1 concurrent programming andrew case slides adapted from mohamed zahran, jinyang li, clark barrett,...
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Concurrent Programming
Andrew Case
Slides adapted from Mohamed Zahran, Jinyang Li, Clark Barrett, Randy Bryant and Dave O’Hallaron
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Concurrent vs. Parallelism Concurrency: At least two tasks are making
progress at the same time frame. – Not necessarily at the same time – Include techniques like time-slicing – Can be implemented on a single processing unit – Concept more general than parallelism
Parallelism: At least two tasks execute literally at the same time. – Requires hardware with multiple processing units
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Concurrent vs. Parallelism
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Concurrent Programming is Hard! Classical problem classes of concurrent programs:
Races: outcome depends on arbitrary scheduling decisions elsewhere in the system
Example: who gets the last seat on the airplane? Deadlock: improper resource allocation prevents forward progress
Example: traffic gridlock Livelock / Starvation / Fairness: external events and/or system
scheduling decisions can prevent sub-task progress Example: people always jump in front of you in line
Many aspects of concurrent programming are beyond the scope of this class
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Echo Server Echo Service
Original testing of round trip times / connectivity checks Superseded by “ping/ICMP”
Protocol: Client connects to server Client sends a message to server Server sends the same mess back to client (echos)
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Sequential Echo ServerClient Serversocket socket
bind
listen
read
writeread
write
Connectionrequest
read EOF
close
close
ConnectionFinished
Await connectionrequest fromnext client
open_listenfd
open_clientfd
acceptconnect
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Problems with Sequential Servers Low utilization
Server is idle while waiting for client1’s requests. It could have served another client during those idle times!
Increased latency Client2 waits on client1 to finish before getting served
Solution: implement concurrent servers serve multiple clients at the same time
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Sequential Echo Server Iterative servers process one request at a time
client 1 server client 2
connect
accept connect
write read
call read
close
accept
write
read
close
Wait for Client 1
call read
write
read returns
writeread returns
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Creating Concurrent Flows Allow server to handle multiple clients simultaneously
1. Processes Fork a new server process to handle each connection Kernel automatically interleaves multiple logical flows Each process has its own private address space
2. Threads (same process, multiple flows) Create one server thread to handle each connection Kernel automatically interleaves multiple logical flows Each flow shares the same address space
3. I/O multiplexing with select() Programmer manually interleaves multiple logical flows All flows share the same address space Relies on lower-level system abstractions
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Concurrent Servers: Multiple Processes Spawn separate process for each client
client 1 server client 2
call connectcall accept
call read
ret connectret accept
call connect
call fgetsforkchild 1
Client 1 blockswaiting for user to type in data
call acceptret connect
ret accept call fgets
writefork
call read
child 2
write
call read
end readclose
close
...
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Sequential Echo Serverint main(int argc, char **argv) { int listenfd, connfd; listenfd = socket(…) /* create socket */ bind(listenfd,…); /* bind socket to port */ listen(listenfd,…); /* listen for incoming connections*/
while (1) {connfd = accept(listenfd, …); /* connect to client */while (readline(connfd, …) > 0) /* read from client */
write(connfd, …); /* write to client */ close(connfd); } exit(0);}
Accept a connection request Handle echo requests until client terminates
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int main(int argc, char **argv) { int listenfd, connfd; signal(SIGCHLD, sigchld_handler); listenfd = socket(…) /* create socket */ bind(listenfd,…); /* bind socket to port */ listen(listenfd,…); /* listen for incoming connections*/
while (1) {connfd = accept(listenfd, …); /* client connects */if (fork() == 0) { close(listenfd); /* Child closes its listening socket */ while (readline(connfd, …); /* Child services client */
write(connfd,…) close(connfd); /* Child closes connection with client */ exit(0); /* Child exits */}close(connfd); /* Parent closes connected socket (important!) */
}}
Process-Based Concurrent Server
Fork separate process for each client
Does not allow any communication between different client handlers
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Process Concurrency Requirements
Listening server process must reap zombie children to avoid fatal memory leak
Listening server process must close its copy of connfd Kernel keeps reference for each socket/open file After fork, refcnt(connfd) = 2 Connection will not be closed until refcnt(connfd) == 0
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Process-Based Concurrent Server – Reaping
void sigchld_handler(int sig) { while (waitpid(-1, 0, WNOHANG) > 0)
; return;}
Reap all zombie children
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Process-Based Execution Model
Each client handled by independent process No shared state between them Both parent & child have copies of listenfd and connfd
Client 1Server
Process
Client 2Server
Process
ListeningServer
Process
Connection Requests
Client 1 data Client 2 data
Connection Requests
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Pros and Cons of Process-Based Designs
+ Handle multiple connections concurrently + Clean sharing model
Shared file tables with separate file descripters No shared address space (no shared variables/globals)
+ Simple and straightforward – Additional overhead for process control – Nontrivial to share data between processes
Requires IPC (interprocess communication) mechanisms FIFO’s (named pipes), shared memory and semaphores
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Approach #2: Multiple Threads
Very similar to approach #1 (multiple processes) but, with threads instead of processes
Multithreading
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Traditional View of a Process Process = process context + code, data, and stack
shared libraries
run-time heap
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read/write data
Program context: Data registers Condition codes Stack pointer (SP) Program counter (PC)Kernel context: VM structures Descriptor table brk pointer
Code, data, and stack
read-only code/data
stackSP
PC
brk
Process context
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Alternate View of a Process Process = thread + code, data, and kernel context
shared libraries
run-time heap
0
read/write dataThread context:
Data registers Condition codes Stack pointer (SP) Program counter (PC)
Code and Data
read-only code/data
stackSP
PC
brk
Thread (main thread)
Kernel context: VM structures Descriptor table brk pointer
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Multi-Threaded process A process can have multiple threads
Each thread has its own logical control flow (PC, registers, etc.) Each thread shares the same code, data, and kernel context
Share common virtual address space
shared libraries
run-time heap
0
read/write dataThread 1 context: Data registers Condition codes SP1 PC1
Shared code and data
read-only code/data
stack 1
Thread 1 (main thread)
Kernel context: VM structures Descriptor table brk pointer
Thread 2 context: Data registers Condition codes SP2 PC2
stack 2
Thread 2 (peer thread)
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Thread Execution
Single Core Processor time slicing
Multi-Core Processor true concurrency
Time
Thread A Thread B Thread C Thread A Thread B Thread C
(Running 3 threads on 2 cores)
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Threads vs. Processes Similarities
Each has its own logical control flow Each can run concurrently with others (often on different cores/CPUs) Each is context switched
Differences Threads share code and some data
Processes (typically) do not Threads are less resource intensive than processes
Process control (creating and reaping) is ~2x as expensive as thread control
Scheduling may be skewed in favor of processes If one thread blocks, more likely to bring down the whole lot
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POSIX Threads (Pthreads)
Pthreads: Standard interface for 60+ functions that manipulate threads from C programs (pthread.h)
Compile with GCC:gcc/g++ -pthread programname
Programmer responsible for synchronizing/protecting shared resources
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POSIX Threads (Pthreads) Creating and reaping threads
pthread_create() pthread_join()
Terminating threads pthread_cancel() pthread_exit() exit() [terminates all threads]
Synchronizing access to shared variables pthread_mutex_init pthread_mutex_[un]lock pthread_cond_init pthread_cond_[timed]wait
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The pthread_join() blocks the calling threaduntil the thread with the specified threadID exits.
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/* thread routine */void *thread(void *vargp) { printf("Hello, world!\n"); return NULL;}
The Pthreads "hello, world" Program/* * hello.c - Pthreads "hello, world" program */
void *thread(void *vargp);
int main() { pthread_t tid;
pthread_create(&tid, NULL, thread, NULL); pthread_join(tid, NULL); exit(0);}
Thread attributes (usually NULL)
Thread arguments(void *p)
return value(void **p)
Thread function
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Execution of Threaded“hello, world”main thread
peer thread
return NULL;main thread waits for peer thread to terminate
exit() terminates
main thread and any peer threads
Call pthread_create()
Call pthread_join()
pthread_join() returns
printf()
(peer threadterminates)
pthread_create() returns
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Thread-Based Concurrent Echo Serverint main(int argc, char **argv) { … pthread_t tid; listenfd = socket(…); bind(listenfd,…); listen(listenfd,…); while (1) { connfd = accept(listenfd,…); /* Create a new thread for each connection */ pthread_create(&tid, NULL, echo_thread, (void *) connfd); ptread_detach(tid); /* if not planning to pthread_join */ }}void *echo_thread(void *p) { int connfd = (int)p; /* Get connection file handler */ while (readline(connfd,…)>0) write(connfd,…); close(connfd); /* Close file handler when done */ return NULL; /* Not returning any data to main thread */}
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Threaded Execution Model
Multiple threads within single process Shared state between them
Client 1Server
Client 2Server
ListeningServer
Connection Requests
Client 1 data Client 2 data
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Problems: Race Conditions
A race condition occurs when correctness of the program depends on one thread or process reaching point x before another thread or process reaches point y
Any ordering of instructions from multiple threads may occur
race.c
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Potential Race Condition
int i;for (i = 0; i < 100; i++) { pthread_create(&tid, NULL, thread, &i);}
Race Test If no race, then each thread would get different value of i Set of saved values would consist of one copy each of 0 through 99.
Main
void *thread(void *p) { int i = *((int *)p); pthread_detach(pthread_self()); save_value(i); return NULL;}
Thread
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Experimental Results
No Race
Multicore server
0 3 6 9 12 15 18 21 24 27 30 33 36 39 42 45 48 51 54 57 60 63 66 69 72 75 78 81 84 87 90 93 96 990
1
2
0 3 6 9 12 15 18 21 24 27 30 33 36 39 42 45 48 51 54 57 60 63 66 69 72 75 78 81 84 87 90 93 96 990
2
4
6
8
10
12
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Single core laptop
0 3 6 9 12 15 18 21 24 27 30 33 36 39 42 45 48 51 54 57 60 63 66 69 72 75 78 81 84 87 90 93 96 990
1
2
3
(Number of times each value is used)
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Pros and Cons of Thread-Based Designs
+ Easy to share data structures between threads e.g., logging information, file cache.
+ Threads are more efficient than processes.
– Unintentional sharing can introduce subtle and hard-to-reproduce errors! Race conditions, data corruptions from other threads, etc.
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Event-Based Servers Using I/O Multiplexing
OS provides detection for input among a list of FDs select(), poll(), and epoll()
Server maintains set of active connections Array of connfd’s
Repeat: Determine which connections have pending inputs If listenfd has input, then accept connection
Add new connfd to array Service all connfd’s with pending inputs
Details in book
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I/O Multiplexed Event Processing
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clientfd
7
4
-1
-1
12
5
-1
-1
-1
0
1
2
3
4
5
6
7
8
9
Active
Inactive
Active
Never Used
listenfd = 3
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clientfd
7
4
-1
-1
12
5
-1
-1
-1
listenfd = 3
Active Descriptors Pending Inputs
Read
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Pros and Cons of I/O Multiplexing
+ One logical control flow + Easier to debug + No process or thread control overhead
– More complex to code than process/thread based designs – Cannot take advantage of multi-core
Single thread of control
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Approaches to Concurrency
Processes Hard to share resources: Easy to avoid unintended sharing High overhead in adding/removing clients
Threads Easy to share resources: Perhaps too easy Medium overhead Not much control over scheduling policies Difficult to debug
Event orderings not repeatable I/O Multiplexing
Tedious / more code to write (scheduler) Total control over scheduling Very low overhead only one process so it can only run on one cpu-core