Operating Systems

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2.2.2: Thread Usage

Often, when a process A is blocked (say for I/O) there is still computation that can be done. Another process B can't do this computation since it doesn't have access to the A's memory. But two threads in the same process do share memory so that problem doesn't occur.

An important modern example is a multithreaded web server. Each thread is responding to a single WWW connection. While one thread is blocked on I/O, another thread can be processing another WWW connection.
Question: Why not use separate processes, i.e., what is the shared memory?
Ans: The cache of frequently referenced pages.

A common organization is to have a dispatcher thread that fields requests and then passes this request on to an idle thread.

Another example is a producer-consumer problem (c.f. below) in which we have 3 threads in a pipeline. One thread reads data from an I/O device into a buffer, the second thread performs computation on the input buffer and places results in an output buffer, and the third thread outputs the data found in the output buffer. Again, while one thread is blocked the others can execute.

Question: Why does each thread block?


  1. The first thread blocks waiting for the device to finish reading the data. It also blocks if the input buffer is full.

  2. The second thread blocks when either the input buffer is empty or the output buffer is full.

  3. The third thread blocks when the output device is busy (it might also block waiting for the output request to complete, but this is not necessary). It also blocks if the output buffer is empty.

Homework: 9.

A final (related) example is that an application that wishes to perform automatic backups can have a thread to do just this. In this way the thread that interfaces with the user is not blocked during the backup. However some coordination between threads may be needed so that the backup is of a consistent state.

2.2.3: Implementing threads in user space

Write a (threads) library that acts as a mini-scheduler and implements thread_create, thread_exit, thread_wait, thread_yield, etc. The central data structure maintained and used by this library is the thread table, the analogue of the process table in the operating system itself.



Possible methods of dealing with blocking system calls

2.2.4: Implementing Threads in the Kernel

Move the thread operations into the operating system itself. This naturally requires that the operating system itself be (significantly) modified and is thus not a trivial undertaking.

2.2.5: Hybrid Implementations

One can write a (user-level) thread library even if the kernel also has threads. This is sometimes called the M:N model since M user mode threads run on each of N kernel threads. Then each kernel thread can switch between user level threads. Thus switching between user-level threads within one kernel thread is very fast (no context switch) and we maintain the advantage that a blocking system call or page fault does not block the entire multi-threaded application since threads in other processes of this application are still runnable.

2.2.6: Scheduler Activations


2.2.7: Popup Threads

The idea is to automatically issue a thread-create system call upon message arrival. (The alternative is to have a thread or process blocked on a receive system call.) If implemented well, the latency between message arrival and thread execution can be very small since the new thread does not have state to restore.

Making Single-threaded Code Multithreaded

Definitely NOT for the faint of heart.

2.3: Interprocess Communication (IPC) and Coordination/Synchronization

2.3.1: Race Conditions

A race condition occurs when two (or more) processes are about to perform some action. Depending on the exact timing, one or other goes first. If one of the processes goes first, everything works, but if another one goes first, an error, possibly fatal, occurs.

Imagine two processes both accessing x, which is initially 10.

Homework: 18.

2.3.2: Critical sections

We must prevent interleaving sections of code that need to be atomic with respect to each other. That is, the conflicting sections need mutual exclusion. If process A is executing its critical section, it excludes process B from executing its critical section. Conversely if process B is executing is critical section, it excludes process A from executing its critical section.

Requirements for a critical section implementation.

  1. No two processes may be simultaneously inside their critical section.

  2. No assumption may be made about the speeds or the number of CPUs.

  3. No process outside its critical section (including the entry and exit code)may block other processes.

  4. No process should have to wait forever to enter its critical section.

2.3.3 Mutual exclusion with busy waiting

The operating system can choose not to preempt itself. That is, we do not preempt system processes (if the OS is client server) or processes running in system mode (if the OS is self service). Forbidding preemption for system processes would prevent the problem above where x<--x+1 not being atomic crashed the printer spooler if the spooler is part of the OS.

But simply forbidding preemption while in system mode is not sufficient.

Software solutions for two processes

Initially P1wants=P2wants=false

Code for P1                             Code for P2

Loop forever {                          Loop forever {
    P1wants <-- true         ENTRY          P2wants <-- true
    while (P2wants) {}       ENTRY          while (P1wants) {}
    critical-section                        critical-section
    P1wants <-- false        EXIT           P2wants <-- false
    non-critical-section }                  non-critical-section }

Explain why this works.

But it is wrong! Why?

Let's try again. The trouble was that setting want before the loop permitted us to get stuck. We had them in the wrong order!

Initially P1wants=P2wants=false

Code for P1                             Code for P2

Loop forever {                          Loop forever {
    while (P2wants) {}       ENTRY          while (P1wants) {}
    P1wants <-- true         ENTRY          P2wants <-- true
    critical-section                        critical-section
    P1wants <-- false        EXIT           P2wants <-- false
    non-critical-section }                  non-critical-section }

Explain why this works.

But it is wrong again! Why?

So let's be polite and really take turns. None of this wanting stuff.

Initially turn=1

Code for P1                      Code for P2

Loop forever {                   Loop forever {
    while (turn = 2) {}              while (turn = 1) {}
    critical-section                 critical-section
    turn <-- 2                       turn <-- 1
    non-critical-section }           non-critical-section }

This one forces alternation, so is not general enough. Specifically, it does not satisfy condition three, which requires that no process in its non-critical section can stop another process from entering its critical section. With alternation, if one process is in its non-critical section (NCS) then the other can enter the CS once but not again.

The first example violated rule 4 (the whole system blocked). The second example violated rule 1 (both in the critical section. The third example violated rule 3 (one process in the NCS stopped another from entering its CS).

In fact, it took years (way back when) to find a correct solution. Many earlier “solutions” were found and several were published, but all were wrong. The first correct solution was found by a mathematician named Dekker, who combined the ideas of turn and wants. The basic idea is that you take turns when there is contention, but when there is no contention, the requesting process can enter. It is very clever, but I am skipping it (I cover it when I teach distributed operating systems in V22.0480 or G22.2251). Subsequently, algorithms with better fairness properties were found (e.g., no task has to wait for another task to enter the CS twice).

What follows is Peterson's solution, which also combines turn and wants to force alternation only when there is contention. When Peterson's solution was published, it was a surprise to see such a simple soluntion. In fact Peterson gave a solution for any number of processes. A proof that the algorithm satisfies our properties (including a strong fairness condition) for any number of processes can be found in Operating Systems Review Jan 1990, pp. 18-22.

Initially P1wants=P2wants=false  and  turn=1

Code for P1                        Code for P2

Loop forever {                     Loop forever {
    P1wants <-- true                   P2wants <-- true
    turn <-- 2                         turn <-- 1
    while (P2wants and turn=2) {}      while (P1wants and turn=1) {}
    critical-section                   critical-section
    P1wants <-- false                  P2wants <-- false
    non-critical-section               non-critical-section

Hardware assist (test and set)

TAS(b), where b is a binary variable, ATOMICALLY sets b<--true and returns the OLD value of b.
Of course it would be silly to return the new value of b since we know the new value is true.

The word atomically means that the two actions performed by TAS(x) (testing, i.e., returning the old value of x and setting , i.e., assigning true to x) are inseparable. Specifically it is not possible for two concurrent TAS(x) operations to both return false (unless there is also another concurrent statement that sets x to false).

With TAS available implementing a critical section for any number of processes is trivial.

loop forever {
    while (TAS(s)) {}   ENTRY
    s<--false           EXIT

2.3.4: Sleep and Wakeup

Remark: Tanenbaum does both busy waiting (as above) and blocking (process switching) solutions. We will only do busy waiting, which is easier. Sleep and Wakeup are the simplest blocking primitives. Sleep voluntarily blocks the process and wakeup unblocks a sleeping process. We will not cover these.

Homework: Explain the difference between busy waiting and blocking process synchronization.

2.3.5: Semaphores

Remark: Tannenbaum use the term semaphore only for blocking solutions. I will use the term for our busy waiting solutions. Others call our solutions spin locks.

P and V and Semaphores

The entry code is often called P and the exit code V. Thus the critical section problem is to write P and V so that

loop forever
  1. Mutual exclusion.
  2. No speed assumptions.
  3. No blocking by processes in NCS.
  4. Forward progress (my weakened version of Tanenbaum's last condition).

Note that I use indenting carefully and hence do not need (and sometimes omit) the braces {} used in languages like C or java.

A binary semaphore abstracts the TAS solution we gave for the critical section problem.

The above code is not real, i.e., it is not an implementation of P. It is, instead, a definition of the effect P is to have.

To repeat: for any number of processes, the critical section problem can be solved by

loop forever

The only specific solution we have seen for an arbitrary number of processes is the one just above with P(S) implemented via test and set.

Remark: Peterson's solution requires each process to know its processor number. The TAS soluton does not. Moreover the definition of P and V does not permit use of the processor number. Thus, strictly speaking Peterson did not provide an implementation of P and V. He did solve the critical section problem.

To solve other coordination problems we want to extend binary semaphores.

Both of the shortcomings can be overcome by not restricting ourselves to a binary variable, but instead define a generalized or counting semaphore.

These counting semaphores can solve what I call the semi-critical-section problem, where you premit up to k processes in the section. When k=1 we have the original critical-section problem.

initially S=k

loop forever
    SCS   <== semi-critical-section

Producer-consumer problem

Initially e=k, f=0 (counting semaphore); b=open (binary semaphore)

Producer                         Consumer

loop forever                     loop forever
    produce-item                     P(f)
    P(e)                             P(b); take item from buf; V(b)
    P(b); add item to buf; V(b)      V(e)
    V(f)                             consume-item

2.3.6: Mutexes

Remark: Whereas we use the term semaphore to mean binary semaphore and explicitly say generalized or counting semaphore for the positive integer version, Tanenbaum uses semaphore for the positive integer solution and mutex for the binary version. Also, as indicated above, for Tanenbaum semaphore/mutex implies a blocking primitive; whereas I use binary/counting semaphore for both busy-waiting and blocking implementations. Finally, remember that in this course we are studying only busy-waiting solutions.

My Terminology
Busy waitblock/switch
critical(binary) semaphore(binary) semaphore
semi-criticalcounting semaphorecounting semaphore
Tanenbaum's Terminology
Busy waitblock/switch
criticalenter/leave regionmutex
semi-criticalno namesemaphore

2.3.7: Monitors


2.3..8: Message Passing

Skipped. You can find some information on barriers in my lecture notes for a follow-on course (see in particular lecture #16).