1 Concurrent Programming Andrew Case Slides adapted from Mohamed Zahran, Jinyang Li, Clark Barrett, Randy Bryant and Dave O’Hallaron

2 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

3 Concurrent vs. Parallelism

4 Concurrent Programming is Hard! The human mind tends to be sequential The notion of time is often misleading Thinking about all possible sequences of events in a computer system is at least error prone and frequently impossible

5 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

6 Echo Server Echo Service  Original testing of round trip times / connectivity checks  Superseded by “ping/ICMP” Protocol:  Client connects to server  Client sends a message to server  Server sends the same mess back to client (echos)

7 Sequential Echo Server ClientServer socket bind listen read writeread write Connection request read EOF close Connection Finished Await connection request from next client open_listenfd open_clientfd acceptconnect

8 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

9 Sequential Echo Server Iterative servers process one request at a time client 1serverclient 2 connect accept connect write read call read close accept write read close Wait for Client 1 call read write read returns write read returns

10 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

11 Concurrent Servers: Multiple Processes Spawn separate process for each client client 1serverclient 2 call connect call accept call read ret connect ret accept call connect call fgets fork child 1 Client 1 blocks waiting for user to type in data call accept ret connect ret accept call fgets writefork call read child 2 write call read end read close...

12 Sequential Echo Server int 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

13 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

14 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

15 Process-Based Concurrent Server – Reaping void sigchld_handler(int sig) { while (waitpid(-1, 0, WNOHANG) > 0) ; return; }  Reap all zombie children

16 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 1 Server Process Client 2 Server Process Listening Server Process Connection Requests Client 1 dataClient 2 data Connection Requests

17 View from Server’s TCP Manager Client 1ServerClient 2 cl1>./echoclient greatwhite.ics.cs.cmu.edu srv>./echoserverp srv> connected to ( ), port cl2>./echoclient greatwhite.ics.cs.cmu.edu srv> connected to ( ), port ConnectionHostPortHostPort Listening cl cl

18 View from Server’s TCP Manager Port Demultiplexing  TCP manager maintains separate stream for each connection  Each represented to application program as socket  New connections directed to listening socket  Data from clients directed to one of the connection sockets ConnectionHostPortHostPort Listening cl cl

19 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

20 Approach #2: Multiple Threads Very similar to approach #1 (multiple processes)  but, with threads instead of processes Multithreading

21 Traditional View of a Process Process = process context + code, data, and stack shared libraries run-time heap 0 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 stack SP PC brk Process context

22 Alternate View of a Process Process = thread + code, data, and kernel context shared libraries run-time heap 0 read/write data Thread context: Data registers Condition codes Stack pointer (SP) Program counter (PC) Code and Data read-only code/data stack SP PC brk Thread (main thread) Kernel context: VM structures Descriptor table brk pointer

23 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 data Thread 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)

24 Thread Execution Single Core Processor  time slicing Multi-Core Processor  true concurrency Time Thread AThread BThread C Thread AThread BThread C (Running 3 threads on 2 cores)

25 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

26 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

27 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

28 The pthread_join() blocks the calling thread until the thread with the specified threadID exits.

29 /* 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

30 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 thread terminates) pthread_create() returns

31 Thread-Based Concurrent Echo Server int 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 */ }

32 Threaded Execution Model  Multiple threads within single process  Shared state between them Client 1 Server Client 2 Server Listening Server Connection Requests Client 1 dataClient 2 data

33 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

34 Potential Form of Unintended Sharing main thread peer 1 while (1) { int connfd = Accept(listenfd, (SA *) &clientaddr, &clientlen); pthread_create(&tid, NULL, echo_thread, (void *) &connfd); } connfd Main thread stack vargp Peer 1 stack vargp Peer 2 stack peer 2 connfd = connfd 1 connfd = *vargp connfd = connfd 2 connfd = *vargp Race! Why would both copies of vargp point to same location?

35 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

36 Experimental Results More on this later No Race Multicore server Single core laptop (Number of times each value is used)

37 Issues With Thread-Based Servers Must run “detached” to avoid memory leak.  At any point in time, a thread is either joinable or detached.  Joinable thread can be reaped and killed by other threads.  must be reaped (with pthread_join ) to free memory resources.  Detached thread cannot be reaped or killed by other threads.  resources are automatically reaped on termination.  Default state is joinable.  use pthread_detach(pthread_self()) to make detached. Must be careful to avoid unintended sharing.  For example, passing pointer to main thread’s stack Pthread_create(&tid, NULL, thread, (void *)&connfd); All functions called by a thread must be thread-safe  Stay tuned

38 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.

39 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

40 I/O Multiplexed Event Processing 10 clientfd Active Inactive Active Never Used listenfd = 3 10 clientfd listenfd = 3 Active Descriptors Pending Inputs Read

41 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

42 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