Process Synchronization

Background

The Critical-Section Problem

Synchronization Hardware

Semaphores

Classical Problems of Synchronization

Critical Regions

Monitors

Synchronization in Solaris 2 & Windows 2000

Background

Concurrent access to shared data may result in data inconsistency.

Maintaining data consistency requires mechanisms to ensure the orderly execution of cooperating processes.

Shared-memory solution to bounded-butter problem (Chapter 4) allows at most n – 1 items in buffer at the same time. A solution, where all N buffers are used is not simple.

Suppose that we modify the producer-consumer code by adding a variable counter, initialized to 0 and incremented each time a new item is added to the buffer

Bounded-Buffer

Shared data

#define BUFFER_SIZE 10

typedef struct {

. . .

} item;

item buffer[BUFFER_SIZE];

int in = 0;

int out = 0;

int counter = 0;

Bounded-Buffer

Producer process

item nextProduced;

while (1) {

while (counter == BUFFER_SIZE)

; /* do nothing */

buffer[in] = nextProduced;

in = (in + 1) % BUFFER_SIZE;

counter++;

}

Bounded-Buffer

Consumer process

item nextConsumed;

while (1) {

while (counter == 0)

; /* do nothing */

nextConsumed = buffer[out];

out = (out + 1) % BUFFER_SIZE;

counter--;

}

Bounded Buffer

The statements

counter++;
counter--;

must be performed atomically.

Atomic operation means an operation that completes in its entirety without interruption.

Bounded Buffer

The statement “count++” may be implemented in machine language as:

register1 = counter // a Load instr

register1 = register1 + 1 // an IncReg instr

counter = register1 // a Store instr

The statement “count—” may be implemented as:

register2 = counter
register2 = register2 – 1
counter = register2

Bounded Buffer

If both the producer and consumer attempt to update the buffer concurrently, the machine instructions may get interleaved.

Interleaving depends upon how the producer and consumer processes are scheduled.

Bounded Buffer

Assume counter is initially 5. One interleaving of statements is:

producer: register1 = counter (register1 = 5)
producer: register1 = register1 + 1 (register1 = 6)
consumer: register2 = counter (register2 = 5)
consumer: register2 = register2 – 1 (register2 = 4)
producer: counter = register1 (counter = 6)
consumer: counter = register2 (counter = 4)

The value of count may be either 4 or 6, where the correct result should be 5.

Race Condition

Race condition: The situation where several processes access – and manipulate shared data concurrently. The final value of the shared data depends upon which process finishes last.

To prevent race conditions, concurrent processes must be synchronized.

The Critical-Section Problem

n processes all competing to use some shared data

Each process has a code segment, called critical section, in which the shared data is accessed.

Problem – ensure that when one process is executing in its critical section, no other process is allowed to execute in its critical section.

Solution to Critical-Section Problem

1. Mutual Exclusion. If process P_i 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.

Initial Attempts to Solve Problem

Only 2 processes, P₀ and P₁

General structure of process P_i (other process P_j)

do {

enter section

critical section

exit section

reminder section

} while (1);

Processes may share some common variables to synchronize their actions.

Algorithm 1

Shared variables:

int turn;
initially turn = 0

turn = i Þ P_i can enter its critical section

Process P_i

do {

while (turn != i) ;

critical section

turn = j;

reminder section

} while (1);

Satisfies mutual exclusion, but not progress

Algorithm 2

Shared variables

boolean flag[2];
initially flag [0] = flag [1] = false.

flag [i] = true Þ P_i ready to enter its critical section

Process P_i

do {

flag[i] := true;
while (flag[j]) ; critical section

flag [i] = false;

remainder section

} while (1);

Satisfies mutual exclusion, but not progress requirement.

Algorithm 3

Combined shared variables of algorithms 1 and 2.

Process P_i

do {

flag [i]:= true;
turn = j;
while (flag [j] and turn = j) ;

critical section

flag [i] = false;

remainder section

} while (1);

Meets all three requirements; solves the critical-section problem for two processes.

Bakery Algorithm

Before entering its critical section, process receives a number. Holder of the smallest number enters the critical section.

If processes P_i and P_j receive the same number, if i < j, then P_i is served first; else P_j is served first.

The numbering scheme always generates numbers in increasing order of enumeration; i.e., 1,2,3,3,3,3,4,5...

Bakery Algorithm

Notation <º lexicographical order (ticket #, process id #)

(a,b) < (c,d) if a < c or if a = c and b < d

max (a₀,…, a_n-1) is a number, k, such that k ³ a_i for i - 0,
…, n – 1

Shared data

boolean choosing[n];

int number[n];

Data structures are initialized to false and 0 respectively

Bakery Algorithm

do {

choosing[i] = true;

number[i] = max(number[0], number[1], …, number [n – 1])+1;

choosing[i] = false;

for (j = 0; j <>

while (choosing[j]) ;

while ((number[j] != 0) && (number[j],j) <>

}

critical section

number[i] = 0;

remainder section

} while (1);

Synchronization Hardware

Test and modify the content of a word atomically

boolean TestAndSet(boolean &target) {

boolean rv = target;

target = true;

return rv;

}

Mutual Exclusion with Test-and-Set

Shared data:
boolean lock = false;

Process P_i

do {

while (TestAndSet(lock)) ;

critical section

lock = false;

remainder section

}

Synchronization Hardware

Atomically swap two variables.

void Swap(boolean &a, boolean &b) {

boolean temp = a;

a = b;

b = temp;

}

Mutual Exclusion with Swap

Shared data (initialized to false):
boolean lock;

boolean waiting[n];

Process P_i

do {

key = true;

while (key == true)

Swap(lock,key);

critical section

lock = false;

remainder section

}

Semaphores

Synchronization tool that does not require busy waiting.

Semaphore S – integer variable

can only be accessed via two indivisible (atomic) operations

wait (S):

while S£ 0 do no-op;
S--;

signal (S):

S++;

Critical Section of n Processes

Shared data:

semaphore mutex; //initially mutex = 1

Process Pi:

do {
wait(mutex);
critical section

signal(mutex);
remainder section
} while (1);

Semaphore Implementation

Define a semaphore as a record

typedef struct {

int value;
struct process *L;
} semaphore;

Assume two simple operations:

block suspends the process that invokes it.

wakeup(P) resumes the execution of a blocked process P.

Implementation

Semaphore operations now defined as

wait(S):
S.value--;

if (S.value <>

add this process to S.L;
block;

}

signal(S):
S.value++;

if (S.value <= 0) {

remove a process P from S.L;
wakeup(P);

}

Semaphore as a General Synchronization Tool

Execute B in P_j only after A executed in P_i

Use semaphore flag initialized to 0

Code:

P_i P_j

M M

A wait(flag)

signal(flag) B

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);

M M

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.

Two Types of Semaphores

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.

Can implement a counting semaphore S as a binary semaphore.

Implementing S as a Binary Semaphore

Data structures:

binary-semaphore S1, S2;

int C:

Initialization:

S1 = 1

S2 = 0

C = initial value of semaphore S

Implementing S

wait operation

wait(S1);

C--;

if (C <>

signal(S1);

wait(S2);

}

signal(S1);

signal operation

wait(S1);

C ++;

if (C <= 0)

signal(S2);

else

signal(S1);

Classical Problems of Synchronization

Bounded-Buffer Problem

Readers and Writers Problem

Dining-Philosophers Problem

Bounded-Buffer Problem

Shared data

semaphore full, empty, mutex;

Initially:

full = 0, empty = n, mutex = 1

Bounded-Buffer Problem Producer Process

do {

…

produce an item in nextp

…

wait(empty);

wait(mutex);

…

add nextp to buffer

…

signal(mutex);

signal(full);

} while (1);

Bounded-Buffer Problem Consumer Process

do {

wait(full)

wait(mutex);

…

remove an item from buffer to nextc

…

signal(mutex);

signal(empty);

…

consume the item in nextc

…

} while (1);

Readers-Writers Problem

Shared data

semaphore mutex, wrt;

Initially

mutex = 1, wrt = 1, readcount = 0

Readers-Writers Problem Writer Process

wait(wrt);

…

writing is performed

…

signal(wrt);

Readers-Writers Problem Reader Process

wait(mutex);

readcount++;

if (readcount == 1)

wait(wrt);

signal(mutex);

…

reading is performed

…

wait(mutex);

readcount--;

if (readcount == 0)

signal(wrt);

signal(mutex):

Dining-Philosophers Problem

Shared data

semaphore chopstick[5];

Initially all values are 1

Dining-Philosophers Problem

Philosopher i:

do {

wait(chopstick[i])

wait(chopstick[(i+1) % 5])

…

eat

…

signal(chopstick[i]);

signal(chopstick[(i+1) % 5]);

…

think

…

} while (1);

Monitors

To allow a process to wait within the monitor, a condition variable must be declared, as

condition x, y;

Condition variable can only be used with the operations wait and signal.

The operation

x.wait();
means that the process invoking this operation is suspended until another process invokes

x.signal();

The x.signal operation resumes exactly one suspended process. If no process is suspended, then the signal operation has no effect.

Schematic View of a Monitor

Monitor With Condition Variables

Dining Philosophers Example

monitor dp

{

enum {thinking, hungry, eating} state[5];

condition self[5];

void pickup(int i) // following slides

void putdown(int i) // following slides

void test(int i) // following slides

void init() {

for (int i = 0; i <>

state[i] = thinking;

}

}

Dining Philosophers

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);

}

Dining Philosophers

void test(int i) {

if ( (state[(i + 4) % 5] != eating) &&

(state[i] == hungry) &&

(state[(i + 1) % 5] != eating)) {

state[i] = eating;

self[i].signal();

}

}

Solaris 2 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 2000 Synchronization

Uses interrupt masks to protect access to global resources on uniprocessor systems.

Uses spinlocks (that is, busy waits) on multiprocessor systems.

Also provides dispatcher objects which may act as wither mutexes and semaphores.

Dispatcher objects may also provide events. An event acts much like a condition variable.