Chapter 6: Synchronization

6.2 Silberschatz, Galvin and Gagne ©2005 Operating System Principles Module 6: Synchronization 6.1 Background 6.2 The Critical-Section Problem 6.3 Peterson’s Solution 6.4 Synchronization Hardware 6.5 Semaphores 6.6 Classic Problems of Synchronization 6.7 Monitors 6.8 Synchronization Examples 6.9 Atomic Transactions

6.3 Silberschatz, Galvin and Gagne ©2005 Operating System Principles Independent process cannot affect or be affected by the execution of another process Cooperating process can affect or be affected by the execution of another process Advantages of process cooperation Information sharing Computation speed-up Modularity Convenience Review Interproces Communication

6.4 Silberschatz, Galvin and Gagne ©2005 Operating System Principles Communications Models Message passing Shared memory

6.5 Silberschatz, Galvin and Gagne ©2005 Operating System Principles Producer-Consumer Problem Paradigm for cooperating processes, producer process produces information that is consumed by a consumer process unbounded-buffer places no practical limit on the size of the buffer bounded-buffer assumes that there is a fixed buffer size Shared-Memory Solution : Shared data #define BUFFER_SIZE 10 Typedef struct {... } item; item buffer[BUFFER_SIZE]; int in = 0; int out = 0;

6.6 Silberschatz, Galvin and Gagne ©2005 Operating System Principles Bounded-Buffer – Producer() Method while (true) { /* produce an item in nextProduced*/ while (( (in + 1) % BUFFER_SIZE) == out) ; /* do nothing -- no free buffers */ buffer[in] = nextProduced; in = (in + 1) % BUFFER_SIZE; } Solution is correct, but can only use BUFFER_SIZE-1 elements Bounded-Buffer – Consumer() Method while (true) { while (in == out) ; // do nothing -- nothing to consume nextConsumed = buffer[out]; out = (out + 1) % BUFFER SIZE; /* consume the item in nextConsumed */; }

6.7 Silberschatz, Galvin and Gagne ©2005 Operating System Principles BUFFER_SIZE solution One more shared memory variable: counter

6.8 Silberschatz, Galvin and Gagne ©2005 Operating System Principles Still Have Problems

6.9 Silberschatz, Galvin and Gagne ©2005 Operating System Principles 6.1 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 (Section 3.4.1) 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.

6.10 Silberschatz, Galvin and Gagne ©2005 Operating System Principles Producer while (true) { /* produce an item and put in nextProduced */ while (counter == BUFFER_SIZE) ; // do nothing buffer [in] = nextProduced; in = (in + 1) % BUFFER_SIZE; counter++; } while (true) { while (counter == 0) ; // do nothing nextConsumed = buffer[out]; out = (out + 1) % BUFFER_SIZE; counter--; /* consume the item in nextConsumed } Consumer

6.11 Silberschatz, Galvin and Gagne ©2005 Operating System Principles Race Condition counter++ could be implemented as register1 = counter register1 = register1 + 1 counter = register1 counter-- could be implemented as register2 = counter register2 = register2 - 1 counter = register2

6.12 Silberschatz, Galvin and Gagne ©2005 Operating System Principles Race Condition Consider this execution interleaving with “counter = 5” initially: T0: producer execute register1 = counter {register1 = 5} T1: producer execute register1 = register1 + 1 {register1 = 6} T2: consumer execute register2 = counter {register2 = 5} T3: consumer execute register2 = register2 - 1 {register2 = 4} T4: producer execute counter = register1 {count = 6 } T5: consumer execute counter = register2 {count = 4} If the order T4 and T5 is reversed, then the final state is count = 6

6.13 Silberschatz, Galvin and Gagne ©2005 Operating System Principles 6.2 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 some processes wish to enter their critical sections, then only those processes that are not executing in their remainder sections can participate in the decision on which will enter its critical section next, and this selection 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

6.14 Silberschatz, Galvin and Gagne ©2005 Operating System Principles Solution to Critical-Section Problem 6.2 Solution to Critical-Section Problem Example kernel data structure that is subject to race conditions: List of open files in the OS Data structure for free/allocated memory Process lists Data structure for interrupts handling Approaches in handling critical sections in OS: Preemptive kernels Nonpreemptive kernels A preemptive kernel is more suitable for real-time programming, more responsive 訂正： p190 倒數第 3 列第 2 個字 應為 preemptive

6.15 Silberschatz, Galvin and Gagne ©2005 Operating System Principles 6.3 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 P i is ready!

6.16 Silberschatz, Galvin and Gagne ©2005 Operating System Principles Algorithm for Process P i while (true) { flag[i] = TRUE; turn = j; // j is i -1 while ( flag[j] && turn == j); CRITICAL SECTION flag[i] = FALSE; REMAINDER SECTION } entry section (acquire lock) exit section (release lock)

6.17 Silberschatz, Galvin and Gagne ©2005 Operating System Principles To prove Peterson’s solution is correct: Mutual exclusion is preserved The progress requirement is satisfied The bounded-waiting requirement is met

6.18 Silberschatz, Galvin and Gagne ©2005 Operating System Principles 6.4 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

6.19 Silberschatz, Galvin and Gagne ©2005 Operating System Principles TestAndndSet Instruction Definition: boolean TestAndSet (boolean *target) { boolean rv = *target; *target = TRUE; return rv: } Shared boolean variable lock initialized to false. Solution using TestandSet: while (true) { while ( TestAndSet (&lock )) ; // do nothing // critical section lock = FALSE; // remainder section }

6.20 Silberschatz, Galvin and Gagne ©2005 Operating System Principles Swap Instruction Definition: void Swap (boolean *a, boolean *b) { boolean temp = *a; *a = *b; *b = temp: } Shared boolean variable lock initialized to FALSE; Each process has a local boolean variable key. Solution using Swap: while (true) { key = TRUE; while ( key == TRUE) Swap (&lock, &key ); // critical section lock = FALSE; // remainder section } Does not satisfy bounded-waiting

6.21 Silberschatz, Galvin and Gagne ©2005 Operating System Principles Common data structure: boolean waiting[n] and boolean lock; Solution using TestandSet: while (true) { waiting[i] = TRUE; key = TRUE; while ( waiting[i] && key) key = TestAndSet(&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 } Bounded-waiting mutual exclusion with TestAndSet()