as the semaphore becomes available then thread B will be interrupted and thread A will be started.
Threadx has a number of other features to optimize the context switching time.
For example, each thread has its own stack.
For more detail you should get this: http://www.amazon.com/Real-Time-Embedded-Multithreading-Using-ThreadX/dp/1578201349/ref=sr_1_2?s=books&ie=UTF8&qid=1390859108&sr=1-2&keywords=real+time+threadx
Not an expert but, When you impose time constraints on application threads/processes it is called real-time software.
In RTOS, if high priority thread comes then low priority thread will be suspended until high priority thread is finished (or go into to idle/suspended state). Low priority thread will never get time (event time slice is enabled) until any high priority thread is active.
In case of same thread priority, if time slice is enabled then each thread will get specific amount of time.
You should also check priority inversion in RTOS case.
ThreadX will have the same response time no matter the size of the system: if the system has one thread or many, one semaphore or many, etc the response time will be the same. All operations have constant response times. Thread preemption time is bounded and constant. Interrupt response time is bounded and constant. The level of capabilities that ThreadX offers is sometimes described in academic literature as "hard real-time".
Is there a relationship between a kernel and a user thread?
Some operating system textbooks said that "maps one (many) user thread to one (many) kernel thread". What does map means here?
When they say map, they mean that each kernel thread is assigned to a certain number of user mode threads.
Kernel threads are used to provide privileged services to applications (such as system calls ). They are also used by the kernel to keep track of what all is running on the system, how much of which resources are allocated to what process, and to schedule them.
If your applications make heavy use of system calls, more user threads per kernel thread, and your applications will run slower. This is because the kernel thread will become a bottleneck, since all system calls will pass through it.
On the flip side though, if your programs rarely use system calls (or other kernel services), you can assign a large number of user threads to a kernel thread without much performance penalty, other than overhead.
You can increase the number of kernel threads, but this adds overhead to the kernel in general, so while individual threads will be more responsive with respect to system calls, the system as a whole will become slower.
That is why it is important to find a good balance between the number of kernel threads and the number of user threads per kernel thread.
http://www.informit.com/articles/printerfriendly.aspx?p=25075
Implementing Threads in User Space
There are two main ways to implement a threads package: in user space and in the kernel. The choice is moderately controversial, and a hybrid implementation is also possible. We will now describe these methods, along with their advantages and disadvantages.
The first method is to put the threads package entirely in user space. The kernel knows nothing about them. As far as the kernel is concerned, it is managing ordinary, single-threaded processes. The first, and most obvious, advantage is that a user-level threads package can be implemented on an operating system that does not support threads. All operating systems used to fall into this category, and even now some still do.
All of these implementations have the same general structure, which is illustrated in Fig. 2-8(a). The threads run on top of a run-time system, which is a collection of procedures that manage threads. We have seen four of these already: thread_create, thread_exit, thread_wait, and thread_yield, but usually there are more.
When threads are managed in user space, each process needs its own private thread table to keep track of the threads in that process. This table is analogous to the kernel's process table, except that it keeps track only of the per-thread properties such the each thread's program counter, stack pointer, registers, state, etc. The thread table is managed by the run-time system. When a thread is moved to ready state or blocked state, the information needed to restart it is stored in the thread table, exactly the same way as the kernel stores information about processes in the process table.
When a thread does something that may cause it to become blocked locally, for example, waiting for another thread in its process to complete some work, it calls a run-time system procedure. This procedure checks to see if the thread must be put into blocked state. If so, it stores the thread's registers (i.e., its own) in the thread table, looks in the table for a ready thread to run, and reloads the machine registers with the new thread's saved values. As soon as the stack pointer and program counter have been switched, the new thread comes to life again automatically. If the machine has an instruction to store all the registers and another one to load them all, the entire thread switch can be done in a handful of instructions. Doing thread switching like this is at least an order of magnitude faster than trapping to the kernel and is a strong argument in favor of user-level threads packages.
However, there is one key difference with processes. When a thread is finished running for the moment, for example, when it calls thread_yield, the code of thread_yield can save the thread's information in the thread table itself. Furthermore, it can then call the thread scheduler to pick another thread to run. The procedure that saves the thread's state and the scheduler are just local procedures, so invoking them is much more efficient than making a kernel call. Among other issues, no trap is needed, no context switch is needed, the memory cache need not be flushed, and so on. This makes thread scheduling very fast.
User-level threads also have other advantages. They allow each process to have its own customized scheduling algorithm. For some applications, for example, those with a garbage collector thread, not having to worry about a thread being stopped at an inconvenient moment is a plus. They also scale better, since kernel threads invariably require some table space and stack space in the kernel, which can be a problem if there are a very large number of threads.
Despite their better performance, user-level threads packages have some major problems. First among these is the problem of how blocking system calls are implemented. Suppose that a thread reads from the keyboard before any keys have been hit. Letting the thread actually make the system call is unacceptable, since this will stop all the threads. One of the main goals of having threads in the first place was to allow each one to use blocking calls, but to prevent one blocked thread from affecting the others. With blocking system calls, it is hard to see how this goal can be achieved readily.
The system calls could all be changed to be nonblocking (e.g., a read on the keyboard would just return 0 bytes if no characters were already buffered), but requiring changes to the operating system is unattractive. Besides, one of the arguments for user-level threads was precisely that they could run with existing operating systems. In addition, changing the semantics of read will require changes to many user programs.
Another alternative is possible in the event that it is possible to tell in advance if a call will block. In some versions of UNIX, a system call, select, exists, which allows the caller to tell whether a prospective read will block. When this call is present, the library procedure read can be replaced with a new one that first does a select call and then only does the read call if it is safe (i.e., will not block). If the read call will block, the call is not made. Instead, another thread is run. The next time the run-time system gets control, it can check again to see if the read is now safe. This approach requires rewriting parts of the system call library, is inefficient and inelegant, but there is little choice. The code placed around the system call to do the checking is called a jacket or wrapper.
Somewhat analogous to the problem of blocking system calls is the problem of page faults. We will study these in Chap. 4. For the moment, it is sufficient to say that computers can be set up in such a way that not all of the program is in main memory at once. If the program calls or jumps to an instruction that is not in memory, a page fault occurs and the operating system will go and get the missing instruction (and its neighbors) from disk. This is called a page fault. The process is blocked while the necessary instruction is being located and read in. If a thread causes a page fault, the kernel, not even knowing about the existence of threads, naturally blocks the entire process until the disk I/O is complete, even though other threads might be runnable.
Another problem with user-level thread packages is that if a thread starts running, no other thread in that process will ever run unless the first thread voluntarily gives up the CPU. Within a single process, there are no clock interrupts, making it impossible to schedule processes round-robin fashion (taking turns). Unless a thread enters the run-time system of its own free will, the scheduler will never get a chance.
One possible solution to the problem of threads running forever is to have the run-time system request a clock signal (interrupt) once a second to give it control, but this, too, is crude and messy to program. Periodic clock interrupts at a higher frequency are not always possible, and even if they are, the total overhead may be substantial. Furthermore, a thread might also need a clock interrupt, interfering with the run-time system's use of the clock.
Another, and probably the most devastating argument against user-level threads, is that programmers generally want threads precisely in applications where the threads block often, as, for example, in a multithreaded Web server. These threads are constantly making system calls. Once a trap has occurred to the kernel to carry out the system call, it is hardly any more work for the kernel to switch threads if the old one has blocked, and having the kernel do this eliminates the need for constantly making select system calls that check to see if read system calls are safe. For applications that are essentially entirely CPU bound and rarely block, what is the point of having threads at all? No one would seriously propose computing the first n prime numbers or playing chess using threads because there is nothing to be gained by doing it that way.
User threads are managed in userspace - that means scheduling, switching, etc. are not from the kernel.
Since, ultimately, the OS kernel is responsible for context switching between "execution units" - your user threads must be associated (ie., "map") to a kernel schedulable object - a kernel thread†1.
So, given N user threads - you could use N kernel threads (a 1:1 map). That allows you to take advantage of the kernel's hardware multi-processing (running on multiple CPUs) and be a pretty simplistic library - basically just deferring most of the work to the kernel. It does, however, make your app portable between OS's as you're not directly calling the kernel thread functions. I believe that POSIX Threads (PThreads) is the preferred *nix implementation, and that it follows the 1:1 map (making it virtually equivalent to a kernel thread). That, however, is not guaranteed as it'd be implementation dependent (a main reason for using PThreads would be portability between kernels).
Or, you could use only 1 kernel thread. That'd allow you to run on non multitasking OS's, or be completely in charge of scheduling. Windows' User Mode Scheduling is an example of this N:1 map.
Or, you could map to an arbitrary number of kernel threads - a N:M map. Windows has Fibers, which would allow you to map N fibers to M kernel threads and cooperatively schedule them. A threadpool could also be an example of this - N workitems for M threads.
†1: A process has at least 1 kernel thread, which is the actual execution unit. Also, a kernel thread must be contained in a process. OS's must schedule the thread to run - not the process.
This is a question about thread library implement.
In Linux, a thread (or task) could be in user space or in kernel space. The process enter kernel space when it ask kernel to do something by syscall(read, write or ioctl).
There is also a so-called kernel-thread that runs always in kernel space and does not represent any user process.
According to Wikipedia and Oracle, user-level threads are actually in a layer mounted on the kernel threads; not that kernel threads execute alongside user-level threads but that, generally speaking, the only entities that are actually executed by the processor/OS are kernel threads.
For example, assume that we have a program with 2 user-level threads, both mapped to (i.e. assigned) the same kernel thread. Sometimes, the kernel thread runs the first user-level thread (and it is said that currently this kernel thread is mapped to the first user-level thread) and some other times the kernel thread runs the second user-level thread. So we say that we have two user-level threads mapped to the same kernel thread.
As a clarification:
The core of an OS is called its kernel, so the threads at the kernel level (i.e. the threads that the kernel knows of and manages) are called kernel threads, the calls to the OS core for services can be called kernel calls, and ... . The only definite relation between kernel things is that they are strongly related to the OS core, nothing more.