Process synchronisation. Chapter .......

Chapter 6: Process Synchronization

6.2 Silberschatz, Galvin and Gagne ©2005
Operating System Concepts
Module 6: Process Synchronization
 Background
 The Critical-Section Problem
 Peterson’s Solution
 Synchronization Hardware
 Semaphores
 Classic Problems of Synchronization
 Monitors
 Synchronization Examples
 Atomic Transactions

Background
 Concurrent access to shared data may result in data inconsistency
 Maintaining data consistency requires mechanisms to ensure the
orderly execution of cooperating processes
 Suppose that we wanted to provide a solution to the consumer-
producer problem that fills all the buffers. We can do so by having an
integer count that keeps track of the number of full buffers. Initially,
count is set to 0. It is incremented by the producer after it produces a
new buffer and is decremented by the consumer after it consumes a
buffer.

Producer
while (true)
/* produce an item and put in nextProduced
while (count == BUFFER_SIZE)
; // do nothing
buffer [in] = nextProduced;
in = (in + 1) % BUFFER_SIZE;
count++;
}

Consumer
while (1)
{
while (count == 0)
; // do nothing
nextConsumed = buffer[out];
out = (out + 1) % BUFFER_SIZE;
count--;
/* consume the item in nextConsumed
}

Race Condition
 count++ could be implemented as
register1 = count
register1 = register1 + 1
count = register1
 count-- could be implemented as
register2 = count
register2 = register2 - 1
count = register2
 Consider this execution interleaving with “count = 5” initially:
S0: producer execute register1 = count {register1 = 5}
S1: producer execute register1 = register1 + 1 {register1 = 6}
S2: consumer execute register2 = count {register2 = 5}
S3: consumer execute register2 = register2 - 1 {register2 = 4}
S4: producer execute count = register1 {count = 6 }
S5: consumer execute count = register2 {count = 4}

Solution to Critical-Section Problem
1. Mutual Exclusion - If process Pi is executing in its critical section,
then no other processes can be executing in their critical sections
2. Progress - If no process is executing in its critical section and
there exist some processes that wish to enter their critical section,
then the selection of the processes that will enter the critical
section next cannot be postponed indefinitely
3. Bounded Waiting - A bound must exist on the number of times
that other processes are allowed to enter their critical sections
after a process has made a request to enter its critical section and
before that request is granted
 Assume that each process executes at a nonzero speed
 No assumption concerning relative speed of the N processes

Solution to Critical-Section Problem
 Two approaches to handle critical sections in operating systems:
 Preemptive kernels – allows a process to be preempted while it is
running in kernel mode.
 Non-preemptive kernels – does not allow a process running in
kernel mode to be preempted.
 Free from race conditions on kernel data structures
 A preemptive kernel is more suitable for real-time processing.
 Windows XP and Windows 2000 are nonpreemptive kernels
 Prior to Linux 2.6, the Linux kernel was nonpreemptive as well.

Peterson’s Solution
 Two process solution
 Assume that the LOAD and STORE instructions are atomic;
that is, cannot be interrupted.
 The two processes share two variables:
 int turn;
 Boolean flag[2]
 The variable turn indicates whose turn it is to enter the
critical section.
 The flag array is used to indicate if a process is ready to
enter the critical section. flag[i] = true implies that process Pi
is ready!

Algorithm for Process Pi
do {
flag[i] = TRUE;
turn = j;
while ( flag[j] && turn == j);
CRITICAL SECTION
flag[i] = FALSE;
REMAINDER SECTION
} while (TRUE);

Peterson’s Solution (Cont.)
 Provable that the three CS requirement are met:
1. Mutual exclusion is preserved
Pi enters CS only if:
either flag[j] = false or turn = i
2. Progress requirement is satisfied
3. Bounded-waiting requirement is met

Synchronization Hardware
 Many systems provide hardware support for critical section
code
 Uniprocessors – could disable interrupts
 Currently running code would execute without
preemption
 Generally too inefficient on multiprocessor systems
 Operating systems using this not broadly scalable
 Modern machines provide special atomic hardware
instructions
 Atomic = non-interruptable
 Either test memory word and set value
 Or swap contents of two memory words

TestAndndSet Instruction
 Definition:
boolean TestAndSet (boolean *target)
{
boolean rv = *target;
*target = TRUE;
return rv:
}
1. Executed atomically
2. Returns the original value of passed parameter
3. Set the new value of passed parameter to “TRUE”.
4. If two TestAndSet() instructions are executed simultaneously (each on
different CPU), they will be executed sequentially in same arbitrary
order.

Solution using test_and_set()
 We can implement mutual exclusion by shared Boolean
variable lock, initialized to FALSE
 Solution:
do {
while (test_and_set(&lock))
; /* do nothing */
/* critical section */
lock = false;
/* remainder section */
} while (true);

Swap Instruction
 Swap() instruction operates on the contents of two words
 Definition:
void Swap (boolean *a, boolean *b)
{
boolean temp = *a;
*a = *b;
*b = temp:
}

Solution using Swap
 Mutual exclusion: Shared Boolean variable lock initialized to
FALSE; Each process has a local Boolean variable key.
 Solution:
do {
key = TRUE;
while ( key == TRUE)
Swap (&lock, &key );
// critical section
lock = FALSE;
// remainder section
} while ( TRUE);

Bounded-waiting Mutual Exclusion with test_and_set
 Earlier algorithms satisfy mutual exclusion requirement but not
bounded waiting requirement
 Solution:
do {
waiting[i] = true;
key = true;
while (waiting[i] && key)
key = test_and_set(&lock);
waiting[i] = false;
/* critical section */
j = (i + 1) % n;
while ((j != i) && !waiting[j])
j = (j + 1) % n;
if (j == i)
lock = false;
else
waiting[j] = false;
/* remainder section */
} while (true);

Semaphore
 Synchronization tool that does not require busy waiting
 Semaphore S – integer variable
 Two standard operations modify S: wait() and signal()
 Originally called P() and V()
 Less complicated
 Can only be accessed via two indivisible (atomic) operations
 wait (S) {
while S <= 0
; // no-op
S--;
}
 signal (S) {
S++;
}

Semaphore as General Synchronization Tool
 Counting semaphore – integer value can range over an
unrestricted domain
 Binary semaphore – integer value can range only between 0
and 1; can be simpler to implement
 Also known as mutex locks
 Can implement a counting semaphore S as a binary semaphore
 Provides mutual exclusion
 Semaphore S; // initialized to 1
 wait (S);
Critical Section
signal (S);

Semaphore Implementation
 Must guarantee that no two processes can execute wait () and
signal () on the same semaphore at the same time
 Thus, implementation becomes the critical section problem
where the wait and signal code are placed in the crtical
section.
 Could now have busy waiting in critical section
implementation
 But implementation code is short
 Little busy waiting if critical section rarely occupied
 Note that applications may spend lots of time in critical
sections and therefore this is not a good solution.

Semaphore Implementation with no Busy waiting
 With each semaphore there is an associated waiting queue.
Each entry in a waiting queue has two data items:
 value (of type integer)
 pointer to next record in the list
 Two operations:
 block – place the process invoking the operation on the
appropriate waiting queue.
 wakeup – remove one of processes in the waiting queue
and place it in the ready queue.

Semaphore Implementation with no Busy waiting (Cont.)
 Implementation of wait:
wait (S){
value--;
if (value < 0) {
add this process to waiting queue
block(); }
}
 Implementation of signal:
Signal (S){
value++;
if (value <= 0) {
remove a process P from the waiting queue
wakeup(P); }
}

Deadlock and Starvation
 Deadlock – two or more processes are waiting indefinitely for an
event that can be caused by only one of the waiting processes
 Let S and Q be two semaphores initialized to 1
P0 P1
wait (S); wait (Q);
wait (Q); wait (S);
. .
. .
. .
signal (S); signal (Q);
signal (Q); signal (S);
 Starvation – indefinite blocking. A process may never be removed
from the semaphore queue in which it is suspended.

Classical Problems of Synchronization
 Bounded-Buffer Problem
 Readers and Writers Problem
 Dining-Philosophers Problem

Bounded-Buffer Problem
 N buffers, each can hold one item
 Semaphore mutex initialized to the value 1
 Semaphore full initialized to the value 0
 Semaphore empty initialized to the value N.

Bounded Buffer Problem (Cont.)
 The structure of the producer process
do {
// produce an item
wait (empty);
wait (mutex);
// add the item to the buffer
signal (mutex);
signal (full);
} while (true);

Bounded Buffer Problem (Cont.)
 The structure of the consumer process
do {
wait (full);
wait (mutex);
// remove an item from buffer
signal (mutex);
signal (empty);
// consume the removed item
} while (true);

Readers-Writers Problem
 A data set is shared among a number of concurrent processes
 Readers – only read the data set; they do not perform any
updates
 Writers – can both read and write.
 Problem – allow multiple readers to read at the same time. Only
one single writer can access the shared data at the same time.
 Shared Data
 Data set
 Semaphore mutex initialized to 1.
 Semaphore wrt initialized to 1.
 Integer readcount initialized to 0.

Readers-Writers Problem (Cont.)
 The structure of a writer process
do {
wait (wrt) ;
// writing is performed
signal (wrt) ;
} while (true)

Readers-Writers Problem (Cont.)
 The structure of a reader process
do {
wait (mutex) ;
readcount ++ ;
if (readercount == 1) wait (wrt) ;
signal (mutex)
// reading is performed
wait (mutex) ;
readcount - - ;
if redacount == 0) signal (wrt) ;
signal (mutex) ;
} while (true)

Dining-Philosophers Problem
 Shared data
 Bowl of rice (data set)
 Semaphore chopstick [5] initialized to 1

Dining-Philosophers Problem (Cont.)
 The structure of Philosopher i:
Do {
wait ( chopstick[i] );
wait ( chopStick[ (i + 1) % 5] );
// eat
signal ( chopstick[i] );
signal (chopstick[ (i + 1) % 5] );
// think
} while (true) ;

Problems with Semaphores
 Correct use of semaphore operations:
 signal (mutex) …. wait (mutex)
 wait (mutex) … wait (mutex)
 Omitting of wait (mutex) or signal (mutex) (or both)

Monitors
 A high-level abstraction that provides a convenient and effective
mechanism for process synchronization
 Only one process may be active within the monitor at a time
monitor monitor-name
{
// shared variable declarations
procedure P1 (…) { …. }
…
procedure Pn (…) {……}
Initialization code ( ….) { … }
…
}
}

Schematic view of a Monitor

Condition Variables
 condition x, y;
 Two operations on a condition variable:
 x.wait () – a process that invokes the operation is
suspended.
 x.signal () – resumes one of processes (if any) tha
invoked x.wait ()

Monitor with Condition Variables

Solution to Dining Philosophers
monitor DP
{
enum { THINKING; HUNGRY, EATING) state [5] ;
condition self [5];
void pickup (int i) {
state[i] = HUNGRY;
test(i);
if (state[i] != EATING) self [i].wait;
}
void putdown (int i) {
state[i] = THINKING;
// test left and right neighbors
test((i + 4) % 5);
test((i + 1) % 5);
}

Solution to Dining Philosophers (cont)
void test (int i) {
if ( (state[(i + 4) % 5] != EATING) &&
(state[i] == HUNGRY) &&
(state[(i + 1) % 5] != EATING) ) {
state[i] = EATING ;
self[i].signal () ;
}
}
initialization_code() {
for (int i = 0; i < 5; i++)
state[i] = THINKING;
}
}

Synchronization Examples
 Solaris
 Windows XP
 Linux
 Pthreads

Solaris Synchronization
 Implements a variety of locks to support multitasking,
multithreading (including real-time threads), and multiprocessing
 Uses adaptive mutexes for efficiency when protecting data from
short code segments
 Uses condition variables and readers-writers locks when longer
sections of code need access to data
 Uses turnstiles to order the list of threads waiting to acquire either
an adaptive mutex or reader-writer lock

Windows XP Synchronization
 Uses interrupt masks to protect access to global resources on
uniprocessor systems
 Uses spinlocks on multiprocessor systems
 Also provides dispatcher objects which may act as either mutexes
and semaphores
 Dispatcher objects may also provide events
 An event acts much like a condition variable

Linux Synchronization
 Linux:
 disables interrupts to implement short critical sections
 Linux provides:
 semaphores
 spin locks

Pthreads Synchronization
 Pthreads API is OS-independent
 It provides:
 mutex locks
 condition variables
 Non-portable extensions include:
 read-write locks
 spin locks

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