1. CPS110: Intro to processes, threads and concurrency Author: Landon Cox

2. Intro to processes  Decompose activities into separate tasks  Allow them to run in parallel  “Independently” (what does this mean?)  “without dependencies” …  Key OS abstraction: processes  Run independently of each other  Don’t have to know about others

3. Intro to processes  Remember, for any area of OS, ask  What interface does the hardware provide?  What interface/abstraction does the OS provide?  What is physical reality?  Single computer (CPUs + memory)  Execute instructions from many programs  What does an application see?  Each app “thinks” it has its own CPU + memory

4. Hardware, OS interfaces Hardware OS Applications Memory CPUs CPU, Mem Job 1 CPU, Mem Job 2 CPU, Mem Job 3

5. What is a process?  Informal  A program in execution  Running code + things it can read/write  Process ≠ program  Formal  ≥ 1 threads in their own address space  (soon threads will share an address space)

6. Parts of a process  Thread  Sequence of executing instructions  Active: does things  Address space  Data the process uses as it runs  Passive: acted upon by threads

7. Play analogy  Process is like a play performance  Program is like the play’s script Threads Address space What are the threads? What is the address space?

8. What is in the address space?  Program code  Instructions, also called “text”  Data segment  Global variables, static variables  Heap (where “new” memory comes from)  Stack  Where local variables are stored

9. Review of the stack  Each stack frame contains a function’s  Local variables  Parameters  Return address  Saved values of calling function’s registers  The stack enables recursion

10. const1=1 const2=0 const1=1 const2=0 main Example stack tmp=1 RA=0x804838c tmp=1 RA=0x804838c A RA=0x8048361 B const=0 RA=0x8048354 const=0 RA=0x8048354 C tmp=0 RA=0x8048347 tmp=0 RA=0x8048347 A 0xfffffff 0x0 Memory void C () { A (0); } void B () { C (); } void A (int tmp){ if (tmp) B (); } int main () { A (1); return 0; } void C () { A (0); } void B () { C (); } void A (int tmp){ if (tmp) B (); } int main () { A (1); return 0; } 0x8048347 0x8048354 0x8048361 0x804838c Code Stack … SP

11. const1=3 const2=0 const1=3 const2=0 main The stack and recursion bnd=3 RA=0x804838c bnd=3 RA=0x804838c A bnd=2 RA=0x8048361 bnd=2 RA=0x8048361 A bnd=1 RA=0x8048361 bnd=1 RA=0x8048361 A bnd=0 RA=0x8048361 bnd=0 RA=0x8048361 A 0xfffffff 0x0 Memory void A (int bnd){ if (bnd) A (bnd-1); } int main () { A (3); return 0; } void A (int bnd){ if (bnd) A (bnd-1); } int main () { A (3); return 0; } 0x8048361 0x804838c Code Stack … SP How can recursion go wrong? Can overflow the stack … Keep adding frame after frame

12. wrd[3] wrd[2] wrd[1] wrd[0] const2=0 wrd[3] wrd[2] wrd[1] wrd[0] const2=0 main The stack and buffer overflows b= 0x00234 RA=0x804838c b= 0x00234 RA=0x804838c cap 0xfffffff 0x0 Memory void cap (char* b){ for (int i=0; b[i]!=‘\0’; i++) b[i]+=32; } int main(char*arg) { char wrd[4]; strcpy(arg, wrd); cap (wrd); return 0; } void cap (char* b){ for (int i=0; b[i]!=‘\0’; i++) b[i]+=32; } int main(char*arg) { char wrd[4]; strcpy(arg, wrd); cap (wrd); return 0; } 0x8048361 0x804838c Code Stack … SP 0x00234 What can go wrong? Can overflow wrd variable … Overwrite cap’s RA

13. What is missing?  What process state isn’t in the address space?  Registers  Program counter (PC)  General purpose registers  Review 104 for more details

14. Multiple threads in an addr space  Several actors on a single set  Sometimes they interact (speak, dance)  Sometimes they are apart (different scenes)

16. Private vs global thread state  What state is private to each thread?  PC (where actor is in his/her script)  Stack, SP (actor’s mindset)  What state is shared?  Global variables, heap  (props on set)  Code (like lines of a play)

17. Looking ahead: concurrency  Concurrency  Having multiple threads active at one time  Thread is the unit of concurrency  Primary topics  How threads cooperate on a single task  How multiple threads can share the CPU  Subject of Project 1

18. Looking ahead: address spaces  Address space  Unit of “state partitioning”  Primary topics  Many addr spaces sharing physical memory  Efficiency  Safety (protection)  Subject of Project 2

19. Course administration  CS account requests are out  Admins should contact you w/i the next day or so  Project 0 due 9/7, groups due Friday  Post questions to the blackboard message board  Once I have your group + you have your CS account, you can submit  Project 1: The Big One  Will be due in about a month  Discussion section  F (2:50-4:05)  Any other questions?

20. Thread independence  Ideal decomposition of tasks:  Tasks are completely independent  Remember our earlier definition of independence  Is such a pure abstraction really feasible?  Word saves a pdf, starts acroread, which reads the pdf?  Running mp3 player, while compiling 110 project?  Sharing creates dependencies  Software resources (file, address space)  Hardware resources (CPU, monitor, keyboard)

21. True thread independence  What would pure independence actually look like?  (system with no shared software, hardware resources)  Multiple computer systems  Each running non-interacting programs  Technically still share the power grid …  “Pure” independence is infeasible  Tension between software dependencies,“features”  Key question: is the thread abstraction still useful?  Easier to have one thread with multiple responsibilities?

22. Consider a web server  One processor  Multiple disks  Tasks  Receives multiple, simultaneous requests  Reads web pages from disk  Returns on-disk files to requester

23. Web server (single thread)  Option 1: could handle requests serially  Easy to program, but painfully slow (why?) Client 1Client 2 WS R1 arrives Receive R1 R2 arrives Disk request 1a 1a completes R1 completes Receive R2

24. Web server (event-driven)  Option 2: use asynchronous I/O  Fast, but hard to program (why?) Client 1 Disk WS R1 arrives Receive R1 Disk request 1a 1a completes R1 completes Receive R2 Client 2 R2 arrives Finish 1a Start 1a

25. Web server (multi-threaded)  Option 3: assign one thread per request  Where is each request’s state stored? Client 1Client 2WS1 R1 arrives Receive R1 R2 arrives Disk request 1a 1a completes R1 completes Receive R2 WS2

26. Threads are useful  It cannot provide total independence  But it is still a useful abstraction!  Threads make concurrent programming easier  Thread system manages sharing the CPU  (unlike in event-driven case)  Apps can encapsulate task state w/i a thread  (e.g. web request state)

27. Where are threads used?  When a resource is slow, don’t want to wait on it  Windowing system  One thread per window, waiting for window input  What is slow?  Human input, mouse, keyboard  Network file/web/DB server  One thread per incoming request  What is slow?  Network, disk, remote user (e.g. ATM bank customer)

28. Where are threads used?  When a resource is slow, don’t want to wait on it  Operating system kernel  One thread waits for keyboard input  One thread waits for mouse input  One thread writes to the display  One thread writes to the printer  One thread receives data from the network card  One thread per disk …  Just about everything except the CPU is slow

29. Cooperating threads  Assume each thread has its own CPU  We will relax this assumption later  CPUs run at unpredictable speeds  Source of non-determinism Memory CPU Thread A CPU Thread B CPU Thread C

30. Non-determinism and ordering Time Thread A Thread B Thread C Global ordering Why do we care about the global ordering? Might have dependencies between events Different orderings can produce different results Why is this ordering unpredictable? Can’t predict how fast processors will run

31. Non-determinism example 1  Thread A: cout << “ABC”;  Thread B: cout << “123”;  Possible outputs?  “A1BC23”, “ABC123”, …  Impossible outputs? Why?  “321CBA”, “B12C3A”, …  What is shared between threads?  Screen, maybe the output buffer

32. Non-determinism example 2  y=10;  Thread A: int x = y+1;  Thread B: y = y*2;  Possible results?  A goes first: x = 11 and y = 20  B goes first: y = 20 and x = 21  What is shared between threads?  Variable y

33. Non-determinism example 3  x=0;  Thread A: x = 1;  Thread B: x = 2;  Possible results?  B goes first: x = 1  A goes first: x = 2  Is x = 3 possible?

34. Example 3, continued  What if “ x = ; ” is implemented as  x := x & 0  x := x |  Consider this schedule  Thread A: x := x & 0  Thread B: x := x & 0  Thread B: x := x | 1  Thread A: x := x | 2

35. Atomic operations  Must know what operations are atomic  before we can reason about cooperation  Atomic  Indivisible  Happens without interruption  Between start and end of atomic action  No events from other threads can occur

36. Review of examples  Print example (ABC, 123)  What did we assume was atomic?  What if “print” is atomic?  What if printing a char was not atomic?  Arithmetic example ( x=y+1, y=y*2 )  What did we assume was atomic?

37. Atomicity in practice  On most machines  Memory assignment/reference is atomic  E.g.: a=1, a=b  Many other instructions are not atomic  E.g.: double-precision floating point store  (often involves two memory operations)

38. Virtual/physical interfaces Hardware OS Applications If you don’t have atomic operations, you can’t make one.

39. Another example  Two threads (A and B)  A tries to increment i  B tries to decrement i Thread A: i = o; while (i < 10){ i++; } print “A done.” Thread B: i = o; while (i > -10){ i--; } print “B done.”

40. Example continued  Who wins?  Does someone have to win? Thread A: i = o; while (i < 10){ i++; } print “A done.” Thread B: i = o; while (i > -10){ i--; } print “B done.”

41. Example continued  Will it go on forever if both threads  Start at about the same time  And execute at exactly the same speed?  Yes, if each C statement is atomic. Thread A: i = o; while (i < 10){ i++; } print “A done.” Thread B: i = o; while (i > -10){ i--; } print “B done.”

42. Example continued  What if i++/i-- are not atomic?  tmp := i+1  i := tmp  ( tmp is private to A and B)

43. Example continued  Non-atomic i++/i--  If A starts ½ statement ahead, B can win  How? Thread A: tmpA := i + 1 // tmpA == 1 Thread B: tmpB := i - 1 // tmpB == -1 Thread A: i := tmpA // i == 1 Thread B: i := tmpB // i == -1

44. Example continued  Non-atomic i++/i--  If A starts ½ statement ahead, B can win  How?  Do you need to worry about this?  Yes!!! No matter how unlikely

45. Debugging non-determinism  Requires worst-case reasoning  Eliminate all ways for program to break  Debugging is hard  Can’t test all possible interleavings  Bugs may only happen sometimes  Heisenbug  Re-running program may make the bug disappear  Doesn’t mean it isn’t still there!

46. Constraining concurrency  Synchronization  Controlling thread interleavings  Some events are independent  No shared state  Relative order of these events don’t matter  Other events are dependent  Output of one can be input to another  Their order can affect program results

47. Goals of synchronization 1.All interleavings must give correct result  Correct concurrent program  Works no matter how fast threads run  Important for your projects! 2.Constrain program as little as possible  Why?  Constraints slow program down  Constraints create complexity

48. Conclusion  Next class: more cooperation  “How do actors interact on stage?”  Start Project 0  Simple, designed to help you with C++