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Chapter 6: ProcessChapter 6: Process
SynchronizationSynchronization
6.2 Silberschatz, Galvin and GagneOperating System Concepts
Module 6: Process SynchronizationModule 6: Process Synchronization
Background
The Critical-Section Problem
Peterson’s Solution
Synchronization Hardware
Semaphores
Classic Problems of Synchronization
Monitors
Synchronization Examples
Atomic Transactions
6.3 Silberschatz, Galvin and GagneOperating System Concepts
BackgroundBackground
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.
6.4 Silberschatz, Galvin and GagneOperating System Concepts
ProducerProducer
while (true)
/* produce an item and put in nextProduced
while (count == BUFFER_SIZE)
; // do nothing
buffer [in] = nextProduced;
in = (in + 1) % BUFFER_SIZE;
count++;
}
6.5 Silberschatz, Galvin and GagneOperating System Concepts
ConsumerConsumer
while (1)
{
while (count == 0)
; // do nothing
nextConsumed = buffer[out];
out = (out + 1) % BUFFER_SIZE;
count--;
/* consume the item in nextConsumed
}
6.6 Silberschatz, Galvin and GagneOperating System Concepts
Race ConditionRace 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}
6.7 Silberschatz, Galvin and GagneOperating System Concepts
Solution to Critical-Section ProblemSolution 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
6.8 Silberschatz, Galvin and GagneOperating System Concepts
Peterson’s SolutionPeterson’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!
6.9 Silberschatz, Galvin and GagneOperating System Concepts
Algorithm for ProcessAlgorithm for Process PPii
do {
flag[i] = TRUE;
turn = j;
while ( flag[j] && turn == j);
CRITICAL SECTION
flag[i] = FALSE;
REMAINDER SECTION
} while (TRUE);
6.10 Silberschatz, Galvin and GagneOperating System Concepts
Synchronization HardwareSynchronization 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
6.11 Silberschatz, Galvin and GagneOperating System Concepts
TestAndndSet InstructionTestAndndSet Instruction
Definition:
boolean TestAndSet (boolean *target)
{
boolean rv = *target;
*target = TRUE;
return rv:
}
6.12 Silberschatz, Galvin and GagneOperating System Concepts
Solution using TestAndSetSolution using TestAndSet
Shared boolean variable lock., initialized to false.
Solution:
do {
while ( TestAndSet (&lock ))
; /* do nothing
// critical section
lock = FALSE;
// remainder section
} while ( TRUE);
6.13 Silberschatz, Galvin and GagneOperating System Concepts
Swap InstructionSwap Instruction
Definition:
void Swap (boolean *a, boolean *b)
{
boolean temp = *a;
*a = *b;
*b = temp:
}
6.14 Silberschatz, Galvin and GagneOperating System Concepts
Solution using SwapSolution using Swap
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);
6.15 Silberschatz, Galvin and GagneOperating System Concepts
SemaphoreSemaphore
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++;
}
6.16 Silberschatz, Galvin and GagneOperating System Concepts
Semaphore as General Synchronization ToolSemaphore 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);
6.17 Silberschatz, Galvin and GagneOperating System Concepts
Semaphore ImplementationSemaphore 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.
6.18 Silberschatz, Galvin and GagneOperating System Concepts
Semaphore Implementation with no Busy waitingSemaphore 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.
6.19 Silberschatz, Galvin and GagneOperating System Concepts
Semaphore Implementation with no Busy waitingSemaphore Implementation with no Busy waiting
(Cont.)(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); }
}
6.20 Silberschatz, Galvin and GagneOperating System Concepts
Deadlock and StarvationDeadlock 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.
6.21 Silberschatz, Galvin and GagneOperating System Concepts
Classical Problems ofClassical Problems of
SynchronizationSynchronization
Bounded-Buffer Problem
Readers and Writers Problem
Dining-Philosophers Problem
6.22 Silberschatz, Galvin and GagneOperating System Concepts
Bounded-Buffer ProblemBounded-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.
6.23 Silberschatz, Galvin and GagneOperating System Concepts
Bounded Buffer Problem (Cont.)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);
6.24 Silberschatz, Galvin and GagneOperating System Concepts
Bounded Buffer Problem (Cont.)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);
6.25 Silberschatz, Galvin and GagneOperating System Concepts
Readers-Writers ProblemReaders-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.
6.26 Silberschatz, Galvin and GagneOperating System Concepts
Readers-Writers Problem (Cont.)Readers-Writers Problem (Cont.)
The structure of a writer process
do {
wait (wrt) ;
// writing is performed
signal (wrt) ;
} while (true)
6.27 Silberschatz, Galvin and GagneOperating System Concepts
Readers-Writers Problem (Cont.)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)
6.28 Silberschatz, Galvin and GagneOperating System Concepts
Dining-Philosophers ProblemDining-Philosophers Problem
Shared data
Bowl of rice (data set)
Semaphore chopstick [5] initialized to 1
6.29 Silberschatz, Galvin and GagneOperating System Concepts
Dining-Philosophers Problem (Cont.)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) ;
6.30 Silberschatz, Galvin and GagneOperating System Concepts
Problems with SemaphoresProblems with Semaphores
Correct use of semaphore operations:
signal (mutex) …. wait (mutex)
wait (mutex) … wait (mutex)
Omitting of wait (mutex) or signal (mutex) (or both)
6.31 Silberschatz, Galvin and GagneOperating System Concepts
MonitorsMonitors
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 ( ….) { … }
…
}
}
6.32 Silberschatz, Galvin and GagneOperating System Concepts
Schematic view of a MonitorSchematic view of a Monitor
6.33 Silberschatz, Galvin and GagneOperating System Concepts
Condition VariablesCondition 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 ()
6.34 Silberschatz, Galvin and GagneOperating System Concepts
Monitor with Condition VariablesMonitor with Condition Variables
6.35 Silberschatz, Galvin and GagneOperating System Concepts
Solution to Dining PhilosophersSolution 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);
}
6.36 Silberschatz, Galvin and GagneOperating System Concepts
Solution to Dining Philosophers (cont)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;
}
}
6.37 Silberschatz, Galvin and GagneOperating System Concepts
Synchronization ExamplesSynchronization Examples
Solaris
Windows XP
Linux
Pthreads
6.38 Silberschatz, Galvin and GagneOperating System Concepts
Solaris SynchronizationSolaris 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
6.39 Silberschatz, Galvin and GagneOperating System Concepts
Windows XP SynchronizationWindows 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
6.40 Silberschatz, Galvin and GagneOperating System Concepts
Linux SynchronizationLinux Synchronization
Linux:
disables interrupts to implement short critical sections
Linux provides:
semaphores
spin locks
6.41 Silberschatz, Galvin and GagneOperating System Concepts
Pthreads SynchronizationPthreads Synchronization
Pthreads API is OS-independent
It provides:
mutex locks
condition variables
Non-portable extensions include:
read-write locks
spin locks
End of Chapter 6End of Chapter 6

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6.Process Synchronization

  • 1. Chapter 6: ProcessChapter 6: Process SynchronizationSynchronization
  • 2. 6.2 Silberschatz, Galvin and GagneOperating System Concepts Module 6: Process SynchronizationModule 6: Process Synchronization Background The Critical-Section Problem Peterson’s Solution Synchronization Hardware Semaphores Classic Problems of Synchronization Monitors Synchronization Examples Atomic Transactions
  • 3. 6.3 Silberschatz, Galvin and GagneOperating System Concepts BackgroundBackground 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.
  • 4. 6.4 Silberschatz, Galvin and GagneOperating System Concepts ProducerProducer while (true) /* produce an item and put in nextProduced while (count == BUFFER_SIZE) ; // do nothing buffer [in] = nextProduced; in = (in + 1) % BUFFER_SIZE; count++; }
  • 5. 6.5 Silberschatz, Galvin and GagneOperating System Concepts ConsumerConsumer while (1) { while (count == 0) ; // do nothing nextConsumed = buffer[out]; out = (out + 1) % BUFFER_SIZE; count--; /* consume the item in nextConsumed }
  • 6. 6.6 Silberschatz, Galvin and GagneOperating System Concepts Race ConditionRace 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}
  • 7. 6.7 Silberschatz, Galvin and GagneOperating System Concepts Solution to Critical-Section ProblemSolution 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
  • 8. 6.8 Silberschatz, Galvin and GagneOperating System Concepts Peterson’s SolutionPeterson’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!
  • 9. 6.9 Silberschatz, Galvin and GagneOperating System Concepts Algorithm for ProcessAlgorithm for Process PPii do { flag[i] = TRUE; turn = j; while ( flag[j] && turn == j); CRITICAL SECTION flag[i] = FALSE; REMAINDER SECTION } while (TRUE);
  • 10. 6.10 Silberschatz, Galvin and GagneOperating System Concepts Synchronization HardwareSynchronization 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
  • 11. 6.11 Silberschatz, Galvin and GagneOperating System Concepts TestAndndSet InstructionTestAndndSet Instruction Definition: boolean TestAndSet (boolean *target) { boolean rv = *target; *target = TRUE; return rv: }
  • 12. 6.12 Silberschatz, Galvin and GagneOperating System Concepts Solution using TestAndSetSolution using TestAndSet Shared boolean variable lock., initialized to false. Solution: do { while ( TestAndSet (&lock )) ; /* do nothing // critical section lock = FALSE; // remainder section } while ( TRUE);
  • 13. 6.13 Silberschatz, Galvin and GagneOperating System Concepts Swap InstructionSwap Instruction Definition: void Swap (boolean *a, boolean *b) { boolean temp = *a; *a = *b; *b = temp: }
  • 14. 6.14 Silberschatz, Galvin and GagneOperating System Concepts Solution using SwapSolution using Swap 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);
  • 15. 6.15 Silberschatz, Galvin and GagneOperating System Concepts SemaphoreSemaphore 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++; }
  • 16. 6.16 Silberschatz, Galvin and GagneOperating System Concepts Semaphore as General Synchronization ToolSemaphore 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);
  • 17. 6.17 Silberschatz, Galvin and GagneOperating System Concepts Semaphore ImplementationSemaphore 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.
  • 18. 6.18 Silberschatz, Galvin and GagneOperating System Concepts Semaphore Implementation with no Busy waitingSemaphore 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.
  • 19. 6.19 Silberschatz, Galvin and GagneOperating System Concepts Semaphore Implementation with no Busy waitingSemaphore Implementation with no Busy waiting (Cont.)(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); } }
  • 20. 6.20 Silberschatz, Galvin and GagneOperating System Concepts Deadlock and StarvationDeadlock 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.
  • 21. 6.21 Silberschatz, Galvin and GagneOperating System Concepts Classical Problems ofClassical Problems of SynchronizationSynchronization Bounded-Buffer Problem Readers and Writers Problem Dining-Philosophers Problem
  • 22. 6.22 Silberschatz, Galvin and GagneOperating System Concepts Bounded-Buffer ProblemBounded-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.
  • 23. 6.23 Silberschatz, Galvin and GagneOperating System Concepts Bounded Buffer Problem (Cont.)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);
  • 24. 6.24 Silberschatz, Galvin and GagneOperating System Concepts Bounded Buffer Problem (Cont.)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);
  • 25. 6.25 Silberschatz, Galvin and GagneOperating System Concepts Readers-Writers ProblemReaders-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.
  • 26. 6.26 Silberschatz, Galvin and GagneOperating System Concepts Readers-Writers Problem (Cont.)Readers-Writers Problem (Cont.) The structure of a writer process do { wait (wrt) ; // writing is performed signal (wrt) ; } while (true)
  • 27. 6.27 Silberschatz, Galvin and GagneOperating System Concepts Readers-Writers Problem (Cont.)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)
  • 28. 6.28 Silberschatz, Galvin and GagneOperating System Concepts Dining-Philosophers ProblemDining-Philosophers Problem Shared data Bowl of rice (data set) Semaphore chopstick [5] initialized to 1
  • 29. 6.29 Silberschatz, Galvin and GagneOperating System Concepts Dining-Philosophers Problem (Cont.)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) ;
  • 30. 6.30 Silberschatz, Galvin and GagneOperating System Concepts Problems with SemaphoresProblems with Semaphores Correct use of semaphore operations: signal (mutex) …. wait (mutex) wait (mutex) … wait (mutex) Omitting of wait (mutex) or signal (mutex) (or both)
  • 31. 6.31 Silberschatz, Galvin and GagneOperating System Concepts MonitorsMonitors 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 ( ….) { … } … } }
  • 32. 6.32 Silberschatz, Galvin and GagneOperating System Concepts Schematic view of a MonitorSchematic view of a Monitor
  • 33. 6.33 Silberschatz, Galvin and GagneOperating System Concepts Condition VariablesCondition 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 ()
  • 34. 6.34 Silberschatz, Galvin and GagneOperating System Concepts Monitor with Condition VariablesMonitor with Condition Variables
  • 35. 6.35 Silberschatz, Galvin and GagneOperating System Concepts Solution to Dining PhilosophersSolution 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); }
  • 36. 6.36 Silberschatz, Galvin and GagneOperating System Concepts Solution to Dining Philosophers (cont)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; } }
  • 37. 6.37 Silberschatz, Galvin and GagneOperating System Concepts Synchronization ExamplesSynchronization Examples Solaris Windows XP Linux Pthreads
  • 38. 6.38 Silberschatz, Galvin and GagneOperating System Concepts Solaris SynchronizationSolaris 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
  • 39. 6.39 Silberschatz, Galvin and GagneOperating System Concepts Windows XP SynchronizationWindows 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
  • 40. 6.40 Silberschatz, Galvin and GagneOperating System Concepts Linux SynchronizationLinux Synchronization Linux: disables interrupts to implement short critical sections Linux provides: semaphores spin locks
  • 41. 6.41 Silberschatz, Galvin and GagneOperating System Concepts Pthreads SynchronizationPthreads Synchronization Pthreads API is OS-independent It provides: mutex locks condition variables Non-portable extensions include: read-write locks spin locks
  • 42. End of Chapter 6End of Chapter 6