I get the idea that if locking and unlocking a mutex is an atomic operation, it can protect the critical section of code in case of a single processor architecture.
Any thread, which would be scheduled first, would be able to "lock" the mutex in a single machine code operation.
But how are mutexes any good when the threads are running on multiple cores? (Where different threads could be running at the same time on different "cores" at the same time).
I can't seem to grasp the idea of how a multithreaded program would work without any deadlock or race condition on multiple cores?
The general answer:
Mutexes are an operating system concept. An operating system offering mutexes has to ensure that these mutexes work correctly on all hardware that this operation system wants to support. If implementing a mutex is not possible for a specific hardware, the operating system cannot offer mutexes on that hardware. If the operating system requires the existence of mutexes to work correctly, it cannot support that hardware at all. How the operating system is implementing mutexes for a specific hardware is unsurprisingly very hardware dependent and varies a lot between the operating systems and their supported hardware.
The detailed answer:
Most general purpose CPUs offer atomic operations. These operations are designed to be atomic across all CPU cores within a system, whether these cores are part of a single or multiple individual CPUs.
With as little as two atomic operations, atomic_or and atomic_and, it is possible to implement a lock. E.g. think of
int atomic_or ( int * addr, int val )
It atomically calculates *addr = *addr | val and returns the old value of *addr prior to performing the calculation. If *lock == 0 and multiple threads call atomic_or(lock, 1), then only one of them will get 0 as result; only the first thread to perform that operation. All other threads get 1 as result. The one thread that got 0 is the winner, it has the lock, all other threads register for an event and go to sleep.
The winner thread now has exclusive access to the section following the atomic_or, it can perform the desired work and once it is done, it just clears the lock again (atomic_and(lock, 0)) and generates a system event, that the lock is now available again.
The system will then wake up one, some, or all of the threads that registered for this event before going to sleep and the race for the lock starts all over. Either one of the woken up threads will win the race or possibly none of them, as another thread was even faster and may have grabbed the lock in between the atomic_and and before the other threads were even woken up but that is okay and still correct, as it's still only one thread having access. All threads that failed to obtain the lock go back to sleep.
Of course, the actual implementations of modern systems are often much more complicated than that, they may take things like threads priorities into account (high prio threads may be preferred in the lock race) or might ensure that every thread waiting for a mutex will eventually also get it (precautions exist that prevent a thread from always losing the lock-race). Also mutexes can be recursive, in which case the system ensures that the same thread can obtain the same mutex multiple times without deadlocking and this requires some additional bookkeeping.
Probably needless to say but atomic operations are more expensive operations as they require the cores within a system to synchronize their work and this will slow their processing throughput. They may be somewhat expensive if all cores run on a single CPU but they may even be very expensive if there are multiple CPUs as the synchronization must take place over the CPU bus system that connects the CPUs with each other and this bus system usually does not operate at CPU speed level.
On the other hand, using mutexes will always slow down processing to begin with as providing exclusive access to resources has to slow down processing if multiple threads ever require access at the same time to continue their work. So for implementing mutexes this is irrelevant. Actually, if you can implement a function in a thread-safe way using just atomic operations instead of full featured mutexes, you will quite often have a noticeable speed benefit, despite these operations being more expensive than normal operations.
Threads are managed by the operating system, which among other things, is responsible for scheduling threads to cores, so it can also avoid scheduling a specific thread onto a core.
A mutex is an operating-system concept. You're basically asking the OS to block a thread until some other thread tells the OS it's ok
On modern operating systems, threads are an abstraction over the physical hardware. A programmer targets the thread as an abstraction for code execution. There is no separate abstraction for working on a hardware core available. The operating system is responsible for mapping threads to physical cores.
A mutex is a data structure that lives in system memory. Any thread that has access can read that memory position, regardless of what thread or core it is running in. It doesn't matter whether your code is executing on core 1 or 20, its still has the ability to read the current state of the lock.
In other words, regardless of the number of threads or cores, there is only shared system memory for them to act on.
Related
I am taking a course on concurrency. The text says that multi-threading allows high throughput as it takes advantage of the multiples cores of the cpu.
I have a question about locking in the context of multiple cores. If we have multiple threads and they are running in different cpu cores, why can't two threads acquire the same lock? How does os protect against such scenarios?
Locking and locks are for synchronization to prevent data corruption when multiple threads want to write to the same memory.
Generally you run multiple threads and use locking only in critical situations.
If two or more threads want to write into the same place at the same time then the multi core calculation is limited. Of course you can use no locking in this situation but results can be unpredictable at that moment.
For example to write multi-threaded calculation of matrix multiplication you make a thread for every row of the resulting matrix. There is no locking needed because every thread writes to different place and this scenario can fully benefit from multiple processors.
If you want to permit more than one shared access to a resource then you can use Semaphore (in java).
If we have multiple threads and they are running in different cpu cores, why can't two threads acquire the same lock?
The purpose of mutex/lock is to implement mutual exclusion - only one thread can lock a mutex at a time. Or, in other words, many threads cannot lock the same mutex at the same time, by definition. This mechanism is needed to allow multiple threads to store into or read from a shared non-atomic resource without data race conditions.
How does os protect against such scenarios?
OS support is needed to prevent the threads from busy-waiting when locking a mutex that is already locked by another thread. Linux implementations of mutex (and semaphore) use futex to put the waiting threads to sleep and wake them up when the mutex is released.
Here is a longer explanation from Linus Torvalds of how mutex is implemented.
I was looking at the differences between user-level threads and kernel-level threads, which I basically understood.
What's not clear to me is the point of implementing user-level threads at all.
If the kernel is unaware of the existence of multiple threads within a single process, then which benefits could I experience?
I have read a couple of articles that stated user-level implementation of threads is advisable only if such threads do not perform blocking operations (which would cause the entire process to block).
This being said, what's the difference between a sequential execution of all the threads and a "parallel" execution of them, considering they cannot take advantage of multiple processors and independent scheduling?
An answer to a previously asked question (similar to mine) was something like:
No modern operating system actually maps n user-level threads to 1
kernel-level thread.
But for some reason, many people on the Internet state that user-level threads can never take advantage of multiple processors.
Could you help me understand this, please?
I strongly recommend Modern Operating Systems 4th Edition by Andrew S. Tanenbaum (starring in shows such as the debate about Linux; also participating: Linus Torvalds). Costs a whole lot of bucks but it's definitely worth it if you really want to know stuff. For eager students and desperate enthusiasts it's great.
Your questions answered
[...] what's not clear to me is the point of implementing User-level threads
at all.
Read my post. It is comprehensive, I daresay.
If the kernel is unaware of the existence of multiple threads within a
single process, then which benefits could I experience?
Read the section "Disadvantages" below.
I have read a couple of articles that stated that user-level
implementation of threads is advisable only if such threads do not
perform blocking operations (which would cause the entire process to
block).
Read the subsection "No coordination with system calls" in "Disadvantages."
All citations are from the book I recommended in the top of this answer, Chapter 2.2.4, "Implementing Threads in User Space."
Advantages
Enables threads on systems without threads
The first advantage is that user-level threads are a way to work with threads on a system without threads.
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.
No kernel interaction required
A further benefit is the light overhead when switching threads, as opposed to switching to the kernel mode, doing stuff, switching back, etc. The lighter thread switching is described like this in the book:
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) [...] 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 happens to have an
instruction to store all the registers and another one to load them
all, the entire thread switch can be done in just a handful of in-
structions. Doing thread switching like this is at least an order of
magnitude—maybe more—faster than trapping to the kernel and is a
strong argument in favor of user-level threads packages.
This efficiency is also nice because it spares us from incredibly heavy context switches and all that stuff.
Individually adjusted scheduling algorithms
Also, hence there is no central scheduling algorithm, every process can have its own scheduling algorithm and is way more flexible in its variety of choices. In addition, the "private" scheduling algorithm is way more flexible concerning the information it gets from the threads. The number of information can be adjusted manually and per-process, so it's very finely-grained. This is because, again, there is no central scheduling algorithm needing to fit the needs of every process; it has to be very general and all and must deliver adequate performance in every case. User-level threads allow an extremely specialized scheduling algorithm.
This is only restricted by the disadvantage "No automatic switching to the scheduler."
They [user-level threads] 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.
Disadvantages
No coordination with system calls
The user-level scheduling algorithm has no idea if some thread has called a blocking read system call. OTOH, a kernel-level scheduling algorithm would've known because it can be notified by the system call; both belong to the kernel code base.
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.
He goes on that system calls could be made non-blocking but that would be very inconvenient and compatibility to existing OSes would be drastically hurt.
Mr Tanenbaum also says that the library wrappers around the system calls (as found in glibc, for example) could be modified to predict when a system cal blocks using select but he utters that this is inelegant.
Building upon that, he says that threads do block often. Often blocking requires many system calls. And many system calls are bad. And without blocking, threads become less useful:
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.
Page faults block per-process if unaware of threads
The OS has no notion of threads. Therefore, if a page fault occurs, the whole process will be blocked, effectively blocking all user-level threads.
Somewhat analogous to the problem of blocking system calls is the
problem of page faults. [...] 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. [...] The process is blocked while the necessary
instruction is being located and read in. If a thread causes a page
fault, the kernel, unaware of even the existence of threads, naturally
blocks the entire process until the disk I/O is complete, even though
other threads might be runnable.
I think this can be generalized to all interrupts.
No automatic switching to the scheduler
Since there is no per-process clock interrupt, a thread acquires the CPU forever unless some OS-dependent mechanism (such as a context switch) occurs or it voluntarily releases the CPU.
This prevents usual scheduling algorithms from working, including the Round-Robin algorithm.
[...] 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.
He says that a possible solution would be
[...] 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.
I would even go on further and say that such a "request" would require some system call to happen, whose drawback is already explained in "No coordination with system calls." If no system call then the program would need free access to the timer, which is a security hole and unacceptable in modern OSes.
What's not clear to me is the point of implementing user-level threads at all.
User-level threads largely came into the mainstream due to Ada and its requirement for threads (tasks in Ada terminology). At the time, there were few multiprocessor systems and most multiprocessors were of the master/slave variety. Kernel threads simply did not exist. User threads had to be created to implement languages like Ada.
If the kernel is unaware of the existence of multiple threads within a single process, then which benefits could I experience?
If you have kernel threads, threads multiple threads within a single process can run simultaneously. In user threads, the threads always execute interleaved.
Using threads can simplify some types of programming.
I have read a couple of articles that stated user-level implementation of threads is advisable only if such threads do not perform blocking operations (which would cause the entire process to block).
That is true on Unix and maybe not all unix implementations. User threads on many operating systems function perfectly fine with blocking I/O.
This being said, what's the difference between a sequential execution of all the threads and a "parallel" execution of them, considering they cannot take advantage of multiple processors and independent scheduling?
In user threads. there is never parallel execution. In kernel threads, the can be parallel execution IF there are multiple processors. On a single processor system, there is not much advantage to using kernel threads over single threads (contra: note the blocking I/O issue on Unix and user threads).
But for some reason, many people on the Internet state that user-level threads can never take advantage of multiple processors.
In user threads, the process manages its own "threads" by interleaving execution within itself. The process can only have a thread run in the processor that the process is running in.
If the operating system provides system services to schedule code to run on a different processor, user threads could run on multiple processors.
I conclude by saying that for practicable purposes there are no advantages to user threads over kernel threads. There are those that will assert that there are performance advantages, but for there to be such an advantage it would be system dependent.
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.
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.
The Windows API provides critical sections in which a waiting thread will spin a limited amount of times before context switching, but only on a multiprocessor system. These are implemented using InitializeCriticalSectionAndSpinCount. (See http://msdn.microsoft.com/en-us/library/ms682530.aspx.) This is efficient when you have a critical section that will often only be locked for a short period of time and therefore contention should not immediately trigger a context switch. Two related questions:
For a high-level, cross-platform threading library or an implementation of a synchronized block, is having a small amount of spinning before triggering a context switch a good default?
What, if anything, is the equivalent to InitializeCriticalSectionAndSpinCount on other OS's, especially Posix?
Edit: Of course no spin count will be optimal for all cases. I'm only interested in whether using a nonzero spin count would be a better default than not using one.
My opinion is that the optimal "spin-count" for best application performance is too hardware-dependent for it to be an important part of a cross-platform API, and you should probably just use mutexes (in posix, pthread_mutex_init / destroy / lock / trylock) or spin-locks (pthread_spin_init / destroy / lock / trylock). Rationale follows.
What's the point of the spin count? Basically, if the lock owner is running simultaneously with the thread attempting to acquire the lock, then the lock owner might release the lock quickly enough that the EnterCriticalSection caller could avoid giving up CPU control in acquiring the lock, improving that thread's performance, and avoiding context switch overhead. Two things:
1: obviously this relies on the lock owner running in parallel to the thread attempting to acquire the lock. This is impossible on a single execution core, which is almost certainly why Microsoft treats the count as 0 in such environments. Even with multiple cores, it's quite possible that the lock owner is not running when another thread attempts to acquire the lock, and in such cases the optimal spin count (for that attempt) is still 0.
2: with simultaneous execution, the optimal spin count is still hardware dependent. Different processors will take different amounts of time to perform similar operations. They have different instruction sets (the ARM I work with most doesn't have an integer divide instruction), different cache sizes, the OS will have different pages in memory... Decrementing the spin count may take a different amount of time on a load-store architecture than on an architecture in which arithmetic instructions can access memory directly. Even on the same processor, the same task will take different amounts of time, depending on (at least) the contents and organization of the memory cache.
If the optimal spin count with simultaneous execution is infinite, then the pthread_spin_* functions should do what you're after. If it is not, then use the pthread_mutex_* functions.
For a high-level, cross-platform threading library or an
implementation of a synchronized block, is having a small amount of
spinning before triggering a context switch a good default?
One would think so. Many moons ago, Solaris 2.x implemented adaptive locks, which did exactly this - spin for a while, if the mutex is held by a thread executing on another CPU or block otherwise.
Obviously, it makes no sense to spin on single-CPU systems.