程序代写代做 concurrency compiler database C kernel Concurrency and Synchronisation

Concurrency and Synchronisation
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Learning Outcomes
• Understand concurrency is an issue in operating systems and multithreaded applications
• Know the concept of a critical region.
• Understand how mutual exclusion of critical regions can be used to solve concurrency issues
• Including how mutual exclusion can be implemented correctly and efficiently.
• Be able to identify and solve a producer consumer bounded buffer problem.
• Understand and apply standard synchronisation primitives to solve synchronisation problems.
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Textbook
• Sections 2.3 – 2.3.7 & 2.5
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Concurrency Example
count is a global variable shared between two threads.
After increment and decrement complete, what is the value of count?
void increment () void decrement () {{
int t;
}}
We have a
race condition
int t;
t = count;
t = t + 1;
count = t;
t = count;
t = t – 1;
count = t;
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Where is the concurrency?
• (a) Three processes each with one thread • (b) One process with three threads

There is in-kernel concurrency even for single-
threaded processes
Process’s user-level stack and execution state
User Mode
Process A Process B Process C Operating System
Kernel Mode
Process’s in-kernel stack and execution state

Critical Region
• We can control access to the shared resource by controlling access to the code that accesses the resource.
 A critical region is a region of code where shared resources are accessed.
• Variables, memory, files, etc…
• Uncoordinated entry to the critical region results in a race condition
 Incorrect behaviour, deadlock, lost work,…
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Identifying critical regions
• Critical regions are regions of code that:
• Access a shared resource,
• and correctness relies on the shared resource not being concurrently modified by another thread/process/entity.
void increment () void decrement () {{
int t;
t = count;
t = t + 1;
count = t;
}}
int t;
t = count;
t = t – 1;
count = t;
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Accessing Critical Regions
Mutual exclusion using critical regions
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Example critical regions
struct node {
int data;
struct node *next;
};
struct node *head;
void insert(struct *item)
{
item->next = head;
head = item; }
void init(void) {{
head = NULL; }
• Simple last-in-first-out queue implemented as a linked list.
struct node *remove(void)
struct node *t;
t = head;
if (t != NULL) {
head = head->next;
}
return t; }
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Example Race
void insert(struct *item)
{
item->next = head;
head = item; }
void insert(struct *item)
{
item->next = head;
head = item; }
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Example critical regions
struct node {
int data;
struct node *next;
};
struct node *head;
void insert(struct *item)
{
item->next = head;
head = item; }
void init(void) {{
head = NULL;
• Critical sections
struct node *remove(void)
struct node *t;
return t; }
}
t = head;
if (t != NULL) {
head = head->next;
}
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Critical Regions Solutions
• We seek a solution to coordinate access to critical regions.
• Also called critical sections
• Conditions required of any solution to the critical region problem
1. Mutual Exclusion:
• No two processes simultaneously in critical region
2. No assumptions made about speeds or numbers of CPUs 3. Progress
• No process running outside its critical region may block another process 4. Bounded
• No process waits forever to enter its critical region
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A solution? • A lock variable
• If lock == 1,
• somebody is in the critical section and we must wait
• If lock == 0,
• nobody is in the critical section and we are free to enter
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A solution?
while(TRUE) {
while(lock == 1);
lock = 1;
critical();
lock = 0
non_critical();
while(TRUE) {
while(lock == 1);
lock = 1;
critical();
lock = 0
non_critical();
}}
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A problematic execution sequence
while(TRUE) {
while(lock == 1);
lock = 1;
critical();
lock = 0
non_critical();
while(TRUE) {
while(lock == 1);
lock = 1;
critical();
lock = 0
non_critical();
}
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}

Observation
• Unfortunately, it is usually easier to show something does not work, than it is to prove that it does work.
• Easier to provide a counter example
• Ideally, we’d like to prove, or at least informally demonstrate, that our solutions work.
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Mutual Exclusion by Taking Turns
Proposed solution to critical region problem (a) Process 0. (b) Process 1.
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Mutual Exclusion by Taking Turns • Works due to strict alternation
• Each process takes turns
• Cons
• Busy waiting
• Process must wait its turn even while the other process is doing something else.
• With many processes, must wait for everyone to have a turn • Does not guarantee progress if a process no longer needs a turn.
• Poor solution when processes require the critical section at differing rates
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Mutual Exclusion by Disabling Interrupts
• Before entering a critical region, disable interrupts
• After leaving the critical region, enable interrupts
• Pros
• simple
• Cons
• Only available in the kernel
• Blocks everybody else, even with no contention • Slows interrupt response time
• Does not work on a multiprocessor
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Hardware Support for mutual exclusion • Test and set instruction
• Can be used to implement lock variables correctly • It loads the value of the lock
• If lock == 0,
• set the lock to 1
• return the result 0 – we acquire the lock • Iflock==1
• return 1 – another thread/process has the lock
• Hardware guarantees that the instruction executes atomically.
• Atomically: As an indivisible unit.
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Mutual Exclusion with Test-and-Set
Entering and leaving a critical region using the TSL instruction
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Test-and-Set
• Pros
• Simple (easy to show it’s correct)
• Available at user-level
• To any number of processors
• To implement any number of lock variables
• Cons
• Busy waits (also termed a spin lock)
• Consumes CPU
• Starvation is possible when a process leaves its critical section and more than one process is waiting.
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Tackling the Busy-Wait Problem • Sleep / Wakeup
• The idea
• When process is waiting for an event, it calls sleep to block, instead of
busy waiting.
• The event happens, the event generator (another process) calls wakeup to unblock the sleeping process.
• Waking a ready/running process has no effect.
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The Producer-Consumer Problem
• Also called the bounded buffer problem
• A producer produces data items and stores the items in a buffer
• A consumer takes the items out of the buffer and consumes them.
Producer
X
X
X
Consumer
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Issues
• We must keep an accurate count of items in buffer
• Producer
• should sleep when the buffer is full,
• and wakeup when there is empty space in the buffer
• The consumer can call wakeup when it consumes the first entry of the full buffer • Consumer
• should sleep when the buffer is empty
• and wake up when there are items available
• Producer can call wakeup when it adds the first item to the buffer
Producer
X
X
X
Consumer
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Pseudo-code for producer and consumer
int count = 0;
#define N 4 /* buf size */
prod() {
while(TRUE) {
item = produce()
if (count == N)
con() {
while(TRUE) {
if (count == 0)
sleep();
remove_item();
count–;
if (count == N-1)
} }
sleep();
insert_item();
count++;
if (count == 1)
wakeup(con);
wakeup(prod);
} }
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Problems
int count = 0;
#define N 4 /* buf size */
prod() {
while(TRUE) {
item = produce()
if (count == N)
con() {
while(TRUE) {
if (count == 0)
sleep();
remove_item();
count–;
if (count == N-1)
} }
sleep();
insert_item();
count++;
if (count == 1)
wakeup(con);
} }
wakeup(prod);
Concurrent uncontrolled access to the buffer
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Problems
int count = 0;
#define N 4 /* buf size */
prod() {
while(TRUE) {
item = produce()
if (count == N)
con() {
while(TRUE) {
if (count == 0)
sleep();
remove_item();
count–;
if (count == N-1)
} }
sleep();
insert_item();
count++;
if (count == 1)
wakeup(con);
} }
wakeup(prod);
Concurrent uncontrolled access to the counter
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Proposed Solution
• Lets use a locking primitive based on test-and-set to protect the concurrent access
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Proposed solution?
int count = 0;
#define N 4 /* buf size */ prod() {
while(TRUE) {
item = produce()
if (count == N)
sleep();
acquire_lock()
insert_item();
count++;
release_lock()
if (count == 1)
con() {
while(TRUE) {
if (count == 0)
sleep();
acquire_lock()
remove_item();
count–;
release_lock();
if (count == N-1)
} }
wakeup(prod);
wakeup(con);
} }
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Problematic execution sequence
prod() {
while(TRUE) {
item = produce()
if (count == N)
sleep();
acquire_lock()
insert_item();
count++;
release_lock()
if (count == 1)
wakeup(con);
if (count == 0)
wakeup without a matching sleep is lost
sleep();
acquire_lock()
remove_item();
count–;
release_lock();
if (count == N-1)
wakeup(prod);
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con() {
while(TRUE) {
} }

Problem
• The test for some condition and actually going to sleep needs to be atomic
• The following does not work:
acquire_lock()
if (count == N)
sleep();
release_lock()
The lock is held while asleep  count will never change
acquire_lock()
if (count == 1)
wakeup();
release_lock()
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Semaphores
• Dijkstra (1965) introduced two primitives that are more powerful than simple sleep and wakeup alone.
• P(): proberen, from Dutch to test.
• V(): verhogen, from Dutch to increment. • Also called wait & signal, down & up.
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How do they work
• If a resource is not available, the corresponding semaphore
blocks any process waiting for the resource
• Blocked processes are put into a process queue maintained
by the semaphore (avoids busy waiting!)
• When a process releases a resource, it signals this by means of the semaphore
• Signalling resumes a blocked process if there is any
• Wait and signal operations cannot be interrupted
• Complex coordination can be implemented by multiple semaphores
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Semaphore Implementation
• Define a semaphore as a record typedef struct {
int count;
struct process *L; } semaphore;
• Assume two simple operations:
• sleep suspends the process that invokes it.
• wakeup(P) resumes the execution of a blocked process P.
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• Semaphore operations now defined as
wait(S):
S.count–;
if (S.count < 0) { add this process to S.L; sleep; } signal(S): S.count++; if (S.count <= 0) { remove a process P from S.L; wakeup(P); } • Each primitive is atomic • E.g. interrupts are disabled for each 37 Semaphore as a General Synchronization Tool • Execute B in Pj only after A executed in Pi • Use semaphore count initialized to 0 • Code: Pi Pj ⁞⁞ A wait(flag) signal(flag) B 38 Semaphore Implementation of a Mutex • Mutex is short for Mutual Exclusion • Can also be called a lock semaphore mutex; mutex.count = 1; /* initialise mutex */ wait(mutex); /* enter the critcal region */ Blahblah(); signal(mutex); /* exit the critical region */ Notice that the initial count determines how many waits can progress before blocking and requiring a signal  mutex.count initialised as 1 39 Solving the producer-consumer problem with semaphores #define N = 4 semaphore mutex = 1; /* count empty slots */ semaphore empty = N; /* count full slots */ semaphore full = 0; 40 Solving the producer-consumer problem with semaphores prod() { while(TRUE) { con() { while(TRUE) { item = produce() wait(empty); wait(mutex) insert_item(); signal(mutex); signal(full); } } wait(full); wait(mutex); remove_item(); signal(mutex); signal(empty); } } 41 Summarising Semaphores • Semaphores can be used to solve a variety of concurrency problems • However, programming with then can be error-prone • E.g. must signal for every wait for mutexes • Too many, or too few signals or waits, or signals and waits in the wrong order, can have catastrophic results 42 Monitors • To ease concurrent programming, Hoare (1974) proposed monitors. • A higher level synchronisation primitive • Programming language construct • Idea • A set of procedures, variables, data types are grouped in a special kind of module, a monitor. • Variables and data types only accessed from within the monitor • Only one process/thread can be in the monitor at any one time • Mutual exclusion is implemented by the compiler (which should be less error prone) 43 Monitor • When a thread calls a monitor procedure that has a thread already inside, it is queued and it sleeps until the current thread exits the monitor. 44 Monitors Example of a monitor 45 Simple example monitor counter { int count; procedure inc() { Note: “paper” language • Compiler guarantees only one thread can be active in count = count + 1; themonitoratanyonetime } procedure dec() { count = count –1; } } • Easy to see this provides mutual exclusion • No race condition on count. 46 How do we block waiting for an event? • We need a mechanism to block waiting for an event (in addition to ensuring mutual exclusion) • e.g., for producer consumer problem when buffer is empty or full • Condition Variables 47 Condition Variable • 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 • Another thread can enter the monitor while original is suspended x.signal(); • The x.signal operation resumes exactly one suspended process. If no process is suspended, then the signal operation has no effect. 48 Condition Variables 49 Monitors • Outline of producer-consumer problem with monitors • only one monitor procedure active at one time • buffer has N slots 50 OS/161 Provided Synchronisation Primitives • Locks • Semaphores • Condition Variables 51 Locks • Functions to create and destroy locks struct lock *lock_create(const char *name); void lock_destroy(struct lock *); • Functions to acquire and release them void lock_acquire(struct lock *); void lock_release(struct lock *); 52 Example use of locks int count; struct lock *count_lock main() { count = 0; count_lock = lock_create(“count lock”); if (count_lock == NULL) panic(“I’m dead”); stuff(); } procedure inc() { lock_acquire(count_lock); count = count + 1; lock_release(count_lock); } procedure dec() { } lock_acquire(count_lock); count = count –1; lock_release(count_lock); 53 Semaphores struct semaphore *sem_create(const char *name, int initial_count); void sem_destroy(struct semaphore *); void P(struct semaphore *); void V(struct semaphore *); 54 Example use of Semaphores int count; struct semaphore *count_mutex; main() { count = 0; count_mutex = sem_create(“count”, 1); procedure inc() { P(count_mutex); count = count + 1; V(count_mutex); } procedure dec() { P(count_mutex); count = count –1; V(count_mutex); } if (count_mutex == NULL) panic(“I’m dead”); stuff(); } 55 Condition Variables struct cv *cv_create(const char *name); void void • • void void • • cv_destroy(struct cv *); cv_wait(struct cv *cv, struct lock *lock); Releases the lock and blocks Upon resumption, it re-acquires the lock • Note: we must recheck the condition we slept on cv_signal(struct cv *cv, struct lock *lock); cv_broadcast(struct cv *cv, struct lock *lock); Wakes one/all, does not release the lock First “waiter” scheduled after signaller releases the lock will re- acquire the lock Note: All three variants must hold the lock passed in. 56 Condition Variables and Bounded Buffers Non-solution lock_acquire(c_lock) if (count == 0) sleep(); remove_item(); count--; lock_release(c_lock) ; Solution lock_acquire(c_lock) while (count == 0) cv_wait(c_cv, c_lock); remove_item(); count--; lock_release(c_lock); 57 Alternative Producer-Consumer Solution Using OS/161 CVs int count = 0; #define N 4 /* buf size */ prod() { while(TRUE) { item = produce() lock_aquire(l) while (count == N) cv_wait(full,l); insert_item(item); count++; cv_signal(empty,l); lock_release(l) }} }} con() { while(TRUE) { lock_acquire(l) while (count == 0) cv_wait(empty,l); item = remove_item(); count--; cv_signal(full,l); lock_release(l); consume(item); 58 Dining Philosophers • Philosophers eat/think • Eating needs 2 forks • Pick one fork at a time • How to prevent deadlock 59 Dining Philosophers Solution to dining philosophers problem (part 1) 60 Dining Philosophers A nonsolution to the dining philosophers problem 61 Dining Philosophers Solution to dining philosophers problem (part 2) 62 63 The Readers and Writers Problem • Models access to a database • E.g. airline reservation system • Can have more than one concurrent reader • To check schedules and reservations • Writers must have exclusive access • To book a ticket or update a schedule 64 The Readers and Writers Problem A solution to the readers and writers problem 65