Lightweight (Multithreads) Processes. Many experimental OS, and some commercial ones, have recently included support for concurrent programming. The most popular is to allow multiple lwp “threads” within a single address space, used from within a single program.
Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author.While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server.
Many experimental OS, and some commercial ones, have recently included support for concurrent programming. The most popular is to allow multiple lwp “threads” within a single address space, used from within a single program.
Concurrent programming has many problems that do not occur in sequential programming.
A thread is a single sequential flow of control. In a high level language we program a thread using procedures, where the procedure calls the traditional stack.
Having “multiple threads” in a program means that at any instant the program has multiple points of execution, one in each of its threads.
The programmer view the threads as executing simultaneously, as if the computer has many processors as there are threads.
Having threads execute within a “single address space” means that the computer’s addressing hardware permit the threads to read and write the same memory locations. In high-level language, this corresponds that the off-stack (global) variables are shared among all the threads of the program. Each thread executes on a separate call stack with its own separate local variables.
The programmer is responsible for using the synchronization mechanisms of the thread facility to ensure that the shared memory is accessed in a manner that will give the correct answer.
Thread facilities are “lightweight”. This means that thread creation, existence, destruction and synchronization primitives are cheap enough that the programmer will use them for all his concurrency needs.
In most conventional OS we have multiple separate processes, running in separate address space. This tends to be expansive to set up, and the costs of communicating between address spaces are high.
“Lighter” than ordinary processes.
They represent a thread of control not bound to an address
Threads operate more efficiently than ordinary SunOs
operating system processes, because threads communicate via
shared memory instead a file system.
Threads can share a common address space. Then the cost of creating tasks and intertask communication is less than the cost of using more “heavyweight” primitives.
Scheduling is by default, priority based, and non-preemptive within a priority.
It is possible to write your own scheduler. A high-priority thread may periodically reshuffle the queue f time-sliced threads which
are at lower priority.
Threads currently lack kernel support, so system calls still serialize thread activity.
When a set of threads are running, it is assumed that they all share memory.
The lwp mechanism allows several threads of control to share the same address space.
Each lwp process is represented by a procedure that will be converted into a thread by the lwp_create().
Once created, a thread is an independent entity, with its own stack
as supplied by the creator.
A collection of threads runs within a single ordinary process. The collection is called a pod.
LWP or threads are scheduled by priority. The highest priority non-blocked thread is executing.
Within priority, threads execute on FCFS basis.
int lwp_create(tid, func, prio, flags, stack, nargs, arg1, ..., argn)
int arg1, ..., argn;
lwp_create() creates a lightweight process which starts at address func and has stack segment stack. If stack is NULL, the thread is created in a suspended state. And prio is the scheduling priority of the thread (higher priorities are favored by the scheduler). The identity of the new thread is filled in the reference parameter tid. flags describes some options on the new thread.
The first time a lwp primitive is used, the lwp library automatically converts the caller (i.e., main) into a thread with the highest available scheduling priority.
Scheduling is, by default, non-preemptive within a priority, and within a priority, threads enter the run queue on a FIFO basis (that is, whenever a thread becomes eligible to run,it goes to the end of the run queue of its particular priority). Thus, a thread continues to run until it voluntarily relinquishes control or an event (including thread creation) occurs to enable a higher priority thread. Some primitives may cause the current thread to block, in which case the unblocked thread with the highest priority runs next. When several threads are created with the same priority, they are queued for execution in the order of creation.
There is no concept of ancestry in threads: the creator of a thread has no special relation to the thread it created.
When all threads have died, the pod terminates.
lwp_destroy() is a way to explicitly terminate a thread or agent (instead of having an executing thread "fall though",which also terminates the thread). tid specifies the id of the thread or agent to be terminated. If tid is SELF, the invoking thread is destroyed. Upon termination, the resources (messages, monitor locks, agents) owned by the thread are released, in some cases resulting in another thread being notified of the death of its peer (by having a blocking primitive become unblocked with an error indication).
lwp_newstk() returns a cached stack that is suitable for use in an lwp_create() call. lwp_setstkcache() must be called (once) prior to any use of lwp_newstk. If running under SunOS 4.x, the stacks allocated by lwp_newstk() will be red-zone protected (an attempt to reference below the stack bottom will result in a SIGSEGV event).
How big to make the threads stacks ? Then, we can decide if we need protection against exceeding this limit.
Unix presents the same problem to the user.
Allocating large stacks is not a performance drain because pages are only allocated if actually used. Hence, we can allocate very large stacks.
Stacks are problematical with lightweight processes. What is desired is that stacks for each thread are red-zone protected so that one thread's stack does not unexpectedly grow into the stack of another. In addition, stacks should be of
infinite length, grown as needed. The process stack is a maximum-sized segment. This stack is red- zone protected, and you can even try to extend it beyond its initial maximum size in some cases.
The stack used by main() is the same stack that the system allocates for a process on fork(). For allocating other thread stacks, the client is free to use any statically or dynamically allocated memory (using memory from main()'s stack is subject to the stack resource limit for any process
created by fork()).
Threads created with stacks from lwp_newstk() should not use the NOLASTRITES flag. If they do, cached stacks will not be returned to the cache when a thread dies.
detect error until after the stack limit has been exceeds.
With lwp_stkcswset() an error is considered fatal.
CHECK() detects errors before any damage is done, so error recovery is possible.
It is possible to assign a statically allocated stack to a thread.
UNIX command limit
datasize 2097152 kbytes
stacksize 65536 kbytes
memoryuse 247848 kbytes
vmemoryuse 2097152 kbytes
It is possible to use threads as pure coroutines: one thread explicitly yields control to another.
Lwp_yield() allows a thread to yield to either a specific thread at the same priority, or the next thread in line at the same priority.
Since we are using coroutines, a single priority (MINPRIO) is sufficient and we do not increase the number of available priorities with pod_setmaxpri().
If we have lwp_yield(THREADNULL) then the current thread goes to the end of its scheduling queue.
When a specific yield is performed, the specified thread jumps in front of the current one at a front of the scheduling queue.
Example 3: Three coroutines: main(), coroutine(), other().
1-7 have to be printed.
lwp_self() returns the ID of the current thread in tid. This is the only way to retrieve the identity of main.
lwp_yield() allows the currently running thread to voluntarily relinquish control to another thread with the same scheduling priority. If tid is SELF, the next thread in the same priority queue of the yielding thread will run and the current thread will go the end of the scheduling queue.
Otherwise, it is the ID of the thread to run next, and the current thread will take second place in the scheduling queue.
To custom-build your own scheduler we can use the following primitives:
lwp_sleep() blocks the thread executing this primitive for at least the time specified by timeout.
Scheduling of threads is, by default, preemptive (higher priorities preempt lower ones) across priorities and non-preemptive within a priority.
lwp_resched() moves the front thread for a given priority to the end of the scheduling queue. Thus, to achieve a preemptive round-robin scheduling discipline, a high priority thread can periodically wake up and shuffle the queue of threads at a lower priority.
lwp_resched() does not affect threads which are blocked. If the priority of the rescheduled thread is the same as that of the caller, the effect is the same as lwp_yield().
lwp_setpri() is used to alter (raise or lower) the scheduling priority of the specified thread. If tid is SELF, the priority of the invoking thread is set. Note: if the priority of the affected thread becomes greater than that of the caller and the affected thread is not blocked, the caller will not run next. lwp_setpri() can be used on either blocked or unblocked threads.
lwp_suspend() makes the specified thread ineligible to run. If tid is SELF, the caller is itself suspended.
lwp_resume() undoes the effect of lwp_suspend(). If a blocked thread is suspended, it will not run until it has been unblocked as well as explicitly made eligible to run using lwp_resume(). By suspending a thread, one can safely examine it without worrying that its execution-time state will change.
Note: When scheduling preemptively, be sure to use monitors to protect shared data structures such as those used by the standard I/O library.
lwp_yield(), lwp_sleep(), lwp_resched(), lwp_join(),
lwp_suspend(), lwp_resume() return:
0 on success.
-1 on failure.
Example 4: how to build round-robin time sliced schedular.
To have a high priority thread that acts as a scheduler, with the other threads at a lower priority. This scheduler thread sleeps for the desired quantum. When the quantum expires, the scheduler issues a lwp_reached() command for the priority of the scheduled threads. This causes a reshuffling of the run queue at that priority.
A thread can pretend to be the only activity executing on its machine even though many threads are running. The LWP library provides this illusion. LWP library provides for the context switches between threads.
Messages vs. Monitors
With rendezvous, a context switch is always required.
With monitors, a context switch is only necessary if the monitor lock is busy at the time of access.
The LWP library provides both.
To use messages, one thread issues a msg_send() and another thread issues a msg_recv(). Whichever thread gets to the corresponding primitive first waits for the other, hence the term rendezvous.
When rendezvous takes place, the sender remains blocked until the receiver decides to issue a msg_reply(). Immediately after msg_reply() returns, both threads are unblocked.
msg_send, msg_recv, msg_reply, msg_recvall, msg_enumsend,msg_enumrecv - LWP send and receive messages
int msg_send(dest,arg,argsize, res, ressize)
thread_t dest; /* destination thread */
caddr_t arg; /* argument buffer */
int argsize; /* size of argument buffer */
caddr_t res; /* result buffer */
int ressize; /* size of result buffer */
int msg_recv(sender,arg,argsize, res, ressize, timeout)
thread_t *sender; /* value-result: sending thread or agent */
caddr_t *arg; /* argument buffer */
int *argsize; /* argument size */
caddr_t *res; /* result buffer */
int *ressize; /* result size */
struct timeval *timeout; /* POLL, INFINITY, else timeout */
thread_t sender; /*agent id or thread id */
int msg_enumsend(vec, maxsize)
thread_t vec; /*list of blocked senders */
int msg_enumrecv(vec, maxsize)
thread_t vec; /*list of blocked receivers */
int MSG_RECVALL(sender, arg, argsize, res, ressize, timeout) /* Has the same parameters as msg_recv() but
ensures that the sender is properly initialized to allow receipt from
any sender. It returns the result from msg_recv */
struct timeval *timeout;
Each thread queues messages addressed to it as they arrive. Threads may either specify that a particular sender's message is to be received next, or that any sender's message
may be received next.
msg_send() specifies a message buffer and a reply buffer, and initiates one half of a rendezvous with the receiver. The sender will block until the receiver replies using
msg_reply(). msg_recv() initiates the other half of a rendezvous and blocks the invoking thread until a corresponding msg_send()is received. When unblocked by msg_send(), the
receiver may read the message and generate a reply by filling in the reply buffer and issuing msg_reply().
msg_reply() unblocks the sender. Once a reply is sent, the receiver should no longer access either the message or reply buffer.
In msg_send(), argsize specifies the size in bytes of the argument buffer argbuf, which is intended to be a read-only (to the receiver) buffer. ressize specifies the size in
bytes of the result buffer resbuf, which is intended to be a write-only (to the receiver) buffer. dest is the thread that is the target of the send.
msg_recv() blocks the receiver until:
A message from the agent or thread bound to sender has been sent to the receiver or,
Sender points to a THREADNULL-valued variable and any message has been sent to the receiver from a thread or agent, or,
After the time specified by timeout elapses and no message is received.
It is the responsibility of the sender to provide the buffer space both for a message to be sent to the receiver, and for a reply message from the receiver.
While the sender is blocked, the receiver has access to the buffers provided by the sender.
Messages are sent to threads, and each thread has exactly one queue associated with it to that receives messages.
We could have provided message queues (ports) as objects not bound to processes. This would give more flexibility, but would require a more complex functionality. It will also complicate the implementation.
To receive a rendezvous request, a process specifies the identity of the sending thread it wishes to rendezvous with.
Optionally, a receiver may specify that any sender will do.
There is no other form of selection available.
Example 6 demonstrates basic message passing.
Because the reply can be done at any time, a receiver can receive a number of messages before replying to them. This enables to implement complex servers.
Example 7 demonstrates how processes send requests in a random order to a server thread. This server serializes the requests and process them in the order associated with the request.
Because of the random nature of interrupts, it is hard to understand programs to deal with them. The LWP library provides a simple way to transform asynchronous events into synchronous ones.
A message paradigm was chosen (instead of monitor) to map interrupts because an interrupt can not wait for a monitor lock if held by a client.
With asynchronous interrupts, an event causes a context switch within the same thread. With LWP’s, a thread must synchronously randezvous within interrupt. Thus, to have an event that do something asynchronously, it is necessary to use a separate thread to handle it.
To simulate typical UNIX signal handling, we have to create two threads, one thread to represent the main program, and another thread at a higher priority to represent the signal handler. The latter thread would have an agent set up to receive signals.
The agent mechanism is provided to map synchronous events into messages to a lightweight process.
A message from an agent looks exactly like a message from another thread. When agent is created, we provide a portion of the pod’s address space for the agent to store its message.
You can not receive the next message from an agent until you reply to the current one.
A set of heavyweight processes can execute concurrently system calls in the kernel. For example, 3 heavyweights processes can concurrently initiate writes to the same device. This is not the case for the lightweight threads.
However, there is no general solution to the problem of having several threads execute system calls concurrently until the LWP primitives are made available as true system calls operating on a set of descriptors.
The use of non-blocking I/O library can help by automatically blocking a thread attempting any I/O until such I/O is likely to succeed immediately.
Non-Blocking I/O Library
Examples 8,9 shows how to use the non-blocking I/O library.
int socket(domain, type, protocol)
int domain, type, protocol;
socket()creates an endpoint for communication and returns a descriptor.
The domain parameter specifies a communications domain within which communication will take place; this selects the protocol family which should be used. The protocol family generally is the same as the address family for the addresses supplied in later operations on the socket. These families are defined in the include file <sys/socket.h>.
The currently understood formats are
PF_UNIX (UNIX system internal protocols),
PF_INET (ARPA Internet protocols), and
PF_IMPLINK (IMP "host at IMP" link layer).
The socket has the indicated type, which specifies the semantics of communication. Currently defined types are:
A SOCK_DGRAM socket supports datagrams (connectionless, unreliable messages of a fixed (typically small) maximum length).
The protocal specifies a particular protocol to be used with the socket. Normally only a single protocol exists to support a particular socket type within a given protocol family. However, it is possible that many protocols may exist, in which case a particular protocol must be specified in this manner. The protocol number to use is particular to
the "communication domain" in which communication is to take place.
The monitor-condition variable paradigm is close to kernel programmers because of the analogue to sleep() and wakeup() in the UNIX system kernel.
A monitor implements a critical section. This is a reentrant code in which access is serialized. As a result, shared data accessed by this code is protected against races.
Once a thread is executing within a monitor, other threads block until that monitor is exited. When thread priorities are equal, they are queued on a FCFS basis for access to the monitor. This ensures fair, serial access to the protected data.
As an example, a producer and consumer thread may use a monitor to protect access to a buffer of data being produced or consumed. When the producer has filled the buffer, it must wait for the consumer to drain the buffer. The synchronization is provided by condition variables.
When a thread waits on a condition, it atomically gives up the monitor and blocks pending a notification. The result of the notification is that the blocked thread will eventually reacquire the monitor in order to access the buffer again.
Within the LWP library, most critical sections are implemented by disabling the scheduler (and not by disabling the interrupts) for the duration of the critical section.
If an interrupt arrives during a critical section, it is processed only to the point of saving the volatile interrupt state. At the end of a critical section, if there are any accumulated events, scheduling decisions are made based upon the agents associated with the events.
Typically, there is some state associated with a condition. When the state acquires a given value, a thread can take some action. Otherwise, it will wait until the state changes. For example, if the buffer is full, a thread writing to the buffer will wait until the state of the buffer indicates that is no longer full.
Another thread reading from the buffer will cooperate by notifying any waiting thread when the buffer is no longer full. Because the buffer state is accessed by several threads, it is protected by a monitor. Otherwise, a thread could decide to wait for a state change, only to have the state change before the wait can be executed, resulting in deadlock. Therefore, both the waiter and the notifier must access the state in a monitor, and the wait primitive (cv_wait) must atomically release the monitor.
The wait code looks as:
The while loop is there because if there are several threads waiting in the monitor when the condition is broadcast and all of them wake up.
The first thread to gain entry to the monitor may alter the state, invalidating it for the other awakened threads.
In the producer/consumer example if two producers are awakened
because the buffer is no longer full, the first one may fill the buffer again and wait, leaving the second one to run. The second producer must not add to the buffer now, because it is full again.
cv_create, cv_destroy, cv_wait, cv_notify, cv_broadcast, cv_send, cv_enumerate, cv_waiters, SAMECV - manage LWP condition variables
cv_t cv_create(cv, mid)
int cv_send(cv, tid)
int cv_enumerate(vec, maxsize)
cv_t vec; /* will contain list of all conditions */
int maxsize; /* maximum size of vec */
int cv_waiters(cv, vec, maxsize)
cv_t cv; /* condition variable being interrogated */
thread_t vec; /* which threads are blocked on cv */
int maxsize; /* maximum size of vec */
Condition variables are useful for synchronization within monitors. By waiting on a condition variable, the currently-held monitor (a condition variable must always be
used within a monitor) is released atomically and the invoking thread is suspended. When monitors are nested, monitor locks other than the current one are retained by the thread.
At some later point, a different thread may awaken the waiting thread by issuing a notification on the condition variable. When the notification occurs, the waiting thread will queue to reacquire the monitor it gave up. It is possible to have different condition variables operating within the same monitor to allow selectivity in waking up threads.
cv_create() creates a new condition variable (returned in cv) which is bound to the monitor specified by mid. It is illegal to access (using cv_wait(), cv_notify(), cv_send() or cv_broadcast()) a condition variable from a monitor other than the one it is bound to. cv_destroy() removes a condition variable.
cv_wait() blocks the current thread and releases the monitor lock associated with the condition (which must also be the monitor lock most recently acquired by the thread). Other monitor locks held by the thread are not affected. The blocked thread is enqueued by its scheduling priority on the condition.
cv_notify() awakens at most one thread blocked on the condition variable and causes the awakened thread to queue for access to the monitor released at the time it waited on the
condition. It can be dangerous to use cv_notify() if there is a possibility that the thread being awakened is one of several threads that are waiting on a condition variable and the awakened thread may not be the one intended. In this case, use of cv_broadcast() is recommended.
cv_broadcast() is the same as cv_notify() except that all threads blocked on the condition variable are awakened.
cv_notify() and cv_broadcast() do nothing if no thread is waiting on the condition. For both cv_notify() and cv_broadcast(), the currently held monitor must agree with the one bound to the condition by cv_create().
cv_send() is like cv_notify() except that the particular thread tid is awakened. If this thread is not currently blocked on the condition, cv_send() reports an error.
cv_enumerate() lists the ID of all of the condition variables. The value returned is the total number of condition variables. The vector supplied is filled in with the ID's
of condition variables. cv_waiters() lists the ID's of the threads blocked on the condition variable cv and returns the number of threads blocked on cv.
SAMECV is a convenient predicate used to compare two condition variables for equality.
In this example we describe the producer consumer thread, synchronizing with condition variables.