Lightweight multithreads processes
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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.

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Lightweight (Multithreads) Processes

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Lightweight multithreads processes

Lightweight (Multithreads)Processes


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.

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.


Lightweight multithreads processes

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.


Lightweight multithreads processes

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.


Why use concurrency

Why use concurrency ?

  • Life would be simpler without concurrency. Who needs it:

  • Multiprocessing (simultaneous points of execution).

  • Driving slow devices such as disks, networks, terminals and printers. The program is doing some other useful work while waiting for the device.

  • Building distributed systems. Shared network servers. Server is willing to service requests from multiple clients. Use of multiple threads allows the server to handle clients’ requests in parallel.


Lightweight multithreads processes

“Lighter” than ordinary processes.

They represent a thread of control not bound to an address

space.

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.


Lightweight multithreads processes

  • Thread creation and destruction, status gathering, scheduling manipulation, suspend and resume.

  • Multiplexing the clock (any number of threads can sleep concurrently).

  • Individualized context switching. It is possible to specify that a given set of threads will touch floating point registers and only those threads will context switch these registers.

  • Monitors and condition variables to synchronize threads.

  • Extended rendezvous (message send-receive-reply) between threads.


Lightweight multithreads processes

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.


Threads

Threads

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.


Lightweight multithreads processes

LWP or threads are scheduled by priority. The highest priority non-blocked thread is executing.

Within priority, threads execute on FCFS basis.

Example 1


Lightweight multithreads processes

#include <lwp/lwp.h>

#include <lwp/stackdep.h>

int lwp_create(tid, func, prio, flags, stack, nargs, arg1, ..., argn)

thread_t *tid;

void (*func)();

int prio;

int flags;

stkalign_t *stack;

int nargs;

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.


Lightweight multithreads processes

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.


Lightweight multithreads processes

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).


Lightweight multithreads processes

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).


Stack size

Stack Size

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.


Lightweight multithreads processes

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.


Lightweight multithreads processes

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.


Protecting against stack overflow

Protecting against stack overflow

  • Lwp_newstk() automatically allocated protected stacks. Reference beyond the stack limit will generate a SIGSEGV event.

  • There are two ways to check stack integrity when not using lwp_newstk():

  • Use the check() macro at the beginning of each procedure (before any locals are assigned), in conjunction with lwp_checkstkset(). If the procedure exceeds the thread stack limit, the procedure will return and set a global variable.

  • Use lwp_stkcswset(). This enables stack checking on context switching. This is transparent to the client programs. It may not


Lightweight multithreads processes

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.

Example 2


Lightweight multithreads processes

UNIX command limit

cputime unlimited

filesize unlimited

datasize 2097152 kbytes

stacksize 65536 kbytes

coredumpsize unlimited

memoryuse 247848 kbytes

vmemoryuse 2097152 kbytes

descriptors 200

threads 1024


Coroutines

Coroutines

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().


Lightweight multithreads processes

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.


Lightweight multithreads processes

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.


Custom schedulars

Custom Schedulars

  • There are three ways to provide scheduling control of threads to the client.

  • Do nothing and provide the client a pointer to a thread context which can be scheduled at will. The problem: the client has to build its own scheduler from scratch.

  • Provide single scheduling policy with very little client control over what runs next. The UNIX system provides such a policy. It is difficult to implement policies that take into account the differing response time needs of client threads.

  • Middle ground: Default scheduling policy, but enough primitives are provided that it is possible to construct a wide variety of scheduling policies. (avoid the two above problems).


Lightweight multithreads processes

To custom-build your own scheduler we can use the following primitives:


Lightweight multithreads processes

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().


Lightweight multithreads processes

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.


Lightweight multithreads processes

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.


Lightweight multithreads processes

lwp_yield(), lwp_sleep(), lwp_resched(), lwp_join(),

lwp_suspend(), lwp_resume() return:

0 on success.

-1 on failure.


Lightweight multithreads processes

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.


Context switching

Context Switching

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

Messages

  • There are two types of process synchronization in use:

  • Rendezvous - easy to use interprocess-communication facilities (RPC). It supports communication across different address spaces. Higher-level than monitors because both data transmission and synchronization are combined into a single concept. It is natural to map asynchronous events into higher-level abstractions since messages are reliable and conditions are not.

  • Monitor - familiarity to UNIX system programmers via similarity to sleep() and wakeup() in the kernel.

Messages vs. Monitors


Lightweight multithreads processes

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.


Rendezvous semantics

Rendezvous Semantics

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.


Lightweight multithreads processes

msg_send, msg_recv, msg_reply, msg_recvall, msg_enumsend,msg_enumrecv - LWP send and receive messages

SYNOPSIS

#include <lwp/lwp.h>

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 */


Lightweight multithreads processes

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 */


Lightweight multithreads processes

int msg_reply(sender)

thread_t sender; /*agent id or thread id */

int msg_enumsend(vec, maxsize)

thread_t vec[]; /*list of blocked senders */

int maxsize;

int msg_enumrecv(vec, maxsize)

thread_t vec[]; /*list of blocked receivers */

int maxsize;

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 */

thread_t *sender;

caddr_t *arg;

int *argsize;

caddr_t *res;

int *ressize;

struct timeval *timeout;


Lightweight multithreads processes

DESCRIPTION

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().


Lightweight multithreads processes

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.


Lightweight multithreads processes

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.


Lightweight multithreads processes

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 and threads

Messages and Threads

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.


Lightweight multithreads processes

There is no other form of selection available.

Example 6 demonstrates basic message passing.


Intelligent severs

Intelligent Severs

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.


Agents

Agents

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.


Lightweight multithreads processes

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.


System calls

System Calls

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


Using the non blocking i o library

Using the Non-Blocking I/O library

Examples 8,9 shows how to use the non-blocking I/O library.


Lightweight multithreads processes

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


Lightweight multithreads processes

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:

SOCK_STREAM

SOCK_DGRAM

SOCK_RAW

SOCK_SEQPACKET

SOCK_RDM

A SOCK_DGRAM socket supports datagrams (connectionless, unreliable messages of a fixed (typically small) maximum length).


Lightweight multithreads processes

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.


Monitors and conditions

Monitors and Conditions

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.


Lightweight multithreads processes

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.


Lightweight multithreads processes

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.


Programming with monitors

Programming with Monitors

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.


Lightweight multithreads processes

The wait code looks as:

mon_enter(m)

…;

while (!state)

cv_wait(cv);

…;

mon_exit(m);

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


Lightweight multithreads processes

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.


Lightweight multithreads processes

cv_create, cv_destroy, cv_wait, cv_notify, cv_broadcast, cv_send, cv_enumerate, cv_waiters, SAMECV - manage LWP condition variables

#include <lwp/lwp.h>

cv_t cv_create(cv, mid)

cv_t *cv;

mon_t mid;

int cv_destroy(cv)

cv_t cv;

int cv_wait(cv)

cv_t cv;

int cv_notify(cv)

cv_t cv;

int cv_send(cv, tid)

cv_t cv;

lwp_t tid

int cv_broadcast(cv)

cv_t cv;


Lightweight multithreads processes

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 */

SAMECV(c1, c2)


Lightweight multithreads processes

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.


Lightweight multithreads processes

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.


Lightweight multithreads processes

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().


Lightweight multithreads processes

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.


Monitor example

Monitor Example

In this example we describe the producer consumer thread, synchronizing with condition variables.


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